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ANALYSIS OF STRUCTURES IN BIOMEDICAL
IMAGES
ANA CATARINA FREITAS DA SILVA DE JESUS
JULHO 2010
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES
Monograph of the Master Course in Biomedical Engineering Program,
Faculty of Engineering of University of Porto
Ana Catarina Freitas da Silva de Jesus
Graduated in Biochemistry (2000)
Faculty of Science of University of Porto
Graduated in Nuclear Medicine (2006)
Superior School of Allied Health Sciences
Polytechnic Institute of Porto
Supervisor:
João Manuel R. S. Tavares
Assistant Professor of the Mechanical Engineering Department
Faculty of Engineering of University of Porto
ii
SUMMARY
The purpose of this monograph is to perform a literature search on the effect of
radiation on living systems and their use as therapy to kill cancer cells. To this end, in
this work I start with a description of the checkpoints of the cell cycle and apoptosis
phenomena as well as the cancer cell characteristics, which are important to
understand the effect of radiation on cancer cells. Then, there is a description of the
biological effects of radiation and how it interacts with normal and cancer cells.
Subsequently, there is a description of the radiological technique used to kill
cancer cells, which will be studied in my thesis dissertation, called brachytherapy. In
addition, the cell cultures and the adequate means to obtain reasonable laboratory
culture of cells, without contamination, for subsequent use to study the effect of
radiation on cells, are discussed.
To finish this monograph it is performed a description of the basic concepts of
digital image processing, highlighting the increasing importance of this technique in
the image processing and analysis.
i
ACKNOWLEDGEMENTS
To Professor João Manuel R. S. Tavares for the support provided throughout
this work, particularly for guidance, support and availability, essential for the proper
and constructive development of the same.
To all of those who make possible the development of this work.
CONTENTS
CONTENTS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES iii
CHAPTER I – INTRODUCTION TO THE THEME AND REPORT ORGANIZATION 1
1.1 – Introduction 3
1.2 - Main Objectives 4
1.3 - Report Organization 4
1.4 - Major Contributions 6
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS 7
2.1 – Introduction 9
2.2 - Cell Life Cycle 10
2.2.1 – Interphase 10
2.2.2 - DNA Replication 11
2.2.3 - Cell Division 12
2.2.3.1 – Mitosis 12
2.2.3.2 – Cytokinesis 14
2.2.4 – Meiosis 14
2.3 - Progression of the cell cycle 17
2.4 - Growth characteristics of malignant cells 24
2.4.1 - Phenotypic Alterations in Cancer Cells 25
2.4.2 - Immortality of Transformed Cells in Culture 26
2.4.3 - Decreased Requirement for Growth Factors 27
2.4.4 - Loss of Anchorage Dependence 27
2.4.5 - Loss of Cell Cycle Control and Resistance to Apoptosis 28
2.5 - Cell Cycle Regulation 29
CONTENTS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES iv
2.5.1 - CDK Inhibitors 30
2.5.2 – Cyclins 31
2.5.3 - Cell Cycle Checkpoints 32
2.5.4 - Cell Cycle Regulatory Factors as Targets for Anticancer Agents 35
2.6 – Apoptosis 37
2.6.1 - Biochemical Mechanism of Apoptosis 39
2.6.2 – Caspases 42
2.6.3 - Bcl-2 Family 43
2.6.4 – Anoikis 43
2.7 - Resistance to Apoptosis in Cancer and Potential Targets for Therapy 45
2.8 – Summary 47
CHAPTER III – CANCER CELL 49
3.1 – Introduction 51
3.2 – Cancer cell 52
3.2.1 – Types of cancer 54
3.2.2 – The uniqueness of cancer 55
3.2.3 – The development of tumors 56
3.2.4 – Genetic influence on tumors 56
3.3 – Cancer through the ages 57
3.3.1 – Early discovery of carcinogens 58
3.3.2 – The use of microscopes demonstrated changes at a cellular level 58
3.4 – Modern day research and treatment 59
CONTENTS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES v
3.5 – Tissues changes in response to stimuli 59
3.5.1 – Metaplasia 60
3.5.2 – Hypertrophy and hyperplasia 63
3.5.3 – Dysplasia 64
3.6 – Feeding tumor growth by angiogenesis 65
3.7 – Characteristics of benign and malignant tumors 67
3.8 – Events that occur during the process of metastasis 70
3.8.1 – Characteristics of metastatic cells 70
3.9 – Summary 71
CHAPTER IV – RADIATION EFFECT ON NORMAL AND NEOPLASTIC TISSUES 74
4.1 – Introduction 76
4.2 – Quantities and units used in radiation dosimetry 77
4.2.1 – Radiation measurements definitions 79
4.2.2 – Quantities and units 80
4.3 – Historical perspective of radiobiology 82
4.3.1 – Law of Bergonie and Tribendeau 82
4.3.2 – Ancel and Vitemberger 83
4.3.3 – Fractionation theory 84
4.3.4 – Mutagenesis 85
4.3.5 – Effect of oxygen 85
4.3.6 – Relative biologic effectiveness 86
4.3.7 – Reproductive failure 87
CONTENTS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES vi
4.4 – Biologic effect of radiation 87
4.4.1 – Elementary phenomena 88
4.4.2 – Molecular damages 89
4.4.3 – Chromossomes irradiation 91
4.4.4 – Irradiation of macromolecules 96
4.4.5 – Dose-response relationship 99
4.4.5.1 – Linear-dose-response relationships 100
4.4.5.2 – Linear quadratic dose-response curves 101
4.4.5.3 – Dose-response curve linear quadratic 101
4.4.6 – Targeted theory 102
4.4.7 – Cell survival curves 103
4.5 - Cell Death in Mammalian Tissues 105
4.6 - Nature of Cell Populations in Tissue 107
4.7 - Cell Population Kinetics and Radiation Damage 109
4.7.1 - Growth Fraction and its significance 109
4.8 - Cell Kinetics in Normal Tissues and Tumors 111
4.9 - Models for Radiobiological Sensitivity of Neoplastic Tissues 112
4.9.1 - Hewitt Dilution Assay 113
4.9.2 - Lung Colony Assay System 116
4.10 - Tumor Growth and Tumor “Cure” Models 116
4.10.1 - Tumor Volume Versus Time 117
4.10.2 - TCD50, Tumor Cure 118
4.11 - Radiobiological Responses of Tumors 118
CONTENTS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES vii
4.12 - Hypoxia and Radiosensitivity in Tumor Cells 119
4.13 – Summary 122
CHAPTER V – CELL CULTURE AND FLOW CYTOMETRY 124
5.1 – Introduction 126
5.2 - Cell-Culture Laboratory 126
5.3 - Maintaining Cultures 127
5.3.1 – Medium 128
5.3.2 - The use of medium in analysis and alternatives 132
5.4 - Cytogenetic Analysis of Cell Lines 133
5.4.1 - The Utility of Cytogenetic Characterization 133
5.5 - Methods to Induce Cell Cycle Checkpoints 134
5.6 - Methods for Synchronizing Mammalian Cells 135
5.7 - Analysis of the Mammalian Cell Cycle by Flow Cytometry 137
5.8 – Conclusion 138
CHAPTER VI – BRACHYTHERAPY 141
6.1 – Introduction 143
6.2 – Brachytherapy 144
6.3 –Sources in brachytherapy 146
6.3.1 – Radium 146
6.3.2 - Radium substitutes 147
6.3.2 – New sources 148
6.4 – Radiobiology of brachytherapy 148
CONTENTS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES viii
6.4.1 – The four Rs of radiobiology 149
6.4.2 – Radiobiology of low dose-rate and fractioned irradiation 151
6.4.2.1 – Split-dose recovery from sub-lethal damages in mammalian cells 152
6.4.2.2 – Cell-cycle complication: a heterogeneous population 154
6.4.2.3 – Radiation affects cell-cycle progression itself 155
6.4.2.4 – Potentially lethal damage 157
6.5 – Dose-rate effects with human cells 157
6.5.1 – Time-scale of radiation action 158
6.5.2 – Mechanism of the dose-rate effect 159
6.5.3 – Dose-rate effect in human tumor cells 162
6.5.4 – Effect of irradiation on cell cycle progression 164
6.5.5 – Cell killing around an implanted radiation source 164
6.5.6 – Implications for clinical brachytherapy 167
6.6 – Predictive assays for radiation oncology 168
6.7 – Summary 169
CHAPTER VI I – BASIC CONCEPTS OF DIGITAL IMAGE PROCESSING 171
7.1 – Introduction 173
7.2 – Pre-processing evaluation of digital images 174
7.3 – Look-up tables 175
7.4 – Flat-field correction and background subtraction 177
7.5 – Image interpretation 181
7.6 – Digital image histogram adjustment 183
CONTENTS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES ix
7.7 – Spatial convolution kernels (or masks) 185
7.8 – Smoothing convolution filters (spatial averaging) 187
7.9 – Sharpening convolution filters 189
7.10 – Median filters 190
7.11 – Specialized convolution filters 191
7.12 – Unsharp mask filtering 192
7.13 – Fourier transforms 193
7.14 – Summary 195
CHAPTER VIII – CONCLUSIONS AND FUTURE WORKS 197
8.1 - Final Conclusions 199
8.2 - Future Works 200
REFERENCES 201
CHAPTER I
INTRODUCTION TO THE THEME AND REPORT ORGANIZATION
CHAPTER I – INTRODUCTION TO THE THEME AND REPORT ORGANIZATION
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 3
1.1 – INTRODUCTION
The different types of radiation applied for radiobiological research is important
for the determination of the biological effectiveness of ionizing photon radiation as a
function of photon energy. The therapeutic dose values (few Gy per daily fraction) can
be delivered in a sufficiently small irradiation duration (dose rate ≈1 Gy/min) to be
independent from repairing processes in human cells (Zeil, 2009).
Brachytherapy is a term used to describe the short distance treatment of
cancer with radiation from small, encapsulated radionuclide sources. This type of
treatment is made by placing sources directly into or near the volume to be treated.
The dose is then delivered continuously, either over a short period of time (temporary
implants) or over the lifetime of the source to a complete decay (Suntharalingam,
2002).
When cells are exposed to ionizing radiation the standard physical effects
between radiation and the atoms or molecules of the cells occur first and the possible
biological damage to cell functions follows later. The biological effects of radiation
result mainly from damage to the DNA, which is the most critical target within the cell;
however, there are also other sites in the cell that, when damaged, may lead to cell
death (Suntharalingam, 2002).
Human tumors strongly differ in radiosensitivity and radiocurability and this is
thought to stem from differences in capacity for repair of sub-lethal damage.
Radiosensitivity varies along the cell cycle, S being the most resistant phase and G2 and
M the most sensitive. Therefore, cells surviving an exposure are preferentially in a
stage of low sensitivity (G1), i.e. synchronized in a resistant cell cycle phase. They
progress thereafter together into S and then to the more sensitive G2 and M phases. A
new irradiation exposure at this time will have a larger biological effect (more cell kill)
(Mazeron, 2005).
Brachytherapy is used to treat patients with cancer cells and the irradiated cells
will be studied by me in my dissertation thesis, as the continued work from this
monograph.
One of the most widely used steps in the process of obtaining information from
images is image segmentation: dividing the input image into regions that hopefully
CHAPTER I – INTRODUCTION TO THE THEME AND REPORT ORGANIZATION
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 4
correspond to structural units in the scene or distinguish objects of interest (Russ,
1998).
1.2 – MAIN OBJECTIVES
Since the 1980s, radiation oncologists and biologists have recognized the need
for additional assays on an individual patient basis that would select the most
advantageous treatment approach. Though, it’s important to have in mind that the
cellular radiation sensitivity of the tumor may differ among individuals, even for
tumors of the same histological type. If the radiosensitivity of the individual's tumor
were precisely known, perhaps total radiation doses could be adjusted before the end
of therapy to maximize tumor response (Joslin, 2001).
The main objective of this monograph is to emphasize the importance and
application of brachytherapy in the cure of cancer patients. To do this, it’s performed a
description of the theory important to understand the underlying biochemical events
upon irradiation of the cells.
These concepts include the knowledge of the cancer cell, regulation of cell cycle
and apoptosis and the biological effects of radiation. This theoretic knowledge is
important to proceed with to my dissertation thesis which consists in the image
processing and analysis of the electron microscopic cell images of cancer irradiated
cells with the brachytherapy radiation technique.
1.3 – REPORT ORGANIZATION
It was intended to organize this document in a self-directed and self-regulating
approach to improve the access to various topics structured in eight chapters. So, it
will be described very succinctly what is treated in each remaining chapter:
CHAPTER I – INTRODUCTION TO THE THEME AND REPORT ORGANIZATION
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 5
Chapter II – Cell cycle regulation and apoptosis
In this chapter takes place a description of key concepts related to the cell cycle
checkpoints, to the behavior of the malignant cells and to the cellular death
mechanisms among other information related to the normal and malignant cells.
Chapter III – Cancer cell
This chapter focuses the characteristics of the cancer cells in comparison with
normal cells, as well as the stages that the normal cell passes to become a cancer cell.
Chapter IV – Radiation and biological effects in cancer cells
In this chapter it is presented a description of the irradiated carcinogenesis as
well as the cell death mechanisms. It is also described important issues regarding the
cellular behavior upon irradiation.
Chapter V – Cell culture and flow cytometry
In this fifth chapter it is performed an approach of some important issues
regarding the safety manipulation and maintenance of cells when performing cell
culture techniques. It is also described the methods to induce cell cycle checkpoints
and the flow cytometry technique.
Chapter VI – Brachytherapy
In this chapter a description of one of the radiation technique to kill cancer cells
is made. In addition it is mentioned the types of sources used in this radiation
technique as well as the biological events occurring in the cancer cells upon irradiation.
CHAPTER I – INTRODUCTION TO THE THEME AND REPORT ORGANIZATION
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 6
Chapter VII – Image Processing and Analysis
In this chapter it is performed a description of the basic concepts of the image
processing. This chapter is important to emphasize the image processing and
segmentation that will be performed in my thesis to extract information of the
irradiated cancer cell images. This analysis will be performed using the MATLAB image
processing toolbox.
Chapter VIII – Final Conclusions and Future Works
In the last chapter it is presented the final conclusions of the work performed,
as well as the future perspectives regarding the execution of the correspondent thesis.
1.4 – MAJOR CONTRIBUTIONS
This work consists in exposing the theory about cell cycle regulation and
checkpoints that help to understand the behavior of cells when they are irradiated
with the radiation technique named brachytherapy. This information will be helpful to
study the electron microscopy images of breast cancer cells submitted to
brachytherapy for the thesis work.
In addition a description of the image processing and analysis is made, which is
very important to understand the steps that need to the performed to be able to
extract useful information of images. It is also important to highlight the importance of
this tool as a technical aid and complement to the extraction of information on
biological and biochemical events.
CHAPTER II
CELL CYCLE REGULATION AND APOPTOSIS
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 9
2.1 - INTRODUCTION
The development of knowledge about the biochemistry and cell biology of
cancer comes from a number of disciplines. Some of this knowledge has come from
research initiated a century or more ago. There has been a flow of information about
genetics into a knowledge base about cancer, starting with Gregor Mendel and the
discovery of the principle of inherited traits and leading through Theodor Boveri’s work
on the chromosomal mode of heredity and chromosomal damage in malignant cells to
Avery’s discovery of DNA as the hereditary principle, Watson and Crick’s determination
of the structure of DNA, the human genome project, DNA microarrays, and
proteomics. Not only has this information provided a clearer understanding of the
carcinogenic process, it has also provided better diagnostic approaches and new
therapeutic targets for anticancer therapies (Ruddon, 2007).
Cancer cells contain many alterations, which accumulate as tumors develop.
Over the last 25 years, considerable information has been gathered on the regulation
of cell growth and proliferation leading to the identification of the proto-oncogenes
and the tumor suppressor genes. The proto-oncogenes encode proteins, which are
important in the control of cell proliferation, differentiation, cell cycle control and
apoptosis. Mutations in these genes act dominantly and lead to a gain in function. In
contrast the tumor suppressor genes inhibit cell proliferation by arresting progression
through the cell cycle and block differentiation. They are recessive at the level of the
cell although they show a dominant mode of inheritance. In addition, other genes are
also important in the development of tumors. Mutations leading to increase genomic
instability suggest defects in mismatch and excision repair pathways. Genes involved in
DNA repair, when mutated, also predispose the patient to developing cancer
(Macdonald, 2005).
A crucial decision in every proliferating cell is the decision to continue with a
further round of cell division or to exit the cell cycle and return to the stationary phase.
Similarly quiescent cells must make the decision, whether to remain in the stationary
phase (G0) or to enter into the cell cycle. Entry into the cycle occurs in response to
mitogenic signals and exit in response to withdrawal of these signals. To ensure that
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 10
DNA replication is complete and that any damaged DNA is repaired, cells must pass
through specific checkpoints. Tumor cells undergo uncontrolled proliferation either
due to mutations in the signal transduction pathways or because of mutations in the
regulatory mechanism of the cell cycle (Macdonald, 2005).
In this chapter, it is provided a detailed description of the cell cycle, its
progression and the cellular events involved in transforming normal cells into
malignant cells. For this purpose, the chapter starts with the explanation of the cell
cycle followed by the description of the progression of the cell cycle, the growth
characteristics of the malignant cells and the cell cycle regulation. After this, the
chapter focuses the importance of the apoptosis phenomena and ends referring the
resistance to apoptosis in cancer cells and potential targets for therapy.
2.2 – CELL LIFE CYCLE
The cell life cycle includes the changes a cell undergoes from the time it is
formed until it divides to produce two new cells. The life cycle of a cell has two stages,
an interphase and a cell division stage, Figure 2.1 (Seelev, 2004).
Figure 2.1 – Cell cycle (from (Seeley, 2004))
2.2.1 – Interphase
Interphase is the phase between cell divisions. Ninety percent or more of the
life cycle of a typical cell is spent in interphase and, during this time the cell carries out
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 11
the metabolic activities necessary for life and performs its specialized functions such as
secreting digestive enzymes. In addition, the cell prepares to divide which includes an
increase in cell size; because many cell components double in quantity, and a
replication of the cell’s DNA. Consequently, the centrioles within the centrosome are
also duplicated, when the cell divides, each new cell receives the organelles and DNA
necessary for continued functioning. Interphase can be divided into three subphases,
called G1, S, and G2. During G1 (the first gap phase) and G2 (the second gap phase), the
cell carries out routine metabolic activities. During the S phase (the synthesis phase),
the DNA is replicated (new DNA is synthesized) (Seelev, 2004).
Many cells in the human body do not divide for days, months, or even years.
These “resting” cells exit and enter the cell cycle that is called the G0 phase, in which
they remain, unless, stimulated to divide (Seelev, 2004).
2.2.2 - DNA Replication
DNA replication is the process by which two new strands of DNA are made,
using the two existing strands as templates. During interphase, DNA and its associated
proteins appear as dispersed chromatin threads within the nucleus. When DNA
replication begins, the two strands of each DNA molecule separate from each other for
some distance, Figure 2.2. Then, each strand functions as a template, or pattern, for
the production of a new strand of DNA, which is formed as new nucleotides pair with
the existing nucleotides of each strand of the separated DNA molecule. The production
of the new nucleotide strands is catalyzed by DNA polymerase, which adds new
nucleotides at the 3` end of the growing strands. One strand, called the leading strand,
is formed as a continuous strand, whereas the other strand, called the lagging strand,
is formed in short segments going in the opposite direction. The short segments are
then spliced by DNA ligase. As a result of DNA replication, two identical DNA molecules
are produced, each of them having one strand of nucleotides derived from the original
DNA molecule and one newly synthesized strand (Seelev, 2004).
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 12
Figure 2.2 – Replication of DNA (from (Seelev, 2004))
2.2.3 - Cell Division
New cells necessary for growth and tissue repair are produced by cell division.
A parent cell divides to form two daughter cells, each of which has the same amount
and type of DNA as the parent cell. Because DNA determines cell structure and
function, the daughter cells have identical structure and perform the same functions as
the parent cell. Cell division involves two major events: the division of the nucleus to
form two new nuclei, and the division of the cytoplasm to form two new cells. Each of
the new cells contains one of the newly formed nuclei. The division of the nucleus
occurs by mitosis, and the division of the cytoplasm is called cytokinesis (Seelev, 2004).
2.2.3.1 - Mitosis
Mitosis is the division of the nucleus into two nuclei, each of which has the
same amount and type of DNA as the original nucleus. The DNA, which was dispersed
as chromatin in interphase, condenses in mitosis to form chromosomes. All human
somatic cells, which include all cells except the sex cells, contain 46 chromosomes,
which are referred to as a diploid number of chromosomes. Sex cells have half the
number of chromosomes as somatic cells (Seelev, 2004).
The 46 chromosomes in somatic cells are organized into 23 pairs of
chromosomes. Twenty-two of these pairs are called autosomes. Each member of an
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 13
autosomal pair of chromosomes looks structurally alike, and together they are called a
homologous pair of chromosomes. One member of each autosomal pair is derived
from the person’s father, and the other is derived from the mother. The remaining pair
of chromosomes is the sex chromosomes. In females, the sex chromosomes look alike,
and each is called an X chromosome. In males, the sex chromosomes do not look
similar. One chromosome is an X chromosome, and the other is smaller and is called a
Y chromosome. One X chromosome of a female is derived from her mother and the
other is derived from her father. The X chromosome of a male is derived from his
mother and the Y chromosome is derived from his father (Seelev, 2004).
Mitosis is divided into four phases: prophase, metaphase, anaphase, and
telophase. Although each phase represents major events, mitosis is a continuous
process, and no discrete jumps occur from one phase to another. Learning the
characteristics associated with each phase is helpful, but a more important concept is
how each daughter cell obtains the same number and type of chromosomes as the
parent cell. The major events of mitosis are summarized in Figure 2.3 (Seelev, 2004).
Figure 2.3 – Mitosis. (1) Interphase; (2) Prophase; (3) Metaphase; (4) Anaphase; (5) Telophase; (6) Interphase,
Cytokinesis (from (Seelev, 2004))
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 14
2.2.3.2 - Cytokinesis
Cytokinesis is the division of the cytoplasm of the cell to produce two new cells
(Figure 2.3). Cytokinesis begins in anaphase continues through telophase and ends in
the following interphase. The first sign of cytokinesis is the formation of a cleavage
furrow, or puckering of the plasma membrane, which forms midway between the
centrioles. A contractile ring composed primarily of actin filaments pulls the plasma
membrane inward, dividing the cell into two halves. Cytokinesis is complete when the
membranes of the two halves separate at the cleavage furrow to form two separate
cells (Seelev, 2004).
2.2.4 – Meiosis
All cells of the body are formed by mitosis, except sex cells that are formed by
meiosis. In meiosis the nucleus undergoes two divisions resulting in four nuclei, each
containing half as many chromosomes as the parent cell. The daughter cells that are
produced by cytokinesis differentiate into gametes, or sex cells.
The gametes are reproductive cells—sperm cells in males and oocytes (egg
cells) in females. Each gamete not only has half the number of chromosomes found in
a somatic cell but also has one chromosome from each of the homologous pairs
verified in the parent cell. The complement of chromosomes in a gamete is referred to
as a haploid number. Oocytes contain one autosomal chromosome from each of the
22 homologous pairs and an X chromosome. Sperm cells have 22 autosomal
chromosomes and either an X or Y chromosome. During fertilization, when a sperm
cell fuses with an oocyte, the normal number of 46 chromosomes in 23 pairs is
reestablished. The sex of the baby is determined by the sperm cell that fertilizes the
oocyte. The sex is male if a Y chromosome is carried by the sperm cell that fertilizes the
oocyte and female if the sperm cell carries an X chromosome (Seelev, 2004).
The first division during meiosis is divided into four phases: prophase I,
metaphase I, anaphase I, and telophase I, Figure 2.4. As in prophase of mitosis, the
nuclear envelope degenerates, spindle fibers form, and the already duplicated
chromosomes become visible. Each chromosome consists of two chromatids joined by
a centromere. In prophase I, however, the four chromatids of a homologous pair of
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 15
chromosomes join together, or synapse, to form a tetrad. In metaphase I the tetrads
align at the equatorial plane and in anaphase I each pair of homologous chromosomes
separate and move toward opposite poles of the cell (Seelev, 2004).
For each pair of homologous chromosomes, one daughter cell receives one
member of the pair, and the other daughter cell receives the other member. Thus each
daughter cell has 23 chromosomes, each of which is composed of two chromatids.
Telophase I with cytokinesis is similar to telophase of mitosis and two daughter cells
are produced. Interkinesis is the phase between the formation of the daughter cells
and the second meiotic division. No duplication of DNA occurs during this phase. The
second division of meiosis also has four phases: prophase II, metaphase II, anaphase II,
and telophase II. These stages occur much as they do in mitosis, except that 23
chromosomes are present instead of 46 (Seelev, 2004).
The chromosomes align at the equatorial plane in metaphase II, and their
chromatids split apart in anaphase II. The chromatids then are called chromosomes,
and each new cell receives 23 chromosomes. In addition to reducing the number of
chromosomes in a cell from 46 to 23, meiosis is also responsible for genetic diversity
for two reasons:
A random distribution of the chromosomes is received from each
parent. One member of each homologous pair of chromosomes was
derived from the person’s father and the other member from the
person’s mother. The homologous chromosomes align randomly during
metaphase I when they split apart, each daughter cell receives some of
the father’s and some of the mother’s chromosomes. The number of
chromosomes each daughter cell receives from each parent is
determined by chance;
However, when tetrads are formed, some of the chromatids may break
apart, and part of one chromatid from one homologous pair may be
exchanged for part of another chromatid from the other homologous
pair, Figure 2.5. This exchange is called crossing-over; as a result,
chromatids with different DNA content are formed, Figure 2.5.
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 16
With random assortment of homologous chromosomes and crossing-over, the
possible number of gametes with different genetic makeup is practically unlimited.
When the distinct gametes of two individuals unite, it is virtually certain that the
resulting genetic makeup never has occurred before and never will occur again. The
genetic makeup of each new human being is unique (Seelev, 2004).
Figure 2.4 – Meiosis (from (Seelev, 2004))
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 17
Figure 2.5 – Crossing-over (from (Seelev, 2004))
2.3 - PROGRESSION OF THE CELL CYCLE
The cell cycle is controlled by a complex pattern of synthesis and degradation of
regulators together with careful control of their spatial organization in specific
subcellular compartments. In addition, checkpoint controls can modulate the
progression of the cycle in response to adverse conditions such as DNA damage.
Cells either enter G1 from G0 in response to mitogenic stimulation or follow on
from cytokinesis if actively proliferating (i.e. from M to G1). Removal of mitogens
allows them to return to G0. The critical point between mitogen dependence and
independence is the restriction point or R which occurs during G1. It is here that cells
reach the ‘point of no return’ and are committed to a round of replication (Macdonald,
2005), Figure 2.6.
Figure 2.6 – Restriction point, R (from (Griffiths, 1999))
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 18
Synthesis of the D-type cyclins begins at the G0/G1 transition and continues so
long as growth factor stimulation persists. This mitogen stimulation of cyclin D is in
part dependent on RAS activation, a role which is highlighted by the ability of anti-RAS
antibodies to block the progression of the cell cycle if added to cells prior to mitogen
stimulation. The availability of cyclin D activates CDK4 and 6 and these complexes then
drive the cell from early G1 through R to late G1; largely by regulation of RB which
exists in a phosphorylated state at the start of G1 complexed to a large number of
proteins. Cyclin D-CDK4/6 activation begins phosphorylation of Rb during early G1. This
initial phosphorylation leads to release of histone deacetylase activity from the
complex alleviating transcriptional repression. The E2F transcription factor remains
bound to Rb at this stage but can still transcribe some genes including cyclin E.
Therefore, levels of cyclin E increase and lead to activation of CDK2, which can then
complete phosphorylation of Rb. Consequently, complete phosphorylation of Rb
results in the release of E2F to activate genes required to drive cells through the G1/S
transition (Macdonald, 2005), Figure 2.7.
Figure 2.7 – Regulation of the G1 to S transition (from (Griffiths, 1999))
The CKIs also play a role in control of cell cycle progression at this stage and in
response to antimitogenic signals, oppose the activity of the CDKs and cause cell cycle
arrest. INK4 inhibitors bind to CDK4/6 to prevent cyclin D binding and CIP/KIP
inhibitors similarly inhibit the kinase activity of cyclin ECDK2, Figure 2.8. CIP/KIP
inhibitors also interact with cyclin D-CDK4/6 complexes during G1, but rather than
blocking cell cycle progression, this interaction is required for the complete function of
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 19
the complex and allows G1 progression. This interaction sequesters CIP/KIP, preventing
its inhibition of cyclin E-CDK2 and thereby facilitating its full activation to contribute to
G1 progression. In the presence of an antimitogenic signal, levels of cyclin D-CDK4/6
are reduced, CIP/KIP is released, which can then interact with and inhibit CDK2 to
cause cell cycle arrest (Macdonald, 2005).
Cells which have suffered DNA damage are prevented from entering S phase
and are blocked at G1. This process is dependent on the tumor suppressor gene p53
and p21. Activation of p53 by DNA damage results in increased p21 levels which can
then inactivate cyclin E-CDK2 to prevent phosphorylation of Rb and inhibit the release
of E2F to promote transcription of genes involved in DNA synthesis, Figure 2.8. This
causes the cell cycle to arrest in G1. Clearly, loss or mutation of p53 will lead to loss of
this checkpoint control and cells will be able to enter S phase with damaged DNA. After
cells have entered S phase, cyclin E is rapidly degraded and CDK2 is released. In S
phase, a further set of cyclins and CDKs, cyclin A-CDK2, are required for continued DNA
replication. Two A-type cyclins have been identified to date: cyclin A1 is expressed
during meiosis and in early cleavage embryos whereas cyclin A2 is present in all
proliferating cells. Cyclin A2 is also induced by E2F and is expressed from S phase
through G2 and M until prometaphase when it is degraded by ubiquitin-dependent
proteolysis (Macdonald, 2005).
Cyclin A2 binds to two different CDKs. Initially, during S phase, it is found
complexed to CDK2 following its release from cyclin E and subsequently in G2 and M it
is found complexed to CDC2 (also known as CDK1). Cyclin A2 has a role in both
transcriptional regulation and DNA replication and its nuclear localization is crucial to
its function. Cyclin A regulates the E2F transcription factor and in S phase, when E2F
directed transcription is no longer required, cyclin A directs its phosphorylation by
CDK2 leading to its degradation. This down-regulation by cyclin A2 is required for
orderly S phase progression and in its absence apoptosis occurs. Recently, cyclin A as
well as cyclin E have been shown to be regulators of centrosome replication and are
able to do so because of their ability to shuttle between nucleus and cytoplasm, Figure
2.9 (Macdonald, 2005).
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Figure 2.8 – Cell cycle arrest at G1/S, mediated by cdk inhibitors (from (Shapiro, 1999))
Figure 2.9 – Dynamics of the DNA synthesome (from (Frouin, 2003))
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The final phase of the cycle is M phase that comprises mitosis and cytokinesis.
The purpose of mitosis is to segregate sister chromatids into two daughter cells so that
each cell receives a complete set of chromosomes, a process that requires the
assembly of the mitotic spindle. Mitosis is split into a number of stages that includes
prophase, prometaphase, metaphase, anaphase and telophase (Macdonald, 2005).
Cytokinesis, the process of cytoplasmic cleavage, follows the end of mitosis and
its regulation is closely linked to mitotic progression. Mitosis involves the last of
cyclin/CDKs, cyclin B1 and CDC2 as well as additional mitotic kinases. These include
members of the Polo family (PLK1), the aurora family (aurora A, B and C) and the NIMA
family (NEK2) plus kinases implicated at the mitotic checkpoints (BUB1), mitotic exit
and cytokinesis (Macdonald, 2005).
Entry into the final phase of the cell cycle, mitosis, is signaled by the activation
of the cyclin B1-CDC2 complex also known as the M phase promoting factor or MPF.
This complex accumulates during S and G2, but is kept in the inactive state by
phosphorylation of tyrosine 15 and threonine 14 residues on CDC2 by two kinases,
WEE1 and MYT1. WEE1 is nuclear and phosphorylates tyrosine 15, whereas MYT1 is
cytoplasmic and phosphorylates threonine 14. At the end of G2, the CDC25
phosphatase is stimulated to dephosphorylate these residues thereby activating CDC2.
These enzymes are all controlled by DNA structure checkpoints which delay the onset
of mitosis if DNA is damaged. Regulation of cyclin B1-CDC2 is also regulated by
localization of specific subcellular compartments. It is initially localized to the
cytoplasm during G2, but is translocated to the nucleus at the beginning of mitosis. A
second cyclin B, cyclin B2, also exists in mammalian cells and is localized to the Golgi
and endoplasmic reticulum where it may play a role in disassembly of the Golgi
apparatus at mitosis (Macdonald, 2005).
A further checkpoint exists at the end of G2 which checks that DNA is not
damaged before entry into M. Once more p21 activation by p53 can arrest the cell
cycle as at the end of G1. In addition, the CHK1 kinase can phosphorylate CDC25 to
create a binding site for the 14–3–3 protein, a process which inactivates CDC25,
thereby preventing dephosphorylation of CDC2 and halting the cell cycle, Figure 2.10
(Macdonald, 2005).
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Tumor cells can enter mitosis with damaged DNA, suggesting a defect in the
G2/M checkpoint. Tumor cell lines have been shown to activate the cyclin B-CDC2
complex irrespective of the state of the DNA. Activation of cyclin B1-CDC2 leads to
phosphorylation of numerous substrates including the nuclear lamins, microtubule-
binding proteins, condensins and Golgi matrix components that are all needed for
nuclear envelope breakdown, centrosome separation, spindle assembly, chromosome
condensation and Golgi fragmentation respectively. During prophase, the
centrosomes—structures which organize the microtubules and which were duplicated
during G2—separate to define the poles of the future spindle apparatus, a process
regulated by several kinases including the NIMA family member NEK2, as well as
aurora A. At the same time centrosomes begin nucleating the microtubules which
make up the mitotic spindle (Macdonald, 2005).
Chromatin condensation also occurs accompanied by extensive histone
phosphorylation to produce well defined chromosomes. Nuclear envelope breakdown
occurs shortly after centrosome separation. The nuclear envelope is normally
stabilized by a structure known as the nuclear lamin which is composed of lamin
intermediate filament proteins. This envelope is broken down as a result of
hyperphosphorylation of lamins by cyclin B-CDC2 (Macdonald, 2005).
During prometaphase, the microtubules are captured by kinetochores, the
structure which binds to the centromere of the chromosome. Paired sister chromatids
interact with the microtubules emanating from opposite poles resulting in a stable
bipolar attachment. Chromosomes then sit on the metaphase plate where they
oscillate during metaphase. Once all bipolar attachments are complete anaphase is
triggered. This is characterized by simultaneous separation of all sister chromatids.
Each chromosome must be aligned in the center of the bipolar spindle such that its
two sister chromatids are attached to opposite poles. If this is correct, the anaphase-
promoting complex (APC) together with CDC20 is activated to control degradation of
proteins such as securin. This in turn activates the separin protease which cleaves the
cohesion molecules between the sister chromatids allowing them to separate. At this
stage, there is one final checkpoint, the spindle assembly checkpoint, at the
metaphase to anaphase transition, which checks the correct assembly of the mitotic
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 23
apparatus and the alignment of chromosomes on the metaphase plate. The
gatekeeper at this checkpoint is the APC complex. Unaligned kinetochores are
recognized and associate with the MAD2 and BUB proteins which can prevent
activation of APC and cell arrest at metaphase preventing exit from mitosis. In tumor
cell abnormalities of spindle formation are found, suggesting that checkpoint control is
lost (Macdonald, 2005).
Mitotic exit requires that sister chromatids have separated to opposite poles.
During telophase, nuclear envelopes can begin to form around the daughter
chromosomes and chromatin decondensation occurs. The spindle is also disassembled
and cytokinesis is completed. The control of these processes requires destruction of
both the cyclins and other kinases such as NIMA and aurora family members by
ubiquitin dependent proteolysis mediated by APC. Daughter cells can now re-enter the
cell cycle (Macdonald, 2005).
Figure 2.10 – Cell cycle regulation of cyclin dependent kinase (Cdk1) Cyclin-B (CycB) complex (from (Novák, 2010))
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2.4 - GROWTH CHARACTERISTICS OF MALIGNANT CELLS
Cancer can be characterized as a disease of genetic instability, altered cellular
behavior and altered cell–extracellular matrix interactions. These alterations lead to
dysregulated cell proliferation, and ultimately to invasion and metastasis. There are
interactions between the genes involved in these steps. For example, the genes
associated with loss of control of cell proliferation may also be involved in genetic
instability (rapidly proliferating cells have less time to repair DNA damage) and tumor
vascularization that leads to dysregulated proliferation of cells, which in turn eats up
more oxygen, creates hypoxia, and turns on HIF-1 and additional angiogenesis.
Similarly, genes involved in tumor cell invasion may also be involved in loss of growth
control (invasive cells have acquired the skills to survive in ‘‘hostile’’ new
environments) and evasion of apoptosis (less cell death even in the face of a normal
rate of cell proliferation produces more cells). The molecular genetic alterations of
cancer cells lead to cells that can generate their own growth-promoting signals are less
sensitive to cell cycle checkpoint controls, evade apoptosis, and thus have almost
limitless replication potential. This redundancy makes design of effective signal
transduction-targeted chemotherapeutic drugs that target a single pathway very
difficult indeed (Ruddon, 2007).
Cancer cells can also subvert the environment in which they proliferate.
Alterations in both cell–cell and cell–extracellular matrix interactions also occur,
leading to creation of a cancer-facilitating environment. For example, a common
alteration in epithelial carcinomas is alteration of E-cadherin expression, which is a
cell–cell adhesion molecule found on all epithelial cells. Cancer cells exhibit remarkable
plasticity and have the ability to mimic some of the characteristics of other cell types
as they progress and became less well differentiated. For example, cancer cells may
assume some of the structure and function of vascular cells. As cancer cells
metastasize, they may eventually take on a new phenotype such that the tissues of
origin may become unclear—so-called cancers of unknown primary site (Ruddon,
2007).
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2.4.1 - Phenotypic Alterations in Cancer Cells
Treatment of animals or cells in culture with carcinogenic agents is a means of
studying discrete biochemical events that lead to malignant transformation, Figure
2.11. However, studies of cell transformation in vitro have many pitfalls. These ‘‘tissue
culture artifacts’’ include overgrowth of cells not characteristic of the original
population of cultured cells (e.g., overgrowth of fibroblasts in cultures that were
originally primarily epithelial cells), selection for a small population of variant cells with
continued passage in vitro, or appearance of cells with an abnormal chromosomal
number or structure (karyotype). Such changes in the characteristics of cultured cell
populations can lead to ‘‘spontaneous’’ transformation that mimics some of the
changes seen in populations of cultured cells treated with oncogenic agents. Thus, it is
often difficult to sort out the critical malignant events from the noncritical ones
(Ruddon, 2007).
Figure 2.11 – Cellular response (from (Gil, 2006))
Although closer to the carcinogenic process in humans, malignant
transformation induced in vivo by treatment of susceptible experimental animals with
carcinogenic chemicals or oncogenic viruses or by irradiation, is even more difficult
because it is hard to discriminate toxic from malignant events and to determine what
role a myriad of factors, such as the nutritional state of the animal, hormone levels, or
endogenous infections with microorganisms or parasites, might have on the in vivo
carcinogenic events. Moreover, tissues in vivo are a mixture of cell types, and it is
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difficult to determine in which cells the critical transformation events are occurring
and what role the microenvironment of the tissue plays. Thus, most studies designed
to identify discrete biochemical events occurring in cells during malignant
transformation have been done with cultured cells, since clones of relatively
homogeneous cell populations can be studied and the cellular environment defined
and manipulated. The ultimate criterion that establishes whether cells have been
transformed, however, is their ability to form a tumor in an appropriate host animal.
The generation of immortalized ‘‘normal’’ cell lines of a given differentiated phenotype
from human embryonic stem cells, has enhanced the ability to study cells of a normal
genotype from a single source. Such cell lines may also be generated by transfection of
the telomerase gene into cells to maintain chromosomal length (Ruddon, 2007).
Over the past 60 years, much scientific effort has gone into research aimed at
identifying the phenotypic characteristics of in vitro transformed cells that correlate
with the growth of a cancer in vivo. This research has tremendously increased our
knowledge of the biochemistry of cancer cells. However, many of the biochemical
characteristics initially thought to be closely associated with the malignant phenotype
of cells in culture has subsequently been found to be dissociable from the ability of
those cells to produce tumors in animals. Furthermore, individual cells of malignant
tumors growing in animals or in humans exhibit marked biochemical heterogeneity, as
reflected in their cell surface composition, enzyme levels, immunogenicity, response to
anticancer drugs, and so on. This has made it extremely difficult to identify the
essential changes that produce the malignant phenotype (Ruddon, 2007).
2.4.2 - Immortality of Transformed Cells in Culture
Most normal diploid mammalian cells have a limited life expectancy in culture.
For example, normal human fibroblast lines may live for 50 to 60 population doublings
(the ‘‘Hayflick index’’), but then viability begins to decrease rapidly, unless they
transform spontaneously or are transformed by oncogenic agents. However, malignant
cells, once they become established in culture, will generally live for an indefinite
number of population doublings, provided the right nutrients and growth factors
(Ruddon, 2007).
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It is not clear what limits the life expectancy of normal diploid cells in culture,
but it may be related to the continual shortening of chromosomal telomeres each time
cells divide. Transformed cells are known to have elevated levels of telomerase that
maintain telomere length. Transformed cells that become established in culture also
frequently undergo karyotypic changes, usually marked by an increase in
chromosomes (polyploidy), with continual passage. This suggests that cells with
increased amounts of certain growth-promoting genes are generated and/or selected
during continual passage in culture. The more undifferentiated cells from cancers of
animals or patients also often have an atypical karyology, thus the same selection
process may be going on in vivo with progression over time of malignancy from a lower
to a higher grade (Ruddon, 2007).
2.4.3 - Decreased Requirement for Growth Factors
Other properties that distinguish transformed cells from their non transformed
counterparts are decreased density-dependent inhibition of proliferation and the
requirement for growth factors for replication in culture. Cells transformed by
oncogenic viruses have lower serum growth requirements than do normal cells. Cancer
cells may also produce their own growth factors that may be secreted and activate
proliferation in neighboring cells (paracrine effect) or, if the same malignant cell type
has both the receptor for a growth factor and the means to produce the factor, self-
stimulation of cell proliferation (autocrine effect) may occur. One example of such an
autocrine loop is the production of tumor necrosis factor-alpha (TNF-α) and its
receptor TNFR1 by diffuse large cell lymphoma. Co-expression of TNF-α and its
receptor are negative prognostic indicators of survival, suggesting that autocrine loops
can be powerful stimuli for tumor aggressiveness and thus potentially important
diagnostic and therapeutic targets.
2.4.4 - Loss of Anchorage Dependence
Most freshly isolated normal animal cells and cells from cultures of normal
diploid cells do not grow well when they are suspended in fluid or a semisolid agar gel.
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 28
However, if these cells contact with a suitable surface they attach, spread, and
proliferate. This type of growth is called anchorage-dependent growth. Many cell lines
derived from tumors and cells transformed by oncogenic agents are able to proliferate
in suspension cultures or in a semi solid medium (methylcellulose or agarose) without
attachment to a surface. This is called anchorage-independent growth and this
property of transformed cells has been used to develop clones of malignant cells. This
technique has been widely used to compare the growth properties of normal and
malignant cells. Another advantage that has been derived from the ability of malignant
cells to grow in soft agar (agarose), is the ability to grow cancer cells derived from
human tumors to test their sensitivity to chemotherapeutic agents and to screen for
potential new anticancer drugs (Ruddon, 2007).
2.4.5 - Loss of Cell Cycle Control and Resistance to Apoptosis
Normal cells respond to a variety of suboptimal growth conditions by entering a
quiescent phase in the cell division cycle, the G0 state. There appears to be a decision
point in the G1 phase of the cell cycle, at which time the cell must make a commitment
to continue into the S phase, the DNA synthesis step, or to stop in G1 and wait until
conditions are more optimal for cell replication to occur. If this waiting period is
prolonged, the cells are said to be in a G0 phase. Once cells make a commitment to
divide, they must continue through S, G2, and M to return to G1. If the cells are blocked
in S, G2, or M for any length of time, they die. The events that regulate the cell cycle
are called cell cycle checkpoints (Ruddon, 2007).
The loss of cell cycle check point control by cancer cells may contribute to their
increased susceptibility to anticancer drugs. Normal cells have mechanisms to protect
themselves from exposure to growth-limiting conditions or toxic agents by calling on
these check point control mechanisms. Cancer cells, by contrast, can continue through
these checkpoints into cell cycle phases that make them more susceptible to the
cytotoxic effects of drugs or irradiation. For example, if normal cells accrue DNA
damage due to ultraviolet (UV) or X-irradiation, they arrest in G1 so that the damaged
DNA can be repaired prior to DNA replication. Another check point in the G2 phase
allows repair of chromosome breaks before chromosomes are segregated at mitosis,
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 29
Figure 2.12. Cancer cells, which exhibit poor or absent check point controls, proceed to
replicate the damaged DNA, thus accounting for persisting and accumulating
mutations (Ruddon, 2007).
2.5 - CELL CYCLE REGULATION
Cyclin-dependent protein kinases (CDKs), of which CDC2 is only one, are crucial
regulators of the timing and coordination of eukaryotic cell cycle events. Transient
activation of members of this family of serine/threonine kinases occurs at specific cell
cycle phases (Ruddon, 2007).
Figure 2.12 - Major pathways where Plks may play a role in intra-S-phase checkpoint in mammalian systems (from
(Suqing, 2005))
In budding yeast G1 cyclins encoded by the CLN genes, interact with and are
necessary for the activation of, the CDC2 kinase (also called p34cdc2), driving the cell
cycle through a regulatory point called START (because it is regulated by the cdc2 or
start gene) and committing cells to enter S phase. START is analogous to the G1
restriction point in mammalian cells. The CDKs work by forming active heterodimeric
complexes following binding to cyclins, their regulatory subunits. CDK2, 4, and 6, and
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 30
possibly CDK3 cooperate to push cells through G1 into S phase. CDK4 and CDK6 form
complexes with cyclins D1, D2, and D3, and these complexes are involved in
completion of G1. Cyclin D–dependent kinases accumulate in response to mitogenic
signals and this leads to phosphorylation of the Rb protein. This process is completed
by the cyclin E1- and E2-CDK2 complexes. Once cells enter S phase, cyclin E is degraded
and A1 and A2 cyclins get involved by forming a complex with CDK2. There are a
number of regulators of CDK activities; where they act in the cell cycle is depicted in
Figure 2.13 (Ruddon, 2007).
Figure 2.13 - Restriction point control and the G1-S transition (from (Ruddon, 2007))
2.5.1 - CDK Inhibitors
The inhibitors of CDKs include the Cip/Kip and INK4 family of polypeptides. The
Cip/Kip family includes p21cip1, p27kip1, and p57kip2. The actions of these proteins
are complex. Although the Cip/Kip proteins can inhibit CDK2, they are also involved in
the sequestration of cyclin D-dependent kinases that facilitates cyclin E-CDK2
activation necessary for G1/S transition (Ruddon, 2007).
The INK4 proteins target the CDK4 and CDK6 kinases, sequester them into
binary CDKINK4 complexes, and liberate bound Cip/Kip proteins. This indirectly inhibits
cyclin E–CDK and promotes cell cycle arrest. The INK4-directed arrest of the cell cycle
in G1 keeps Rb in a hypophosphorylated state and represses the expression of S-phase
genes. Four INK4 proteins have been identified: p16INK4a, p15INK4b, p18INK4c, and
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p19INK4d. INKA4a loss of function occurs in a variety of cancers including pancreatic
and small cell lung carcinomas and glioblastomas. INK4a fulfills the criteria of a tumor
suppressor and appears to be the INK4 family member with the most active role in this
regard. The INK4a gene encodes another tumor suppressor protein called ARF
(p14ARF). Mice with a disrupted ARF gene have a high propensity to develop tumors,
including sarcomas, lymphomas, carcinomas, and CNS tumors. These animals
frequently die at less than 15 months of age. ARF and p53 act in the same pathway to
insure growth arrest and apoptosis in response to abnormal mitogenic signals such as
myc-induced carcinogenesis, Figure 2.14 (Ruddon, 2007).
Figure 2.14 - Regulation of the Rho pathway and the cytoskeleton by cyclin-dependent kinase (CDK) inhibitors (from
(Besson, 2004))
2.5.2 - Cyclins
The originally discovered cyclins, cyclin A and B, identified in sea urchins, act at
different phases of the cell cycle. Cyclin A is first detected near the G1/S transition and
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 32
cyclin B is first synthesized during S phase and accumulates in complexes with p34cdc2
as cells approach the G2-to-M transition. Cyclin B is then abruptly degraded during
mitosis. Thus, cyclins A and B regulate S and M phase, but do not appear to play a role
in G1 control points such as the restriction point (R point), which is the point where key
factors have accumulated to commit cells to enter S phase (Ruddon, 2007).
Three more recently discovered mammalian cyclins, C, D1, and E, are the
cyclins that regulate the key G1 and G1/S transition points. Unlike cyclins A and B,
cyclins C, D1, and E are synthesized during the G1 phase in mammalian cells. Cyclin C
levels change only slightly during the cell cycle but peak in early G1. Cyclin E peaks at
the G1–S transition, suggesting that it controls entry into S. Three distinct cyclin D
forms, D1, 2, and 3, have been discovered and are differentially expressed in different
mouse cell lineages. These D cyclins all have human counterparts and cyclin D levels
are growth factor dependent in mammalian cells: when resting cells are stimulated by
growth factors, D-type cyclin levels rise earlier than cyclin E levels, implying that they
act earlier in G1 than E cyclins. Cyclin D levels drop rapidly when growth factors are
removed from the medium of cultured cells. All of these cyclins (C, D, and E) form
complexes with, and regulate the activity of various CDKs and these complexes control
the various G1, G1–S, and G2–M transition points, Figure 2.15 (Ruddon, 2007).
Interestingly, negative growth regulators also interact with the cyclin-CDK system. For
example, TGF-b1, which inhibits proliferation of epithelial cells by interfering with G1-S
transition, reduced the stable assembly of cyclin E-CDK2 complexes in mink lung
epithelial cells, and prevented the activation of CDK2 kinase activity and the
phosphorylation of Rb. This was one of the first pieces of data suggesting that the
mammalian G1 cyclin-dependent kinases are targets for negative regulators of the cell
cycle (Ruddon, 2007).
2.5.3 - Cell Cycle Checkpoints
The role of various CDKs, cyclins, and other gene products in regulating
checkpoints at G1 to S, G2 to M, and mitotic spindle segregation have been described in
detail previously. Alterations of one or more of these checkpoint controls occur in
most, if not all, human cancers at some stage in their progression to invasive cancer. A
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 33
key player in the G1–S checkpoint system is the retinoblastoma gene Rb (Ruddon,
2007).
Figure 2.15 - Cell-cycle regulation (from (Charles, 2004))
Phosphorylation of the Rb protein by cyclin D–dependent kinase releases Rb
from the transcriptional regulator E2F and activates E2F function. Inactivation of Rb by
genetic alterations occurs in retinoblastoma and is also observed in other human
cancers, for example, small cell lung carcinomas and osteogenic sarcomas (Ruddon,
2007).
The p53 gene product is an important cell cycle checkpoint regulator at both
the G1–S and G2–M checkpoints but does not appear to be important at the mitotic
spindle checkpoint because gene knockout of p53 does not alter mitosis. The p53
tumor suppressor gene is the most frequently mutated gene in human cancer,
indicating its important role in conservation of normal cell cycle progression. One of
p53’s essential roles is to arrest cells in G1 after genotoxic damage, to allow for DNA
repair prior to DNA replication and cell division. In response to massive DNA damage,
p53 triggers the apoptotic cell death pathway. Data from short-term cell-killing assays,
using normal and minimally transformed cells, have led to the conclusion that mutated
p53 protein confers resistance to genotoxic agents (Ruddon, 2007).
The spindle assembly checkpoint machinery involves genes called bub (budding
uninhibited by benomyl) and mad (mitotic arrest deficient). There are three bub genes
and three mad genes involved in the formation of this checkpoint complex. A protein
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 34
kinase called Mps1 also functions in this checkpoint function. The chromosomal
instability, leading to aneuploidy in many human cancers, appears to be due to
defective control of the spindle assembly checkpoint. Mutant alleles of the human
bub1 gene have been observed in colorectal tumors displaying aneuploidy. Mutations
in these spindle checkpoint genes may also result in increased sensitivity to drugs that
affect microtubule function because drug-treated cancer cells do not undergo mitotic
arrest and go on to die (Ruddon, 2007).
Maintaining the integrity of the genome is a crucial task of the cell cycle
checkpoints. Two checkpoint kinases, called Chk1 and Chk2 (also called Cds1), are
involved in checkpoint controls that affect a number of genes involved in maintenance
of genome integrity. Chk1 and Chk2 are activated by DNA damage and initiate a
number of cellular defense mechanisms that modulate DNA repair pathways and slow
down the cell division cycle to allow time for repair. If DNA is not successfully mended,
the damaged cells usually undergo cell death via apoptosis. This process prevents the
defective genome from extending its paternity into daughter cells (Ruddon, 2007).
Upstream elements activating the checkpoint signaling pathways such as those
turned on by irradiation or agents causing DNA double strand breaks include the ATM
kinase, a member of the phosphatidylinositol 3-kinase (PI3K) family, which activates
Chk2 and its relative ATR kinase that activates Chk1. There is also cross talk between
ATM and ATR that mediates these responses. Chk1 and Chk2 phosphorylate CDC25A
and C, which inactivate them. In its dephosporylated state CDC25A activates the CDK2-
cyclin E complex that promotes progression through S phase. It should be noted that
this is an example of dephosphorylation rather than phosphorylation activating a key
biological function. This is in contrast to most signal transduction pathways, where the
phosphorylated state of a protein (often a kinase) is the active state and the
dephosphorylated state is the inactive one. In addition, Chk1 renders CDC25A
unstable, which also diminishes its activity. CDC25A also binds to and activates CDK1-
cyclin B, which facilitates entry into mitosis. G2 arrest induced by DNA damage induces
CDC25A degradation and, in contrast, G2 arrest is lost when CDC25A is overexpressed.
A number of proteins are now known to act as mediators of checkpoint responses by
impinging on the Chk1 and 2 pathways. These include the BRCT domain–containing
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proteins 53BP1, BRCA1, and MDC1.These proteins are involved in activation of Chk1
and Chk2 by acting through protein–protein interactions that modulate the activity of
these checkpoint kinases. In general, these modulators are thought to be tumor
suppressors (Ruddon, 2007).
Chk1 and 2 have overlapping roles in cell cycle regulation, but different roles during
development. Chk1 but not Chk2 is essential for mammalian development, as
evidenced by the early embryonic lethality of Chk1 knockout mice. Chk2-deficient mice
are viable and fertile and do not have a tumor-prone phenotype unless exposed to
carcinogens, and this effect is more evident later in life. As illustrated in Figure 2.16,
there are interactions between the Chk kinases and the p53 pathway. Chk2
phosphorylates threonine-18 or serine-20 on p53, which attenuates p53’s interaction
with its inhibitor MDM2, thus contributing to p53 stabilization and activation.
However, Chk2 and p53 only have partially overlapping roles in checkpoint regulation
because not all DNA-damaging events activate both pathways, Figure 2.16 (Ruddon,
2007).
2.5.4 - Cell Cycle Regulatory Factors as Targets for Anticancer Agents
The commonly observed defects in cell cycle regulatory pathways in cancer
cells distinguish them from normal cells and provide potential targets for therapeutic
agents. One approach is to inhibit cell cycle checkpoints in combination with DNA-
damaging drugs or irradiation. The rationale for this is that normal cells have a full
complement of checkpoint controls, whereas tumor cells are defective in one or more
of these and thus are more subject to undergoing apoptosis in response to excessive
DNA damage. This has been accomplished by combining ATM/ATR inhibitors such as
caffeine or Chk1 inhibitors in combination with DNA-damaging drugs. So far this
approach has not been demonstrated clinically, and indeed is somewhat counter
intuitive, since p53 mutant tumor cells are more resistant to many chemotherapeutic
drugs. p53 is a key player in causing cell death in drug treated, DNA-damaged cells
(one exception to that is the microtubule inhibitor paclitaxel), and active, unmutated
p53 is needed for this response (Ruddon, 2007).
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Figure 2.16 - Simplified scheme of cell-cycle checkpoint pathways induced in response to DNA damage (here
DSBs), with highlighted tumor suppressors shown in red and proto-oncogenes shown in green (from (Kastan,
2004))
Another approach is to target the cyclin dependent kinases directly. Alteration
of the G1–S checkpoint occurs in many human cancers. Cyclin D1 gene amplification
occurs in a subset of breast, esophageal, bladder, lung, and squamous cell carcinomas.
Cyclins D2 and D3 are overexpressed in some colorectal carcinomas. In addition, the
cyclin D–associated kinases CDK4 and CDK6 are over expressed or mutated in some
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 37
cancers. Mutations or deletions in the CDK4 and CDK6 inhibitor INK4 have been
observed in familial melanomas, and in biliary tract, esophageal, pancreatic, head and
neck, non small cell lung, and ovarian carcinomas. Inactivating mutations of CDK4
inhibitory modulators p15, p16, and p18 have been observed in a wide variety of
human cancers. Cyclin E is also amplified and overexpressed in some breast and colon
carcinomas and leukemias (Ruddon, 2007).
Human cancers have a variety of mutations in cell cycle regulatory genes. This
includes overexpression of D1 and E1 cyclins and CDKs (mainly CDK4 and CDK6) as
noted above. Loss of CDK inhibitory functions (mainly INK4a and 4b and Kip1) also
occurs, as does loss of Rb, one of the first tumor suppressor genes identified. Loss of
Kip1 function and overexpression of cyclin E1 occur frequently and are associated with
poor prognosis in breast and ovarian cancers (Ruddon, 2007).
The mitogen-stimulated proliferation of cells is mediated via a retinoblastoma
(Rb) pathway that involves phosphorylation of Rb, its dissociation form and activation
of the E2F family of transcription factors, and subsequent turn-on of genes involved in
G1–S transition and DNA synthesis. Disruption of this pathway by overexpression of
cyclin D1, loss of the INK4 inhibitor p16, mutation of CDK4 to a p16-resistant form, or
loss or mutation of Rb is frequently seen in cancer cells. The activation of CDK
inhibitory factors such as p16INK4 or p27kip1 and inhibition of cyclin dependent
kinases are, therefore, potential ways to interdict the overactive cell proliferation
pathways in cancer cells. Thus, inhibition of cyclins D1 and E and CDKs, especially CDK4
and CDK6, could be targets for inhibiting growth of cancers. As more knowledge of the
complicated steps in cell cycle regulation is gained, more potential targets become
available (Ruddon, 2007).
2.6 - APOPTOSIS
Apoptosis (sometimes called programmed cell death) is a cell suicide
mechanism that enables multicellular organisms to regulate cell number in tissues and
to eliminate unneeded or aging cells as an organism develops. The biochemistry of
apoptosis has been well studied in recent years, and the mechanisms are now
reasonably well understood (Ruddon, 2007).
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The apoptosis pathway involves a series of positive and negative regulators of
proteases called caspases, which cleave substrates, such as poly (ADP-ribose)
polymerase, actin and lamin. In addition, apoptosis is accompanied by the
intranucleosomal degradation of chromosomal DNA, producing the typical DNA ladder
seen for chromatin isolated from cells undergoing apoptosis. The endonuclease
responsible for this effect is called caspase-activated DNase, or CAD (Ruddon, 2007).
A number of ‘‘death receptors’’ have also been identified, they are cell surface
receptors that transmit apoptotic signals initiated by death ligands, Figure 2.17. The
death receptors sense signals that tell the cell that it is in an uncompromising
environment and needs to die. These receptors can activate the death caspases within
seconds of ligand binding and induce apoptosis within hours. Death receptors belong
to the tumor necrosis factor (TNF) receptor gene superfamily and have the typical
cystine rich extracellular domains and an additional cytoplasmic sequence termed the
death domain (Ruddon, 2007).
Figure 2.17 - Apoptosis signaling through death receptors (from (Frederik, 2002))
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The best-characterized death receptors are CD95 (also called Fas or Apo1) and
TNF receptor TNFR1 (also called p55 or CD120a). The importance of the apoptotic
pathway in cancer progression is seen when there are mutations that alter the ability
of the cell to undergo apoptosis and allow transformed cells to keep proliferating
rather than die. Such genetic alterations include the translocation of the bcl-2 gene in
lymphomas that prevents apoptosis and promotes resistance to cytotoxic drugs. Other
genes involved as players on the apoptosis stage include c-myc, p53, c-fos, and the
gene for interleukin-1b-converting enzyme (ICE). Various oncogene products can
suppress apoptosis, like the adenovirus protein E1b, ras, and n-abl (Ruddon, 2007).
Mitochondria plays a pivotal role in the events of apoptosis by at least three
mechanisms:
1) Release of proteins, e.g., cytochrome c, that triggers activation of caspases;
2) Alteration of cellular redox potential;
3) Production and release of reactive oxygen species after mitochondrial
membrane damage.
Another mitochondrial link to apoptosis is implied by the fact that Bcl-2, the
anti-apoptotic factor, is a mitochondrial membrane protein that appears to regulate
mitochondrial ion channels and proton pumps, Figure 2.18 (Ruddon, 2007).
2.6.1 - Biochemical Mechanism of Apoptosis
Multicellular organisms, from the lowest to the highest species, must have a
way to get rid of excess cells or cells that are damaged in order for the organism to
survive. Apoptosis is the mechanism that they use to do this. It is the way that the
organism controls cell numbers and tissue size and protects itself from ‘‘rogue’’ cells.
A simplified version of the apoptotic pathways can be visualized in Figure 2.19
(Ruddon, 2007).
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 40
Figure 2.18 - Apoptosis signaling through mitochondria (from (Frederik, 2002))
The death receptor–mediated pathway is turned on by members of the death
receptor superfamily of receptors including Fas receptor (CD95) and TNF receptor 1,
which are activated by Fas ligand and TNF, respectively. Interaction of these ligands
with their receptors induces receptor clustering, binding of the receptor clusters to
Fas-associated death domain protein (FADD), and activation of caspase-8, Figure 2.20.
This activation step is regulated by c-FLIP. Caspase-8, in turn, activates caspase-3 and
other ‘‘executioner’’ caspases, which induce a number of apoptotic substrates. The
DNA damage–induced pathway invokes a mitochondrial-mediated cell death pathway
that involves pro-apoptotic factors like Bax (blocked by the anti-apoptotic protein Bcl-
2). This results in cytochrome c release from the mitochondria and triggering of
downstream effects facilitating caspase-3 activation, which is where the two pathways
intersect. There are both positive and negative regulators that also interact on these
pathways (Ruddon, 2007).
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Figure 2.19 - The two main apoptotic signaling pathways (from (Frederik, 2002))
Figure 2.20 - Illustration of the main TNF receptor signaling pathways (from (Dash, 2003))
CHAPTER II – CELL CYCLE REGULATION AND APOPTOSIS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 42
2.6.2 - Caspases
Caspases are a family of cysteine proteases that are activated specifically in
apoptotic cells. This family of proteases is highly conserved through evolution all the
way from hydra and nematodes up to humans. Over 12 caspases have been identified
and although most of them appear to function during apoptosis, the function of all of
them is not yet clear. The caspases are called cysteine-proteases because they have a
cysteine in the active site that cleaves substrates after asparagines in a sequence of
asp-X, with the four amino acids amino-terminal to the cleavage site determining a
caspase’s substrate specificity (Ruddon, 2007).
The importance of the caspases in apoptosis is demonstrated by the inhibitory
effects of mutation or drugs that inhibit their activity. Caspases can either inactivate a
protein substrate by cleaving it into an inactive form or activate a protein by cleaving a
pro-enzyme negative regulatory domain. In addition, caspases themselves are
synthesized as pro-enzymes and are activated by cleavage at asp-x sites. Thus, they can
be activated by other caspases, producing elements of the ‘‘caspase cascade’’ shown
in Figure 2.21.
Figure 2.21 – Caspase activation (from (Dash, 2003))
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Also, as illustrated in Figure 2.21, caspases are activated in a number of steps
by proteolytic cleavage by an upstream caspase or by protein–protein interactions,
such as that seen for the activation of caspase-8 and the interaction of cytochrome c
and Apaf-1 in the activation of caspase-9. A number of important substrates of
caspases have been identified, including the caspase-activated DNase (CAD), noted
above, which is the nuclease responsible for the DNA ladder of cells undergoing
apoptosis. Activation of CAD is mediated by caspase-3 cleavage of the CAD-inhibitory
subunit. Caspase-mediated cleavage of other specific substrates has been shown to be
responsible for other typical changes seen in apoptotic cells, such as the cleavage of
nuclear lamins required for nuclear shrinkage and budding, loss of overall cell shape by
cleavage of cytoskeleton proteins, and cleavage of PAK2, a member of the p21-
activated kinase family, that mediates the blebbing seen in dying cells.
2.6.3 - Bcl-2 Family
Mammalian Bcl-2 was first identified as anti-apoptotic protein in lymphomas
cells. It turned out to be a homolog of an anti-apoptotic protein called Ced-9 described
in C. elegans and protects from cell death by binding to the pro-apoptotic factor Ced-4.
Similarly, in mammalian cells, Bcl-2 binds to a number of pro-apoptotic factors such as
Bax, Figure 2.22. One concept is that pro- and anti- apoptotic members of the Bcl-2
family of proteins form heterodimers, which can be looked on as reservoirs of plus and
minus apoptotic factors waiting for the appropriate signals to be released (Ruddon,
2007).
2.6.4 - Anoikis
Anoikis is a form of apoptosis that occurs in normal cells that lose their
adhesion to the substrate or extracellular matrix (ECM) on which they are growing.
Adherence to a matrix is crucial for the survival of epithelial, endothelial, and muscle
cells. Prevention of their adhesion usually results in rapid cell death, which occurs via
apoptosis. Thus, anoikis is a specialized form of apoptosis caused by prevention of cell
adhesion (Ruddon, 2007).
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 44
Figure 2.22 – Apoptotic pathways. Two major pathways lead to apoptosis: the intrinsic cell death pathway
controlled by Bcl-2 family members and the extrinsic cell death pathway controlled by death receptor signaling
(from (Zhang, 2005))
The term anoikis means ‘‘homelessness’’ in Greek and although the observation
of this phenomen occurs only with cultured cells, it is likely to occur also in vivo
because it is known that cell-cell and cell-ECM interactions are crucial to cell
proliferation, organ development, and maintenance of a differentiated state. This may
be a way that a multicellular organism protects itself from free-floating or wandering
cells (such as occurs in tumor metastasis). The basic rule for epithelial and endothelial
cells appears to be ‘‘attach or die’’. Interestedly, cells that normally circulate in the
body such as hematopoietic cells do not undergo anoikis (Ruddon, 2007).
Cell attachment is mediated by integrins, and ECM integrin interactions
transduce intracellular signaling pathways that activate genes involved in cell
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 45
proliferation and differentiation. Although the cell death pathways induced by
disruption of these cell attachment processes are not clearly worked out, cell
detachment–induced anoikis does result in activation of caspases-8 and -3 and is
inhibited by Bcl-2 and Bcl-XL, indicating some similarities to the typical apoptosis
mechanisms. In addition, integrin-ECM interaction activates focal adhesion kinase
(FAK) and attachment-mediated activation of PI3-kinase. Both of these steps protect
cells from anoikis, whereas inhibition of the PI3-kinase pathway induces anoikis
(Ruddon, 2007).
Disruption of cell-matrix interactions also turns on the JNK /p38 pathway, a
stress-activated protein kinase. The mitogen-activated kinase system may also be
involved, since caspase mediated cleavage of MEKK-1 occurs in cells undergoing
anoikis. As stated earlier, one of the hallmarks of malignantly transformed cells
growing in culture is their ability to grow in an anchorage independent manner,
whereas normal cells do not. Thus, cancer cells may develop resistance to anoikis. This
may be a way that metastatic cancer cells can survive in the bloodstream until they
seed out in a metastatic site (Ruddon, 2007).
2.7 - RESISTANCE TO APOPTOSIS IN CANCER AND POTENTIAL TARGETS FOR THERAPY
It would be a mistake to portray apoptosis as only a mechanism to kill cells
damaged by some exogenous insult such as DNA-damaging toxins, drugs, or
irradiation. Apoptosis is, in fact, a usual mechanism used by all multicellular organisms
to facilitate normal development, selection of differentiated cells that the organism
needs, and control of tissue size. For example, studies of nematodes (C. elegans), fruit
flies, and mice indicate that apoptotic-mediated mechanisms similar to those
described here are intrinsic and required for normal development. Dysfunction of
these pathway results in developmental abnormalities and disease states (Ruddon,
2007).
In the human, development of the immune system is perhaps the best example
of the role for apoptosis in normal development. In the immune system, apoptosis is a
fundamental process that regulates T- and B-cell proliferation and survival and is used
to eliminate immune cells that would potentially recognize and destroy host tissues
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 46
(‘‘anti-self ’’). Mechanisms involving Apo-1/FAS (CD95)-mediated signaling of the
caspase cascade are employed in lymphocytic cell selection. In the case of T
lymphocytes, pre-T cells are produced in the bone marrow and circulate to the thymus
where they differentiate and rearrange their T-cell receptors (TCRs). Those cells that
fail to rearrange appropriately their TCR genes, and thus cannot respond to self–major
histocompatibility complex (MHC)–peptide complexes, die by ‘‘neglect’’, Figure 2.23.
Those T cells that pass the TCR selection tests mature and leave the thymus to become
the adult peripheral T-cell pool. The mature T-cell pool thus passes through a number
of selection steps to ensure self-MHC restriction and self-tolerance. Apoptosis also is
used to delete mature peripheral T cells that are insufficiently stimulated by positive
growth signals, and this is a mechanism to downregulate, or terminate, an immune
response (Ruddon, 2007).
B lymphocytes undergo selection and maturation in the bone marrow and
germinal centers of the spleen and other secondary lymphoid organs. Those with low
antigen affinity or those autoreactive are eliminated by apoptosis. Those that pass this
test mature into memory B cells and long-lived plasma cells. The ability of lymphoid
progeny cells to avoid apoptosis may lead to lymphatic leukemias or lymphomas. In
addition, cancers develop multiple mechanisms to evade destruction by the immune
system such as a decreased expression of MHC molecules on cancer cell surfaces and
production of immunosuppressive cytokines. Several cell proliferations promoting
events take place in cancer cells as they evolve over time into growth dysregulated,
invasive, metastatic cell types. These events include activation of proliferation-
promoting oncogenes such as ras and myc, overexpression of cell cycle regulatory
factors such as cyclin D, increased telomerase to overcome cell senescence, and
increased angiogenesis to enhance blood supply to tumor tissue (Ruddon, 2007).
The cancer-related alterations in the apoptotic pathway provide a number of
cancer chemotherapeutic targets.
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 47
Figure 2.23 - The role of apoptosis in the development and function of T lymphocytes. Major pro-apoptotic and anti-
apoptotic signals/molecules (from (Zhang, 2005))
2.8 - SUMMARY
At the end of this chapter is possible to conclude that many of the controls that
govern the transition between quiescence and active cell cycling in mammals operate
in G1 phase. Loss of R point control appears to be a common, possibly even universal
step in tumor development, and a number of genetic lesions that can contribute to this
deregulation have been identified.
Loss of survival proteins can also contribute to apoptosis. The antiapoptotic
gene, BCL2, has been shown to be repressed by p53 and, therefore, contributes to
apoptosis by blocking survival signals mediated by BCL2. The choice as to whether a
cell undergoes apoptosis or cell cycle arrest and DNA repair depends on a number of
factors. Some may be independent of p53 such as extracellular survival factors, the
existence of oncogenic alterations and the availability of additional transcription
factors. However, the extent of DNA damage may also contribute to the choice by
affecting the level of activity of p53 induced. Activation of apoptosis has been
associated with higher levels of p53 than those required for cell cycle arrest which may
reflect a lower affinity of cell cycle arrest target gene promoters for p53. In addition,
the type of cell may affect the response to p53. Importantly, it is vital to identify why
transformed cells die in response to p53, whereas normal cells undergo cell cycle
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 48
arrest and DNA repair as this may be of great potential for the development of cancer
therapies (Macdonald, 2005).
This loss of cell cycle check point control by cancer cells may contribute to their
increased susceptibility to anticancer drugs. Normal cells have mechanisms to protect
themselves from exposure to growth-limiting conditions or toxic agents by calling on
these check point control mechanisms. Cancer cells, by contrast, can continue through
these checkpoints into cell cycle phases that make them more susceptible to the
cytotoxic effects of drugs or irradiation (Ruddon, 2007).
Apoptosis occurs in most, if not all, solid cancers. Ischemia, infiltration of
cytotoxic lymphocytes, and release of TNF may all play a role in this and it would be
therapeutically advantageous to tip the balance in favor of apoptosis over mitosis in
tumors, if that could be done.
Clearly, a number of anticancer drugs induce apoptosis in cancer cells but the
problem is that they usually do this in normal proliferating cells as well. Therefore, the
goal should be to manipulate selectively the genes involved in inducing apoptosis in
tumor cells, although understanding how those genes work may go a long way to
achieving this goal.
CHAPTER III
CANCER CELL
CHAPTER III – CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 51
3.1 - INTRODUCTION
Cancer is an abnormal growth of cells caused by multiple changes in gene
expression leading to dysregulated balance of cell proliferation and cell death and,
ultimately evolving into a population of cells that can invade tissues and metastasize to
distant sites, causing significant morbidity and, if untreated, death of the host
(Ruddon, 2007).
Cancer is a group of diseases of higher multicellular organisms. It is
characterized by alterations in the expression of multiple genes, leading to
dysregulation of the normal cellular program for cell division and cell differentiation.
This results in an imbalance of cell replication and cell death that favors growth of a
tumor cell population (Ruddon, 2007).
The characteristics that delineate a malignant cancer from a benign tumor are
the abilities to invade locally, to spread to regional lymph nodes, and to metastasize to
distant organs in the body (Ruddon, 2007).
Cancer cells contain many alterations which accumulate as tumors develop.
Over the last 25 years, considerable information has been gathered on the regulation
of cell growth and proliferation leading to the identification of the proto-oncogenes
and the tumor suppressor genes. The proto-oncogenes encode proteins which are
important in the control of cell proliferation, differentiation, cell cycle control and
apoptosis (MacDonald, 2005).
Mutations in these genes act dominantly and lead to a gain in function. In
contrast the tumor suppressor genes inhibit cell proliferation by arresting progression
through the cell cycle and block differentiation. They are recessive at the level of the
cell although they show a dominant mode of inheritance. In addition, other genes are
also important in the development of tumors. Mutations leading to increased genomic
instability suggest defects in mismatch and excision repair pathways. Genes involved in
DNA repair, when mutated, also predispose the patient to developing cancer, as
described in chapter 3 (MacDonald, 2005).
In this chapter is held a description of the tumor cell; the types of cancers;
ongoing research and treatments; tissue changes upon stimuli; tumor angiogenesis;
benign and malignant cell characteristics and the process of metastasis.
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The description of the tumor cell is important in this work since then, in my
thesis, I will focus on studies of cancer cells.
This chapter and the chapters three and four complement each other,
describing the steps for the formation of a tumor cell, the changes in the cell cycle and
finally the role of radiation in killing/give rise to cancer cells.
3.2 – CANCER CELL
In normal cell growth there is a finely controlled balance between growth-
promoting and growth-restraining signals such that proliferation occurs only when
required. The balance is tilted when increased cell numbers are required, for example
during wound healing and during normal tissue turnover. Differentiation of cells during
this process occurs in an ordered manner and proliferation ceases when no longer
required. In tumor cells this process is disrupted, continued cell proliferation occurs
and loss of differentiation may be found (MacDonald, 2005).
In addition the normal process of programmed cell death may no longer
operate and cancers arise from a single cell which has undergone mutation. Gene
mutations give the cell increased growth advantages compared to others and allow
them to escape normal controls on proliferation. The initial mutation will cause cells to
divide to produce a genetically homogeneous clone. In turn, additional mutations
occurs which further enhance the cells’ growth potential. These mutations give rise to
subclones within the tumor each with differing properties so that most tumors are
heterogeneous (MacDonald, 2005).
Tumors can be divided into two main groups, benign or malignant. Benign
tumors are rarely life threatening, grow within a well-defined capsule which limits their
size and maintain the characteristics of the cell of origin and are thus usually well
differentiated. Malignant tumors invade surrounding tissues and spread to different
areas of the body to generate further growths or metastases. It is this process which is
often the most life threatening. Different clones within a tumor will have differing
abilities to metastasize, a property which is genetically determined. The process of
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metastasis is likely to involve several different steps and only a few clones within a
tumor will have all of these properties (MacDonald, 2005).
Tumor cells show a number of features which differentiate them from normal
cells: (1) They are no longer as dependent on growth factors as normal cells either
because they are capable of secreting their own growth factors to stimulate their own
proliferation, a process termed autocrine stimulation, or because growth factor
receptors on the surface are altered in such a way that binding of growth factors is no
longer necessary to stimulate proliferation; (2) normal cells require contact with the
surface in the extracellular environment to be able to grow whereas tumor cells are
anchorage independent; (3) normal cells respond to the presence of other cells, and in
culture will form a monolayer due to contact inhibition, whereas tumor cells lack this
and often grow over or under each other; (4) tumor cells are less adhesive than normal
cells; (5) normal cells stop proliferating once they reach a certain density but tumor
cells continue to proliferate (MacDonald, 2005).
In the most basic sense, cancer is the abnormal, uncontrolled growth of
previously normal cells. The transformation of a cell results from alterations to its DNA
that accumulates over time. The change in the genetic information causes a cell to no
longer carry out its functions properly. A primary characteristic of cancer cells is their
ability to rapidly divide, and the resulting accumulation of cancer cells is termed a
tumor. As the tumor grows and if it does not invade the surrounding tissues, it is
referred to as being benign (Figure 3.1a). If, however, the tumor has spread to nearby
or distant tissues then it is classified as malignant (Figure 3.1b) (Almeida, 2010).
Metastasis is the breaking free of cancer cells from the original primary tumor
and their migration to either local or distant locations in the body where they will
divide and form secondary tumors (Almeida, 2010).
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Figure 3.1 – Benign vs. malignant cancers. (a) Benign tumor (b) Malignant tumor (from Almeida, 2010).
3.2.1 - Types of cancer
Cancer is not a single disease; there are over 100 identified types, all with
different causes and symptoms. To distinguish one form from another the cancers are
named according to the part of the body in which they originate. Some tumors are
identified to reflect the type of tissues they arise from, with the suffix -oma, meaning
tumor, added on. For example, myelos- is a Greek term for marrow. Thus, myeloma is
a tumor of the bone marrow, whereas hepatoma is liver cancer (hepato- = liver), and
melanoma is a cancer of melanocytes, cells found primarily in the skin that produce
the pigment melanin (Almeida, 2010).
The four major types of cancer are carcinomas, sarcomas, leukemias, and
lymphomas. Approximately 90% of human cancers are carcinomas, which arise in the
skin or epithelium (outer lining of cells) of the internal organs, glands, and body
cavities. Tissues that commonly give rise to carcinomas are breast, colorectal, lung,
prostate, and skin (Almeida, 2010). In my thesis I will study, in term of image
processing, adenocarcinomas of the prostate and breast before and after irradiation of
the cells (Figure 3.2).
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Figure 3.2 – Adenocarcinoma of the prostate (from IPO Porto, radiobiology department).
Sarcomas are less common than carcinomas and involve the transformation of
cells in connective tissue such as cartilage, bone, muscle, or fat. There are a variety of
sarcoma subtypes and they can develop in any part of the body, but most often arise in
the arms or legs. Liposarcoma is a malignant tumor of fat tissue (lipo- = fat) whereas a
sarcoma that originates in the bone is called osteosarcoma (osteo- = bone). Certain
forms of cancer do not form solid tumors. For example, leukemias are cancers of the
bone marrow, which leads to the overproduction and early release of immature
leukocytes (white blood cells). Lymphomas are cancers of the lymphatic system. This
system, which is a component of the body’s immune defense, consisting of lymph,
lymph vessels, and lymph nodes, serves as a filtering system for the blood and tissues
(Almeida, 2010).
3.2.2 – The uniqueness of cancer
While there are certain commonalities shared by cancers of a particular type,
each may be unique to a single individual. This is because of different cellular
mutations that are possible, and can depend on whether the disease is detected at an
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early or advanced stage. As a result, two women diagnosed with breast cancer may or
may not receive the same treatment (Almeida, 2010).
The impact of the disease on the individual, as well as the final outcome of the
disease, is unique in every case. Still, several types of cancers can have a similar set of
symptoms, which may be shared with several other conditions, making screening,
detection, and diagnosis a complex problem. A tumor can impact the function of the
tissue in which it resides or those in the surrounding areas. Tumors provide no useful
function themselves and may be considered “parasites”, with every step of their
advance being at the expense of healthy tissue. While most types of cancers form
tumors, many do not form discrete masses. As previously stated, leukemia is a cancer
of the blood that does not produce a tumor, but rather rapidly produces abnormal
blood cells in the bone marrow at the expense of normal blood cells (Almeida, 2010).
3.2.3 - The development of tumors
All tumors begin with mutations (changes) that accumulate in the DNA (genetic
information) of a single cell causing it and its offspring to function abnormally. DNA
alterations can be sporadic or inherited. Sporadic mutations occur spontaneously
during the lifespan of a cell for a number of reasons: a consequence of a mistake made
when a cell copies its DNA prior to dividing, the incorrect repair of a damaged DNA
molecule, or chemical modification of the DNA, each of which interferes with
expression of the genetic information. Inherited mutations are present in the DNA
contributed by the sperm and/or egg at the moment of conception. To date, 90–95%
of diagnosed cancers appear to be sporadic in nature and thus have no heredity basis.
Whether the mutations that result in a cancer are sporadic or inherited, certain genes
are altered that negatively affect the function of the cells (Almeida, 2010).
3.2.4 – Genetic influence on tumors
A link between a particular genetic mutation and one or more types of cancers
is made by analyzing and comparing the DNA of malignant tissue samples obtained
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from patients and members of families with a high incidence of a particular cancer and
comparing it to the DNA from healthy individuals. For example, a study could be
conducted in which the DNA isolated from tumor cells obtained from liver cancer
patients is analyzed and determined to possess certain versions of genes whereas
different versions of those same genes are present in the DNA of liver cells of healthy
persons. An association could then be drawn between the “bad” versions of those
genes and liver cancer (Almeida, 2010).
This type of analysis has been crucial in identifying certain versions of genes
associated with a predisposition for the development of particular forms of cancer. For
example, studies have demonstrated that there is an elevated risk of breast or ovarian
cancer associated with certain versions of the BRCA1 and/or BRCA2 genes. Another
example is retinoblastoma, a rare tumor of the eye typically found in infants and young
children, which is associated with alterations within the Rb gene (Almeida, 2010).
3.3 – CANCER THROUGH THE AGES
Although not specifically identified as such, cancer has been known for many
centuries. In fact, there is evidence of tumors in the bones of five thousand year old
mummies from Egypt and Peru. The disease itself was not very common, nor explored
or understood, because in ancient times fatal infectious diseases resulted in shorter
lifespan. Given that the vast majority of cancers are sporadic, there was less
opportunity for the accumulation of the mutations necessary to transform normal cells
into cancerous ones (Almeida, 2010).
The word “cancer” was first introduced by Hippocrates (460–370 BC), the Greek
physician and “father of medicine”. He coined the term carcinoma, from the Greek
word karcinos, meaning “crab,” when describing tumors. This is because tumors often
have a central cell mass with extensions radiating outward that mimic the shape of the
shellfish (Figure 3.3) (Almeida, 2010).
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Figure 3.3 – Cancer cell (from Almeida, 2010).
3.3.1 – Early discovery of carcinogens
Also published in 1761 was a paper by John Hill, an English physician. In it he
made the first causal link between substances in the environment and cancer when he
described a relationship between tobacco snuff and nasal cancer. This brought about
the awareness of carcinogens (chemical agents that have been demonstrated to cause
cancer). In 1775, the English surgeon Sir Percivall Pott observed and noted a high rate
of scrotal cancer among chimney sweepers. He postulated that it was caused by long-
term exposure to the chemicals in the soot-soaked ropes worn as harnesses. His
research led to studies that associated particular occupations with an increased risk of
developing specific forms of cancer – the forerunner to the field of public health and
cancer (Almeida, 2010).
3.3.2 – The use of microscopes demonstrated changes at a cellular level
The development of improved microscopes in the late nineteenth century
allowed for more thorough examinations of cells and their activities than was
previously possible. It was realized that cancer cells were different in both appearance
and behavior from normal cells within the same tissue or organ (Figure 3.4). Early
twentieth century accomplishments in the development of cell culture, new and
improved diagnostic techniques, the discovery of chemical carcinogens, and the use of
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chemotherapy (powerful anticancer drugs) all had significant impacts upon the
understanding and treatment of cancer (Almeida, 2010).
Figure 3.4 – (a) Note the abundance of the thin, sheet-like extensions from the cell bodies of the healthy cells. (b) Note the rounded appearance of the cancer cells (from Almeida, 2010).
3.4 – MODERN DAY RESEARCH AND TREATMENT
The radioactive element radium, isolated by Marie and Pierre Curie in 1898,
was found to be effective in the treatment of tumors in 1903. While both healthy and
cancerous cells are susceptible to the damage caused by X-rays, cancer cells are
inherently less able to repair the damage and recover. Once safe dosage levels were
determined, radiation therapy became a standard form of treatment for many cancers
(Almeida, 2010).
Tumor formation, growth, and metastasis reflect that the regulation of the cell
cycle is critical in maintaining the structural and functional integrity of all tissues. The
inability to control passage of a cell through each of the cycle checkpoints can result in
unwanted growth within a tissue. The growth not only can disrupt the function of that
tissue but also of those nearby. The situation becomes much more serious if cells
break free from the tumor and travel to other tissues where they may take up
residence, multiply, and create additional problems (Almeida, 2010).
3.5 – TISSUES CHANGES IN RESPONSE TO STIMULI
Our cells experience many different types of chemical and physical stimuli on
an almost constant basis. For example, our cells are exposed to both beneficial and
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harmful chemicals in the air, food, and water we take into our bodies, hormones
surging through our bloodstreams relaying messages to the cells to which they bind,
and stresses and strains are applied when we move heavy objects. The type and
strength of the stimuli cells receive or are subjected to affect the structural and
functional changes they will undergo. The cellular changes that occur in response to
stimuli are an indication of both the susceptibility to signals and the adaptability that
cells exhibit in response to changes in their environment (Almeida, 2010).
It is logical to expect that if a certain stimulus causes a cell to change in a
particular way, then the cell should revert back to its original condition upon removal
of the stimulus. The transformation that cells in a tumor have undergone is often the
result of changes brought about by certain stimuli. A unique aspect of tumor cells is
that the cellular changes remain even after the stimulus that led to their
transformation is no longer present (Almeida, 2010).
3.5.1 - Metaplasia
Epithelial cells that line certain portions of the respiratory tract are known to
undergo changes in appearance and function when exposed to noxious chemicals in
the air. The pathway of air through the respiratory tract begins in the nose or back of
the throat and travels down through the trachea or windpipe, the tube that leads from
the back of the throat to the lungs (Figure 3.5). The base of the trachea branches to
form two bronchi, one going to each of the lungs, which then progressively branch into
many smaller tubes called bronchioles that spread to all areas of the lungs. At the ends
of the bronchioles are tiny balloon-like sacs called alveoli where gas exchange between
the area and bloodstream occurs. The surface layer of the trachea, bronchi and some
of the bronchioles consists of pseudostratified columnar epithelial cells (Figure 3.6)
(Almeida, 2010).
These cells are somewhat rectangular in shape and aligned side by side in a
single layer. The term pseudostratified comes from the fact that there appears to be
more than one layer of cells present (pseudo- = false; stratified = layered) because the
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position of the nuclei in adjacent cells alternates from being centrally located to being
at the bottom of the cell(Almeida, 2010).
Figure 3.5 – Respiratory system (from Almeida, 2010).
Figure 3.6 – Pseudostratified columnar epithelium (from Almeida, 2010).
The respiratory epithelium serves a protective function. Among the columnar
cells are specialized goblet cells that secrete thick, sticky mucus that coats the
epithelium. The sticky mucus traps particulate matter in the air, such as dust and
microorganisms, preventing it from getting deeper into the lungs. The exposed surface
of a columnar epithelial cell possesses cilia, short hair like structures that beat back
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and forth to sweep the mucus and anything trapped in it upward to the back of the
throat. The material brought up by the so-called ciliary escalator can be either
swallowed and destroyed in the highly acidic environment of the stomach or
expectorated (spat out) (Almeida, 2010).
Smoke is a mixture of many different types of chemicals, liquids, and solids and
is an irritant of the respiratory epithelium. Over time, smoke paralyzes the cilia of the
respiratory epithelium, allowing mucus to build up in the airways and material to travel
deeper into the lungs. Also observed in tobacco smokers is the replacement of
pseudostratified columnar epithelium with stratified squamous epithelium (Figure 3.6).
The multiple layers of flattened cells in this form of epithelium protect underlying
tissues against abrasion. The cells in the outer layers are regularly sloughed off and
replaced by the replication of the cells in the lower layers. Stratified squamous
epithelium is normally present in the outer layer of skin and the inner lining of the
digestive tract, but not in the respiratory tract (Almeida, 2010).
The previously described condition is often exhibited in the airways of smokers.
It is an example of metaplasia, which is the change of mature and differentiated cells
from one normal cell type to another normal cell type. It is important to note that
what is abnormal about metaplastic tissue when observed under the microscope is not
the presence of abnormal cells, but rather the presence of a type of cell that is
normally found in other types of tissue. The stratified squamous epithelium that may
be present along the airway of a smoker can have a normal appearance (Almeida,
2010).
The problem is that it should not be present in that location. Metaplasia is not a
normal process that cells undergo; there must be an inciting stimulus that triggers the
structural and functional changes that occur. A typical characteristic of metaplasia is
that it is reversible – when the signal that initiated the changes is no longer present,
healthy cells should revert back to their original form. A concern arises when the
inciting stimulus that resulted in the metaplastic changes is no longer present, yet the
cells do not revert back to their normal structure and function. In some cases, the
permanent alterations are the result of genetic mutations that have negatively
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affected oncogenes and tumor suppressor genes. These types of cellular mutations
certainly enhance the likelihood that cells will become cancerous (Almeida, 2010).
3.5.2 - Hypertrophy and hyperplasia
Metaplasia is not a form of growth, which means either an increase in
individual cell size or an increase in the number of cells. The purpose of the majority of
new growth that occurs between conception and adulthood is to form the variety of
differentiated body tissues. In adults, tissues are mature in their size, structure, and
function, and the primary role of cell division is the replacement of those cells that
have either died of old age, are lost due to abrasion (occurs to outer layer of skin and
inner lining of the digestive tract), or are damaged beyond repair (Almeida, 2010).
There are, however, times when growth does occur in adults. For example, the
goal of resistance or weight training is the growth of muscle tissue. A muscle is
composed of individual muscle cells known as muscle fibers, and each fiber contains
bundles of particular proteins that are responsible for contraction and relaxation. The
lifting of heavy weights damages the protein bundles. During the recovery or repair
period, the cells destroy and replace the damaged proteins. The cells, in an attempt to
be stronger and prevent similar damage from occurring again, increase the number of
protein bundles. This form of growth, which is due to an increase in size but not
number, is known as hypertrophy (Figure 3.7a) (Almeida, 2010).
Similar to metaplasia, hypertrophic growth occurs in response to an inciting
stimulus and is reversed when that stimulus is no longer present. When resistance
training is stopped, there will be a loss in muscle size and tone since there is no longer
a need to maintain the greater number of protein bundles. Another example of growth
that occurs in adulthood is the increase in breast size that occurs during pregnancy.
This form of growth is known as hyperplasia and is the result of an increase in the
number of cells in a tissue (Figure 3.7b). The combinations and levels of hormones
produced during pregnancy act as an inciting signal for the cells of the breast’s
mammary tissue to progress through the cell cycle and divide. This growth results in
the development of mammary glands and ducts that produce milk to nourish the
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newborn child. A mother will continue to lactate (produce milk) for as long as the child
breast feeds (Almeida, 2010).
When a woman stops breast feeding, there is an absence of the inciting stimuli
(i.e., pregnancy hormones and infant suckling) that led to the development, activity,
and maintenance of the mammary tissues. The result is that the cells formed in
response to the stimuli now undergo apoptosis, effectively reverting the tissue to its
original state. Hyperplastic growth can also occur in the absence of proper stimuli. This
occurs when there is a loss of regulation at the checkpoints of the cell cycle. The most
common cause for a loss of cell cycle regulation is an accumulation of gain-of-function
mutations within proto-oncogenes, converting them into oncogenes, and/or loss-of-
function mutations in tumor suppressor genes. Mutations in caretaker tumor
suppressor genes may cause structural and functional changes that do not allow cells
to interact with one another in an organized fashion (Almeida, 2010).
3.5.3 - Dysplasia
A Pap test is often part of a woman’s routine gynecological exam. The test
entails obtaining cells from the inner surface of the cervix and the lower portion of the
uterus, followed by their examination under a microscope. Less than 5% of Pap tests
display dysplasia, a disorganized arrangement of cells, which is typically reported as
mild, moderate, or severe (Figure 3.7c). Mild cases often clear up on their own and are
typically followed up with repeat Pap tests every 3–6 months. Moderate and severe
cases require the use of treatment methods to remove the abnormal cells. The stimuli
that result in cervical dysplasia, which is most common in women between 25 and 35
years of age, are unknown, although women who are infected with the human
papilloma virus have an increased risk of exhibiting the condition (Almeida, 2010).
Dysplasia is an indication that the cells are not functioning properly, and is
considered a pre-cancerous condition. The risk associated with dysplasia is the
potential for the cells to progress to a state of neoplasia. A neoplastic growth has, in
addition to a disorganized arrangement of cells, a larger than normal number of cells
capable of dividing (Figure 3.7d) (Almeida, 2010).
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Figure 3.7 – Types of tissue growth (from Almeida, 2010).
A neoplasm is also known as a cancer or tumor because its growth is the result
of disruptions to the normal regulation of the cell cycle resulting in uncontrolled
progression through the cell cycle and cell division (Almeida, 2010).
3.6 – FEEDING TUMOR GROWTH BY ANGIOGENESIS
The formation of new blood vessels, a process known as angiogenesis (angio =
blood and lymph vessel; genesis = production), first occurs during embryonic
development and continues until early adulthood. Expansion of a blood supply is the
result of the division and proliferation of the cells of the blood vessels currently in a
tissue. Therefore, it is a form of growth. As mentioned previously, growth of new
tissue is not a regular occurrence in adults but typically occurs only during the repair of
injured tissue (Almeida, 2010).
Similar to the way that the cell cycle is regulated by balancing a set of opposing
signals from the activities of protooncogenic and tumor suppressor proteins,
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angiogenesis is under the control of competing signals from many activator and
inhibitor molecules. To date, there are more than two dozen proteins and small
molecules that have been identified as angiogenic activators and inhibitors. In adults,
the concentration of angiogenic inhibitors is higher than that of activators, thus
restricting angiogenesis. A shift in the balance so that the concentration of the
activators is higher than that of the inhibitors will have an opposite effect and result in
the formation of new blood vessels (Almeida, 2010).
Capillaries, the smallest blood vessels, are abundant in tissues to ensure that
the nearby cells are provided with a continuous supply of essential nutrients and a way
to remove the metabolic waste products. New tissue growth without a concomitant
expansion of the blood supply is limited to 1–2 mm3 in size, which is approximately the
size of the head of a pin. Tumors are able to exceed that growth limit by stimulating
angiogenesis. In an attempt to support growth, tumor cells may secrete the potent
angiogenic activator vascular endothelial growth factor (VEGF; vascular = pertaining to
vessels) (Figure 3.8a). This protein diffuses to the endothelial cells of a nearby blood
vessel. The binding of VEGF to the appropriate receptors in the outer membranes of
endothelial cells initiates a signal transduction cascade within the cells that results in
changes in gene expression and cell function. For example, the expression of proto-
oncogenes is enhanced while that of tumor suppressor genes is inhibited so that the
cells will progress through the cell cycle and divide (Almeida, 2010).
As the endothelial cells divide, they will form a bud that protrudes from the
blood vessel wall into the surrounding tissue (Figure 3.8b). As the number of
endothelial cells increases, the bud elongates and the endothelial cells produce matrix
metalloproteinases (MMPs). MMPs are enzymes that breakdown the extracellular
matrix proteins to enable the growing blood vessel to migrate between the tissue cells
toward the cancer cells. Once established, a tumor’s blood supply will grow along with
the tumor, nourishing it and removing its wastes (Figure 3.8c). Angiostatin and
endostatin are two angiogenic inhibitors that have been used in extensive animal
studies and human trials. Tests conducted with mice have indicated that the treatment
of tumors with angiogenic inhibitors are effective at inhibiting their growth and can
limit the number of secondary tumors that may form (Almeida, 2010).
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Figure 3.8 – Tumor angiogenesis. (a) Cancer cells secrete vascular endothelial growth factor (VEGF), an angiogenic
activator, which binds to VEGF receptors on endothelial cells of a capillary causing a change in gene expression
within the endothelial cells of the capillary. In response to VEGF signaling an endothelial cell will divide and secrete
matrix metalloproteinases (MMPs). (b) Many rounds of endothelial cell division produce a bud off of a capillary that
grows and forms additional branches. (c) Endothelial cell growth toward a tumor supports its growth (from Almeida,
2010).
3.7 – CHARACTERISTICS OF BENIGN AND MALIGNANT TUMORS
Neoplasms are classified into two broad categories, benign and malignant. The
classification of a tumor is most often done by a pathologist, a physician who
specializes in interpreting and diagnosing changes in bodily fluids and tissues that
occur in response to disease. The assessment of a neoplastic growth is based on a
biopsy (bio- = life; -opsy = look or appearance), a macro- and microscopic examination
of either a portion of or an entire tumor that has been surgically removed. Microscopic
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analysis provides a number of distinguishing features that are key to differentiating
between benign and malignant tissue (Almeida, 2010).
A benign tumor is noncancerous and classified as in situ, or contained solely
within the tissue in which it originated; the abnormal cells have not spread to
surrounding tissues or other areas of the body. In fact, there is typically a well-defined
border between a benign neoplastic growth and normal tissue. Benign neoplastic
growths are usually slow growing and although they are generally not life-threatening,
they can become dangerous based on their location and whether or not their growth
disrupts or interferes with normal healthy tissue functions. Their self-contained nature
is an added benefit that often allows the entire tumor to be surgically removed, unless
it is in an inoperable position, such as within an organ rather than on the surface or
adjacent to major blood vessels or the spinal cord (Almeida, 2010).
A concern with benign growths is that they can progress into the far more
serious malignant or cancerous neoplasms. Principal among the distinguishing features
of malignant tumors is that they are not contained solely within the tissue in which
they originally developed. This means that a portion of the tumor has grown into one
or more of the surrounding tissues or has spread to a distant location in the body.
Metastasis, the process by which malignant cells travel from the original (primary)
tumor to other (secondary) sites in the body, is often accomplished through the use of
either the circulatory or lymphatic systems (Figure 3.9) (Almeida, 2010).
Normal tissues consist of differentiated cells performing specific functions.
Malignant tissue typically exhibits anaplasia, the presence of undifferentiated cells that
bear no resemblance to the cells normally found in that location. The presence of
undifferentiated cells is a reflection of what is normally present during embryonic and
fetal development when tissues are going through their formative stages. Since
undifferentiated cells are involved in tissue formation they divide frequently. As a
result, malignant tissues often exhibit a high mitotic index, the ratio between the
number of cells undergoing mitosis and the total number of cells within the field of
view. This accounts for the faster growth rate of malignant tumors. Malignant tumors
are considered life-threatening because of the rapid growth and production of
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undifferentiated cells that are invasive and disruptive to the structure and function of
surrounding tissues. In addition, the anaplastic nature of malignant cells is an
important factor in the likelihood that they will metastasize and wreak similar havoc
on other locations in the body. Surgery alone is not a sufficient form of treatment for
malignant tumors because of the possibility that some of the cells have spread to
locations throughout the body. Chemotherapy, the use of toxic drugs, is a more
systemic form of treatment used to target the destruction of undetectable metastatic
cancer cells in an attempt to prevent the growth and formation of new tumors
(Almeida, 2010).
Figure 3.9 – Metastasis. (a) Neoplastic cells grow, (b) produce proteases that breakdown the basement membrane,
and then invade the surrounding tissue. (c) Malignant cells can gain access to the circulatory or lymphatic system,
and then (d) exit and take up residence elsewhere in the body. (from Almeida, 2010).
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3.8 – EVENTS THAT OCCUR DURING THE PROCESS OF METASTASIS
The structural and functional changes that occur to the cells within a tumor can
be a consequence of external growth factor signals and/or mutations to DNA. It is
common for tumors, particularly those that are malignant, to exhibit tumor
progression – the cells mutate independently of one another as they grow, thereby
generating a collection of genetically different subpopulations. The genetic differences
between cells result in their unique growth and metastatic potentials (Figure 3.10). It is
only the more potent cells that are likely to have the ability to invade the surrounding
tissues, gain access to the circulatory or lymphatic systems, travel to and invade a
tissue in a new location in the body, proliferate, stimulate angiogenesis, and form a
secondary tumor (Almeida, 2010).
Figure 3.10 – Tumor progression (from Almeida, 2010).
3.8.1 - Characteristics of metastatic cells
Approximately 90% of all human cancers are carcinomas, which mean that
epithelial cells have undergone a neoplastic transformation. All epithelial tissue is
attached to a basement membrane, a upporting layer of extracellular material
composed of a variety of glycoproteins (proteins with sugars bound to them) and
carbohydrates (Figure 3.11). The membrane provides a defining boundary between the
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epithelium and an underlying layer of connective tissue. In order for cells within a
carcinoma to invade surrounding tissue, they must be able to maneuver between
other cells of that tissue and among the extracellular matrix, as well as degrade the
basement membrane (Figure 3.9). These functions are the result of specific cellular
changes that occur during the malignant transformation and tumor progression
processes. Certain cells develop the ability to secrete proteases, the enzymes that
destroy the proteins involved in cell-to-cell and cell-to-extracellular matrix connections
as well as those of the basement membrane (Almeida, 2010).
Figure 3.11 – Basement membrane of epithelium (from Almeida, 2010).
Associated with the fixed location most cells in the body have within tissues is
an absolute requirement for anchorage dependence – they adhere themselves to
neighboring cells and the extracellular matrix. Red and white blood cells are the
exception to the rule since they circulate freely in the blood stream. The ability to
migrate through tissues depends on having a reduced need to be anchored. Malignant
cells that encounter and gain entrance to capillaries and lymphatic vessels by migrating
between their outer layer of endothelial cells can be carried to secondary tissue sites
(Figure 3.9d) (Almeida, 2010).
3.9 – SUMMARY
At the end of this chapter is possible to conclude that a neoplasm can be either
malignant, able to spread and become worse, or benign, not inclined to spread and not
likely to become worse. Although benign tumors are usually less dangerous than
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malignant tumors, they can cause problems. As a benign tumor enlarges, it can
compress surrounding tissues and impair their functions. In some cases (e.g., brain
tumors), the result can be death (Seeley, 2004).
Malignant tumors can spread by local growth and expansion or by metastasis,
which results from tumor cells separating from the main neoplasm and being carried
by the lymphatic or circulatory system to a new site, where a second neoplasm forms.
Malignant neoplasms lack the normal growth control that is exhibited by most other
adult tissues, and in many ways they resemble embryonic tissue. Rapid growth is one
characteristic of embryonic tissue, but as the tissue begins to reach its adult size and
function, it slows or stops growing completely. This cessation of growth is controlled at
the individual cell level (Seeley, 2004).
Cancer results when a cell or group of cells, for some reason, breaks away from
that control. This breaking loose involves the genetic machinery and can be induced by
viruses, environmental toxins, and other causes. The illness associated with cancer
usually occurs as the tumor invades and destroys the healthy surrounding tissues,
eliminating their functions (Seeley, 2004).
Tumors tend to acquire more aggressive characteristics as they develop, and in
1957 Foulds pointed out that tumor progression occurred in a stepwise fashion, each
step determined by the activation, mutation or loss of specific genes. Over the next
two decades biochemical and cytogenetic studies demonstrated the sequential
appearance of subpopulations of cells within a tumor, attributable, in part at least, to
changes in the genes themselves (MacDonald, 2005).
The evidence suggests that, in the majority of cases, cancers arise from a single
cell which has acquired some heritable form of growth advantage. This initiation step
is believed to be caused frequently by some form of genotoxic agent such as radiation
or a chemical carcinogen. The cells at this stage, although altered at the DNA level, are
phenotypically normal. Further mutational events involving genes responsible for
control of cell growth lead to the emergence of clones with additional properties
associated with tumor cell progression. Finally, additional changes allow the outgrowth
of clones with metastatic potential. Each of these successive events is likely to make
the cell more unstable so that the risk of subsequent changes increases. Animal
models of carcinogenesis, primarily based on models of skin cancer development in
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mice, have enabled these steps to be divided into initiation events, promotion,
malignant transformation and metastasis (MacDonald, 2005).
Although it is clear that multiple changes are necessary for tumor development,
it is not clear whether the order in which the changes occur is critical. Evidence
suggests, however, that it is the accumulation of events that is important rather than
the order in which they occur (MacDonald, 2005).
CHAPTER IV
RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELLS
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 76
4.1 - INTRODUCTION
When cells are exposed to ionizing radiation the standard physical effects
between radiation and the atoms or molecules of the cells occur first and the possible
biological damage to cell functions follows later. The biological effects of radiation
result mainly from damage to the DNA, which is the most critical target within the cell;
however, there are also other sites in the cell that, when damaged, may lead to cell
death (Suntharalingam, 2002).
Many aspects of the response of tissue systems are strongly affected by the
state of the cell in its cycle, for example, the state of oxygenation of the cell. The
supply of metabolic substrates and the removal of metabolic products also play a role
in modifying the response of tissue systems. The most significant aspect of the
radiosensitivity of a tissue or organ system centers on the state of reproductive activity
and, this proliferative state varies widely among the tissues of any mammalian species.
At one extreme are the tissues of the central nervous system, some of which rarely, if
ever, undergo division during the organism's adult life, and for which loss of clonogenic
ability is an irrelevant end point. At the other extreme are the blood forming organs,
which are proliferating at a rate approaching that of an exponentially growing, in vitro
culture (Alpen, 1998).
This chapter focuses on the most relevant aspects of radiation and provides a
detailed description of the effects of radiation on normal and neoplastic tissues. The
main objectives covered in this chapter include: knowledge about radiation dosimetry;
description of some important milestones in radiobiology, the types of cell death in
mammalian cells and undertake a relative exhaustive description of the radiation
effects in the environment. After this item, it is performed a description of the nature
of cell population in tissues and of the cell population kinetics and radiation damage.
Subsequently, the chapter focuses on the cell kinetics in normal and tumor tissues, on
the models for radiobiology sensitivity of neoplastic tissues and the tumor growth and
“cure” models. Finally, it ends with a description of the radiobiological responses,
hypoxia and radiosensitivity of the tumor cell.
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4.2 – QUANTITIES AND UNITS USED IN RADIATION DOSIMETRY
The physical interactions of the various types of ionizing radiation with living
matter are the first stage of a series of events that lead to biological changes, whose
manifestations may occur over time, until many years after irradiation occurred.
The radiation gives energy to the medium, thus inducing physical, chemical and
biological processes that will lead to the changes mentioned previously. That part of
biology that studies the chain of phenomena, from physical interaction to the external
consequences, it is called Radiobiology. Given its complexity, not yet known in detail,
many of the physic-chemical triggered the constituent molecules of living cells after
irradiation (Dendy, 2000).
The disproportion between the kinetic energy and its biological consequences
emphasizes this complexity. Indeed, if the energy transferred to the body of an animal,
subject to deadly radiation, was transformed into heat it would only raise the body
temperature of a few thousandths of a degree. However, the kinetic energy that is
transferred to the cells upon irradiation with ionizing radiation, though small, has
major implications as it is released at the molecular level (Dendy, 2000).
Ionizing radiation can then be defined as any type of radiation capable of
removing an orbital electron of an atom or may carry electrons to higher energy levels
(outer orbital), causing their activation or arousal.
Radiation can be divided into:
a) Particulate radiation (corpuscular) (Dendy, 2000):
i. Alpha particles (α) - is a particle equivalent to a
helium nucleus 2He4 (2p + 2n) and has two positive charges. Due
to its high density of ionization, the energy of the α-particle is
rapidly transferred to the medium, which makes its power of
penetration rather limited (approximately 5 cm in air or about
100 mm in soft tissue).
ii. Beta particles (β) - is a more common process
among the light nuclei, which have excess of neutrons or protons
in relation to the corresponding stable structure, Figure 4.1.
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Depending on their energy, a β-particle can go through 10 to 100
cm in air and 1 to 2 cm in biological tissue.
b) Radiation of electromagnetic waves: are high intranuclear
energies transmitted in the form of wave motion, generated by
radioactive isotopes. This emission is for the release of excess energy
from the nucleus core and/or is produced by special equipment such as
x-ray machines or linear accelerators. These waves have neither mass
nor electric charge and can be divided into (Dendy, 2000):
i. X-rays - are produced when fast-moving electrons
collide with a metal object. The kinetic energy of the electron is
transformed into electromagnetic energy. It is important to
remember that the origin of this radiation is extranuclear; that
is, is formed in the electronic layer of the atom. The function of
the X-ray machine is to provide a sufficient flow intensity of
electrons in a controlled manner, for the production of an X-ray
beam with the quality and quantity desired.
ii. Gamma (γ) radiation - are bundles of energy, of
nuclear origin, transmitted in the form of wave motion, and with
great power of penetration, Figure 4.2. This emission is intended
to release excess energy of an unstable atomic nucleus.
Figure 4.1 – Particulate radiation emission (from Jefferson, 2007).
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 79
Figure 4.2 – Penetration power of the main forms of radioactivity (from Suntharalingam, 2002).
When a beam of ionizing radiation passes through the matter, there are three
types of important physical information:
1. Their spectral energy distribution;
2. The intensity of the flow of particles;
3. The amount of energy that is released per unit mass in the area of
irradiated material(Yadunath, 2010).
The action of ionizing radiation in air can be used to evaluate the last two
physical information’s, although the measurement of radiation is complex given the
large number of units involved (Pisco, 2003).
4.2.1 – RADIATION MEASUREMENTS DEFINITIONS
i. Directly Ionizing Particles
Directly ionizing particles are charged particles that have sufficient kinetic
energy to produce ionization by collision. This energy certainly must be greater than
the minimum electron binding energy in the medium in which the interaction takes
place (Alpen, 1998).
ii. Indirectly Ionizing Particles
Indirectly ionizing particles are uncharged particles that can produce ionizing
particles through kinetic interaction with the medium or that can initiate a nuclear
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 80
transformation. For example, neutrons can interact with the medium to produce high
kinetic energy protons or, atomic nuclei through collisions or through the release of
secondary directly ionizing particles after nuclear interactions between the neutron
and a target atom (Alpen, 1998).
iii. Gamma Rays and X-Rays
Gamma rays and X-rays are electromagnetic radiations, that is, photons, of high
enough energy to produce ionization. Gamma rays are identical to X-rays in their
physical properties, but, by convention, it has become practice to call ionizing photons
produced in "machines" X-rays, whereas ionizing photons from radioactive sources are
called gamma rays (Alpen, 1998).
4.2.2 – QUANTITIES AND UNITS
Usually the exposure is a term related with the radiation source and is used to
express the intensity of radiation, from a beam of X-rays or γ rays, measuring the
ability of ionizing radiation in ionizing the air. The exposure is defined as the total
charge released per unit mass of air when all electrons released by interactions with
photons are completely stopped in air. The display units come in coulombs per
kilogram [C/kg] in the international system (SI) or roentgens [R] with 1R = 2.58 x10-4
C/kg. The exposure of a beam of X-rays or γ rays varies inversely with the square of the
distance from the source (Pisco, 2003).
The Kerma (Kinetics Energy Released in the Medium) is the kinetic energy
released in the medium, being defined as the kinetic energy transferred from neutral
particles (photons and neutrons) to charged particles (electrons and protons) when
radiation interacts with matter. The Kerma is specified in units of joules per kilogram
[J/kg]. Additionally, in air or water Kerma can replace roentgen as a measure of
exposure (Pisco, 2003).
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 81
Absorbed dose (D) translate the amount of radiation energy (E) absorbed per
unit mass (M) of the absorbing medium: , being specified in gray (G) in the
SI system and in rad (radiation absorbed dose). One gray equals 1 J of energy
deposited per kilogram and 1 rad equals 100 ergs of energy deposited per kg: 1 Gy =
100 rad, 1 rad = 10 mGy. The absorbed dose is independent of the radiation source,
being dependent of the absorbing medium, which is placed in the radiation field, so
both the absorbing medium and the location should be specified (Pisco, 2003).
The factor-f is a conversion factor between exposure and absorbed dose,
determined by the relationship between the absorbed dose (D) and exposure
(X): where f is the conversion factor from roentgen to rad (Pisco, 2003).
The linear energy transfer (LET) is the energy absorbed by the medium per unit
of the traversed distance [keV/mm]. The high LET radiation is more effective in
producing biological damage than low LET radiation. When considering the biological
effect of radiation, the total amount of energy absorbed (dose) and the effectiveness
of radiation in causing biological damage (LET) should be considered parameters
(Pisco, 2003).
The dose equivalent (H) quantifies the biological damage resulting from the
deposition of ionizing radiation in tissues and is mainly used in radiation protection. It
is defined as the absorbed dose (D) multiplied by the quality factor (QF) of the
radiation . The quality factor depends on the LET value: for sources with
low LET (electrons, beta particles, X-rays and γ rays) QF=1, for sources with high LET
(protons, neutrons and α particles) QF can reach the value 20. The dose equivalent is
expressed in sievert (Sv) in the SI system and in rems: 1 Sv=100 rem and 1 rem= 10
mSv (Pisco, 2003).
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 82
4.3 – HISTORICAL PERSPECTIVE OF RADIOBIOLOGY
Three incidents triggered the beginning of radiobiology: Wilhelm Conrad
Roentgen's discovery of X-rays in 1895; Henri Becquerel's observance of rays being
given off by a uranium-containing substance in 1896 (Marie Curie subsequently would
call this radioactivity); the discovery of radium by Pierre and Marie Curie in 1898
(Forshier, 2008).
Early radiobiology observations included skin erythema (radiation induced skin
reddening), epilation (radiation induced hair loss), and anemia. Because of unshielded
fluoroscopic apparatus, radiologists had to have fingers amputated, and compared
with other doctors, had superior incidence of leukemia (Forshier, 2008).
The first United States X-rays fatality occurred in 1906. Clarence Daly, an
assistant of Thomas Edison, had collaborated with him in producing the fluoroscope
and fluorescent screens. In working long days, Daly was subjected to doses above
modern lifetime limits. In Edison´s day, shielding was seldom used for personnel or x-
ray tubes (Forshier, 2008).
The early observations of Becquerel, the Curies, and early radiologists sparked
much research into the effects of radiation exposure on biological processes.
Beginning in the early 1900s through the 1950s and 1960s, many theories were
developed to define and explain these effects (Forshier, 2008).
4.3.1 – Law of Bergonie and Tribendeau
In 1906 two Frenchmen, J. Bergonie and L. Tribendeau, exposed rodent
testicles to X-rays, and observed the effect of radiation. These researchers selected the
testicles since this organ contains both mature cells (spermatozoa), which execute the
organ´s principal function and immature cells (spermatogonia and spermatocytes),
whose only purpose is t evolve into mature, functional cells. Not only do these cells´
functions differ, but their rate of mitosis also differs. The spermatogonia (immature)
cells divide frequently, whereas the spermatozoa (mature) cells do not divide. After
exposing the testicles to radiation, Bergonie and Tribendeau noticed that the
immature cells were injured at doses lower than mature cells. Supported by these
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 83
founds, they proposed a law describing the radiation sensitivity for all body cells. Their
law maintains that actively mitotic and undifferentiated cells are most susceptible to
damage from ionizing radiation (Forshier, 2008).
The law of Bergonie and Tribondeau states that:
1. Steam cells are more radiosensitive than mature cells. The more mature
a cell is, the more radioresistant.
2. Younger tissues and organs are more radiosensitive than older tissues
and organs.
3. The higher the metabolic activity of a cell, the more radiosensitive it is.
4. The greater the proliferation and growth rate for tissues, the greater the
radiosensitivity.
This law informs us that compared to a child or mature adult, the fetus is
most radiosensitive (Forshier, 2008).
4.3.2 – Ancel and Vitemberger
In 1925 the law of Bergonie and Tribondeau was modified by P. Ancel and P.
Wittenberg. These researchers suggested that the intrinsic susceptibility of damage by
any cell by ionizing radiation is the same, but that the timing of manifestation of
radiation-produced damage varies according to the types of cells. In experiments on
mammals, they determined that there are two factors, which affect the appearance of
radiation damage to the cell (Forshier, 2008):
1. The amount of biological stress the cell receives.
2. Pre- and post-irradiation conditions that the cell is exposed to.
Ancel and Vitemberger theorized that the most significant biological stress on
the cell is the need to division. In their terms, a given dose of radiation will cause the
same degree of damage to all cells (the innate susceptibility is comparable for all cells)
but only if and when a cell divides will damage be demonstrated (Forshier, 2008).
Although Ancel and Vitemberge communicate radiosensitivity differently than
Bergonie and Tribondeau, they do agree with them by placing a significant emphasis
on the amount of mitotic activity involved (Forshier, 2008).
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 84
In the 1920s researchers learned that the process of ionization in tissues was
the cause of biologic results. The two mechanisms recognized were, Figure 4.3:
Direct ionization along charged particles tracks caused direct effects
(original ionization occurs directly on the targeted molecule).
The formation of free radicals caused indirect effects (original ionization
occurs with water, and transfers ionization to target molecule).
Figure 4.3 –Radiation path with low and high LET (from Yadunath, 2010).
4.3.3 – Fractionation Theory
The 20s and 30s brought the fractionation theory from France. Ram testicles
were exposed to large doses of ionizing radiation. Even though the rams could be
sterilized with one large dose, this quantity of radiation also caused the skin next to
the ram´s scrotum to have a reaction. However, it was found, that if the large dose was
fractioned (smaller doses spread out over a period of time, Figure 4.4), the animals
would still become sterile, but with considerably less damage to their skin (Forshier,
2008).
Figure 4.4 – Effect of fractionation (from Cherry, 2006).
X-rays
Neutrons
Cel
l su
rviv
al
Dose (Gy)
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 85
4.3.4 – Mutagenesis
In 1927, H. Muller discovered that ionizing radiation produced mutations
through his experiments with fruit flies. His finding is termed mutagenesis. This
researcher found that the radiation-induced mutations were the same as those
produced by nature. Irradiating the fruit flies did not create any unusual effects, but
the frequency of mutations was intensified. This implies that the effects of ionizing
were not unique to radiation, that is, they could have been caused by things other
than radiation (Forshier, 2008).
4.3.5 – Effect of Oxygen
The oxygen effect was the subject of experimentation during the 1940s and
1950s. Oxygen is a radiosensitizer because it increases the cell-killing effects of a given
dose of radiation. This occurs as a result of the increased production of free radicals
when ionizing radiation is delivered in the presence of oxygen (Forshier, 2008).
The oxygen effect is known as Oxygen Enhancement Ratio (OER) and
numerically defined as (Forshier, 2008):
It is necessary the presence of oxygen in order to form free radicals during
ionization of water. Without free radicals, hydrogen peroxide is not formed, and thus
cell damage is reduced (Forshier, 2008).
The OER is dependent on LET, being more pronounced for low LET radiation
and less effective for high LET radiation. Because of the physical differences between
high and low LET radiations the quantity of damage done by high LET radiation would
be beyond repair. Thus, having oxygen present would not intensify the response to
radiation the same magnitude, as would be the case with the low LET radiation,
(Forshier, 2008), Figure 4.5.
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 86
Figure 4.5 - Oxygen effect of the LET (from Forshier, 2008).
4.3.6 – Relative Biologic Effectiveness
The relative effect of LET is quantitatively described by the relative biologic
effectiveness (RBE). RBE is a comparison of a dose of test radiation to a dose of 250
keV X-ray which produces the same biologic response, being expressed as follows
(Forshier, 2008):
The RBE measures the biological effectiveness of radiation having different LET
values. Factors which influence RBE include radiation type, cell or tissue kind,
physiologic conditions, biologic result being examined, and the radiation dose rate. In
comparing LET and RBE, as LET increases, RBE increases also, Figure 6. Accordingly, low
LET radiations have a low RBE, and high LET radiation have a high RBE (Forshier, 2008).
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 87
Figure 4.6 - RBE versus LET (from Forshier, 2008).
4.3.7 – Reproductive Failure
In 1956, Puck and Marcus exposed human uterine cervix cells to varying doses
of radiation. Thus, experimentally determined reproductive failure by counting the
number of colonies formed by these irradiated cells (Forshier, 2008).
As scientists began to research the effects of radiation exposure had on
biological processes, there occurred a need to measure the levels of radiation causing
specific effects. Units of measurement were developed to quantify radiation levels and
thus track the effects of exposure to varying the levels of exposure (Forshier, 2008).
4.4 – BIOLOGIC EFFECTS OF RADIATION
Ionizing radiation transferring energy to biologic systems causes, in several
successive stages, biological consequences.
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 88
4.4.1 - Elementary phenomena
Physic interactions - these interactions vary according to the nature of
radiation. Photons (X-rays or gamma rays) put in motion, during collisions with atoms
of the medium, electrons to which they transfer whole or part of its energy in the
form of kinetic energy. This kinetic energy is expended in the course of interactions
with electrons belonging to atoms of the medium, and is subjected to the electric
field of the incident electron (excitation and ionization) and these interactions
"consume" an energy that was subsequently transferred, through ionizing radiation,
to the medium. This phase is very brief (Pedroso Lima, 2003).
The proportion of these modified atoms is minimal; however, they are
grouped along the path of electrons, at varying distances. Although the amount of
energy transferred is low, its concentration along these trajectories into bundles of
energy whose value is relatively high (10 to 100 eV) gives a great efficiency. The other
charged particles (alpha particles, protons set in motion when the interactions of
neutrons with the medium) cause the same excitations and ionizations along its own
path but at much shorter distances (the beam energy has the same value but is
closer) (Pedroso Lima, 2003).
Radiochemical phenomena – in a second phase, equally brief, the ionization of
an atom within a molecule leads, in general, to her collapse and the fragments
formed, called radicals. These radicals are chemically very "active" since they are able
to react with other molecules initiating various chemical reactions. The effect is direct
when the ionization directly affects the molecules damaging them, or indirect when
the injury is caused by free radicals formed during the breakdown of water molecules
- radiolysis - which constitute the bulk of biologic systems, Figure 4.7. The final
product of the water radiolysis is the formation of an ion pair, H+ and OH-, and two
free radicals H* and OH*. These chemical species are highly reactive radicals that play
an important role and constitute the starting point of many molecular changes. Half
of the molecular injuries are due to direct effect and the other half to indirect effect.
When the distance between ionizations is short, these radicals react with each other
and their concentration along the trajectories increases the effectiveness of these
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 89
reactions. Therefore, for the same amount of energy absorbed the number of
damaged molecules is larger (Pedroso Lima, 2003).
Figure 4.7 – Radiolysis of water molecules (Forshier, 2008).
The human body is composed of 80% water so the irradiation of water is
involved in most interactions involving radiation.
4.4.2 – Molecular Damages
All biological molecules can be altered but the consequences vary according to
the importance of the injured molecules.
The molecules of deoxyribonucleic acid or DNA are those where the damage is
more serious, since each has a specific role. Indeed, each cell “contains” information
that will allow, according to a preconceived plan, the appropriate development and
reaction to external events. The genetic material, or hereditary material, consists of
DNA molecules that are the backbone of information. Damage to DNA molecules is
the key mechanism of ionizing radiation action (Suntharalingam, 2002).
Deoxyribonucleic acid or DNA - The structure is the same in all living species.
The elementary constituent of DNA molecule is the nucleotide, which is formed by a
phosphate group, a sugar (desoxirribose) and one base. A DNA molecule consists of
two long strands or fibers of millions of nucleotides that form as a ladder whose bars
would be the sequence of alternating sugars and phosphate groups, and the lanes
Radicais livres
OH*, H*
Iões
OH- , H-
Iões
HOH+ , HOH-
Água
H2O
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 90
would be two bases joined together. This string wraps around its axis
(Suntharalingam, 2002), Figure 4.8.
Figure 4.8 - Deoxyribonucleic acid molecule (DNA) (from Seeley, 2004).
There are four different types of bases: adenine (A), cytosine (C), guanine (G)
and thymidine (T), that are always available to form these dishes, paired as follows:
adenine with thymine and guanine with cytosine, forming these four pairs possible:
AT, TA, GC and GC. The order of bases in one of the molecule chains determines,
unambiguously, the order of bases on the other chain (from Seeley, 2004).
The orders in which the bases follow one other constitute one code, and a
sequence of three bases (triplets) determines the amino acid that is present in the
encoded protein. The set of "triplets" that encode a protein constitutes a gene. Thus,
a gene consists of a sequence of several thousand of nucleotides coding for a specific
protein that is synthesized from the information contained in this gene. This
information is transmitted to the cytoplasm by a messenger RNA (from Seeley, 2004).
Besides the coding genes, other DNA sequences constitute regulatory systems
that, for example, activate ('operators' genes) or repress ('repressive' genes) the
expression of a gene and, consequently, the synthesis of the protein encoded by this
gene. These regulatory mechanisms, not yet fully understood, and to which are
certainly devoted numerous DNA sequences, definitely explain the disproportion
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 91
between the number of genes identified and the total of DNA mass (from Seeley,
2004).
When radiation interacts with the cell, the ionization and excitation may occur
in the macromolecules (for example, DNA) or in the medium they are (for example,
water). Depending on the site of interaction, the effect is called direct or indirect
(Suntharalingam, 2002).
The direct interaction occurs when a first ionization reaches a macromolecule
(for example, DNA, RNA, proteins or enzymes). If the macromolecule is ionized it is
considered abnormal or mutated (Suntharalingam, 2002).
The indirect interaction occurs if the initial ionization takes place at a distance
not critical of the macromolecule and, then takes place the transfer of ionization
energy to the molecule (Suntharalingam, 2002).
4.4.3 – Chromosomes Irradiation
In multicellular species the DNA molecules are the heart of chromosomes,
which are essential constituents of the cell nucleus. Each species is characterized by
the number and shape of chromosomes. Human cells, for example, have 46
chromosomes grouped in 23 pairs of 2 chromosomes apparently identical (size,
shape, etc.), one from the mother and one from the father. One of these 23 pairs is
unique, the sex chromosomes. In women, the two chromosomes called X are similar;
in men, they look different: one, called X, is similar to the woman and the other called
Y, is much smaller (Forshier, 2008).
Each chromosome consists of a single molecule of DNA coiled about itself and
closely tied to protein molecules, Figure 4.9. The length of a chromosome is about 0.1
μm, but if the DNA molecule was stretched it would have a length of approximately 4
cm that is 400 000 times longer. Its width is 2 nm (Forshier, 2008).
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 92
Figure 4.9 – DNA Compaction (from Seeley, 2004).
At the time of cell division, chromosomes can be observed microscopically. It
is then possible to count them and identify them by size, shape and after stained, by
structure. In this phase, it is feasible to study chromosomal abnormalities (Forshier,
2008).
When the chromosomes are irradiated, the radiation interaction can be direct
or indirect. The result of any of the interactions is a mutation. The mutation causes a
visible chromosomal change, Figure 4.10, and represents critical lesions in DNA
(Forshier, 2008).
Figure 4.11 depicts the effects of a single mutation caused by an irradiation in
the G1 phase of the cell cycle.
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 93
Figure 4.10 - Chromossome Aberrations (from Forshier, 2008).
Figure 4.11 - Simple Mutation in G1 phase (from Forshier, 2008).
Radiochemical effects on DNA and chromosomes - the main damage caused by
ionizing radiation are:
Modifications of bases: adenine, cytosine, guanine and
specially thymidine. A pair of bases may be absent or replaced by
A. O
ne
bre
ak in
on
e
chro
mo
sso
me
B. T
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bre
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on
e
chro
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C. O
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tw
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mo
sso
mes
Tran
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D. O
ne
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ak in
tw
o
chro
mo
sso
mes
Dic
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Quebra Recombinação Replicação Separação Anafásica
Irradiation
in G1 phase Causes chromatid
breaks
Visualization
in M phase
Replication in S and pass
through the G2 phase
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 94
another. The modification of the order or nature of the bases causes
an alteration of the information carried by the gene (point mutation).
Changes in DNA conformation: a rupture in one of the
two chains (these lesions are easily repairable - Figure 4.12) or rupture
of the two chains (these injuries are difficult to repair).
Figure 4.12 – Schematic of the repair mechanism of excision-resynthesis (from Forshier, 2008).
Other intersection injuries (cross links) form links, for
example, between two DNA strands, DNA-DNA bonds, or between one
nucleic acid and protein: DNA-binding protein.
Several remodeling of chromosome structure: a single or
multiple rupture can cause the loss of a fragment - deletion - if it
occurs in S phase of the cell cycle takes place the replication of the
deletion and, in metaphase the abnormal chromosome looks like the
normal chromosome despite lacking information in the terminal
region; the setting of this fragment on another chromosome is called
translocation. When two chromosomes exchange pieces thus speaks of
reciprocal translocation. This fragment can then re-weld abnormally on
the same chromosome (inversion). If in G1 phase of the cell cycle
occurs two mutations in the same chromosome, the two ends can
3´
5´
3´
5´
3´
5´
3´
5´
3´
5´
5´
3´
5´
3´
5´
3´
5´
3´
5´
3´
Endonuclease
Polimerase Χ
Ligase
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 95
'weld' and form a 'ring' chromosome; chromossomes can weld again in
a more complex way, forming dicentric chromosomes, etc. The quality
of the adhesion ability of damaged chromosomes is a determining
factor in the joining of the chromatid, Figure 4.13 (Forshier, 2008).
Figure 4.13 - Chromosomal aberrations of multiple mutations (from Forshier, 2008).
The morphological study of chromosomes in a cell is of enormous practical
interest, since the number of abnormalities is dose dependent and can assess their
importance from relatively low values (0.25 Gy). Chromosomal aberrations may make
it impossible the balance of genetic material between two daughter cells and, lead to
cell death at the time of cell division or non-viability of the two daughter cells
(Forshier, 2008).
Cellular constituents other than DNA can suffer injuries caused by ionizing
radiation, for example, fatty acids that make up cell membranes, proteins such as
enzymes, involved in all stages of cellular life. Although, if the points of impact of
ionizing radiation are numerous, the biological effect resulting primarily from lesions
in the DNA molecules (Forshier, 2008).
Molecular DNA repair – there are many chemical or physical agents that can
damage DNA and so life would not be possible without repair. The total length of DNA
Ring
Dicentric
Irradiation
in G1 phase
Causes
chromatid
breaks
Bind during
S phase
Visualization
in M phase
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 96
contained in the cells of the body (2m in length per cell) is about 60 million
kilometers. Per day is born 200 billion cells, the length of DNA synthesized is 400
million kilometers a day. These long and narrow molecules are fragile and therefore
the thermal agitation and chemical reactions harm it constantly. Consequently,
becomes, necessary systems to repair the damage, particularly, due to external factors
such as ultraviolet radiation, chemicals, etc. If the injuries were permanent, the impact
of a single photon at the level of a molecule would result in an irreversible alteration
of a gene, and the smallest radiation harm. Thanks to the final repair the damage is
much less than the damage we would get if were added all the molecular lesions
(Forshier, 2008).
When the injuries are related to one of the two chains, restoration is usually
full; however, if the two chains simultaneously suffer injury, repair mechanisms are
more complex and can result in a repair deficient, that is, has an error (mutation)
whose consequences can lead to cell death or start their cancer (Forshier, 2008).
Biological consequences of irradiation - At the cell level the effects are multiple.
Irreversible DNA injuries can result: a mutation, that is, a final modification of the
property inherited from the cell; loss of viability, that is, the inability to divide and give
rise to normal daughter cells, which can express themselves since the first cell division
or during the first five divisions (delayed death). The proportion of surviving cells, i.e.,
is, those which retained the ability to divide many times, it decreases with the dose.
Besides depending on the dose, this ratio also depends on the nature of radiation and
dose rate, as well as suffering from the influence of the environment of cells (for
example, the decrease of oxygen content increases radiation resistance) (Forshier,
2008).
4.4.4 – Irradiation of Macromolecules
The occurrence of molecular derangements or injuries may be classified either
effects on macromolecules or effects on water. Irradiating macromolecules gives very
different results when compared to the irradiation of water, Figure 4.14. If
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 97
macromolecules are exposed to ionizing radiation in vitro (outside the body or cell), a
significant dose of radiation is needed to produce a measurable effect. Irradiating
macromolecules in vivo (inside the living cell) shows that when cells are in their natural
conditions, they are much more radiosensitive (Forshier, 2008).
Figure 4.14 – Macromolecules mutations (from Forshier, 2008).
The three primary effects of irradiating macromolecules in vitro include main-
chain scission, cross-linking and point lesions.
Main chain scission - occurs when the thread or backbone of the long-chain
molecule is broken. This results in the long-chain molecule being reduced to
numerous smaller molecules, which can still be macromolecular in nature. Not only
the size of the macromolecule is reduced, but its viscosity (thickness) is also reduced
(Forshier, 2008).
Cross-linking - certain macromolecules have spurlike extensions off the main
chain. Others develop these spurs after being irradiated. After being irradiated, these
spurs can as if they had a sticky material on their ends. This stickiness causes the
macromolecule to connect to another macromolecule, or to another section of the
same molecule. This is termed cross-linking. Viscosity is increased by radiation-
produced molecular cross-linking (Forshier, 2008).
Point lesions - Irradiating macromolecules may result in disturbance of single
chemical bonds, which create molecular lesions or point lesions. Point lesions may
CHAPTER IV – RADIATION AND BIOLOGICAL EFFECTS IN CANCER CELL
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 98
cause slight molecular changes, which in turn cause the cell to function incorrectly
(Forshier, 2008).
At low doses of radiation, point lesions are regarded to be the cellular
radiation damage that is responsible for late radiation effects, which are observed at
the whole-body level (Forshier, 2008).
Irradiating macromolecules may result in either death of the cell or late
effects. Throughout the cell cycle proteins are constantly being created, and occur in
greater number than nucleic acids. Abundant copies of unique protein molecules
always exist in the cell. These factors allow protein to be more radioresistant than the
nucleic acids. In addition, numerous copies of m-RNA and t-RNA exist in the cell,
although they are not as plentiful as the protein molecules. Conversely, DNA
molecules, having their distinctive base arrangements, are not so frequent. Because
of this, DNA molecule is considered the most radioresistant macromolecule. RNA
radiosensitivity is midway between that of DNA and protein macromolecules
(Forshier, 2008).
There can be visible chromossome abnormalities or cytogenetic damage if the
radiation damage to the DNA is intense enough. DNA can be injured without
producing visible chromosomal aberrations. Even though this damage is reversible, it
can lead to death of the cell, and ultimately destroy tissues and organs (Forshier,
2008).
Metabolic activity can also be affected by DNA damage. The primary
characteristic of radiation-induced malignancies is the uncontrolled reproduction of
cells. If germ cells receive DNA damage, the response may be detected in future
offspring (Forshier, 2008).
Figures 4.15 A-D, illustrate DNA aberrations that are reversible types of
damage. They may involve the sequence of bases being changed, thus changing the
triplet code of codons. This is considered a genetic mutation at the molecular level
(Forshier, 2008).
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Damage type shown in Figure 4.15-E also involves the change of or loss of a
base. This type of damage destroys the triplet code as well, and may not be
reversible; this is considered a genetic mutation (Forshier, 2008).
These molecular genetic mutations are termed point mutations, and are
common with low LET radiation. Point mutations may be either of minor or major
significance to the cell. A key effect of these point mutations would be the genetic
code being incorrectly transferred to daughter cells (Forshier, 2008).
Figure 4.15 – DNA aberrations (from Forshier, 2008).
4.4.5– Dose-response relationship
The dose-response relationships, also referred to as dose-response curves, are
graphical correlations between the observed effects (response) from radiation and
dose of radiation received, Figure 4.16 (Forshier, 2008).
A base deletion
B base substitution
C Hydrogen bond disruption
or or
Low LET (x-ray)
Single strand
or
High LET (α particle)
Double strand
(not repairable)
E D
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Dose-response curves differ in two ways (Forshier, 2008):
They are either linear or non-linear;
They are either threshold or nonthreshold.
Figure 4.16 - Dose-response Relationship (from Forshier, 2008).
Linear means that an observed response is directly proportional to the dose. On
the other hand, nonlinear means that an observed response is not directly
proportional to the dose. Additionally, threshold assumes that there is a radiation level
reached below which there would be no effects observed, and nonthreshold assumes
that any radiation dose produces an effect. Diagnostic radiology is primarily concerned
with linear, nonthreshold dose-response relationships (Forshier, 2008).
4.4.5.1 - Linear-Dose-Response Relationships
Since dose-response relationship A and B intersect the dose (x) axis at either
zero or on the y-axis, they are considered linear, nonthreshold, Figure 4.16.
All linear dose-response relationships exhibit an effect regardless of the dose.
This is demonstrated by relationship A. Even at zero doses, A exhibits a measurable
response (RA). This RA is termed the ambient or natural response. Dose-response
relationships C and D intercept the dose axis (x) at a dose value greater than zero.
Thus, C and D are considered linear, threshold. At doses below the respective C and D
values, o response would be anticipated (Forshier, 2008).
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4.4.5.2 - Linear Quadratic Dose-Response Curves
In 1980, the Committee on the Biological Effects of Ionizing Radiation (BEIR
Committee) concluded that the effects of low doses of low LET radiation follow a
linear, quadratic dose-response relationship, Figure 4.17. At low doses, the curve is
linear and at high doses, the curve becomes curvilinear and is no threshold (Forshier,
2008).
The portion of the curve where increases in dose shows no or light increase in
the effect is named as the toe. The shoulder is considered the area of the curve in
which a leveling off occurs, again demonstrating no or little increase off or flattened
(Forshier, 2008).
In 1990, with 10 additional years of human data, the BEIR committee revised its
radiation risk estimates and adopted the linear, nonthreshold dose-response
relationship as most relevant (Forshier, 2008).
Current radiation dose-response curve, there is a nonlinear relationship
between dose and effect, meaning that the effect is not directly proportional to the
dose (Forshier, 2008).
Figure 4.17 – Linear quadratic dose-response curve (from Forshier, 2008).
4.4.5.3 - Dose-response curve linear quadratic
The sigmoid dose-response curve s applied predominantly to the high dose
effects observed in radiotherapy, Figure 4.18. Sigmoid means S-shaped. There is
usually a threshold below which no observable effects occur. With a sigmoid dose-
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response curve, there is a nonlinear relationship between dose and effect, meaning
that the effect is not directly proportional to dose (Forshier, 2008).
Figure 4.18 – Sigmoid dose-response curve (from Forshier, 2008).
4.4.6 – Targeted Theory
As cells contain a profusion of molecules, radiation damage to these molecules
is not likely to result in significant cell injury because additional molecules are present
to assist in cell survival. However, there are molecules that are not in abundance that
are considered necessary for the cell survival. Irradiating these could have serious
consequences, because there may not be others available to maintain cell survival.
This idea of a sensitive critical molecule is the foundation for the targeted theory.
According to the targeted theory, there will be cell death only if cell´s targeted
molecules is inactivated. It is theorized that DNA is the critical molecular target
(Forshier, 2008).
The target is regarded to be the area of the cell that contains the target
molecule. Because radiation interaction with cells is random, target interactions also
occur randomly. The radiation shows no favoritism toward the targeted molecules
(Forshier, 2008).
When a target is irradiated, this is considered a hit. Both direct and indirect
effects cause hits, Figure 4.19. Direct versus indirect hits are not distinguishable.
With low LET radiation in an anoxic condition, chances for a hit on the targeted
molecule are low because of the large distances between ionizing events (Forshier,
2008).
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In an aerobic state with low LET radiation, the indirect effect is intensified, as
more free radicals are formed, and the volume of action surrounding each interaction
enlarged. This increases the likelihood of a hit (Forshier, 2008).
Using high LET radiation, ionization distances are so close together that there is
a high probability that a direct hit will take place, probably even higher than for the
low LET, indirect effect (Forshier, 2008).
Adding oxygen to high LET radiation will probably not result in additional hits,
as the high LET has already produced the maximum number of hits possible (Forshier,
2008).
4.4.7 – Cell Survival Curves
Cellular sensitivity studies began in the middle 1950s with Puck and Marcus.
They performed in vitro studies using HeLa cells. Their initial study was on failure of
reproduction in which they exposed HeLa cells to differing radiation doses and then
totaled the number of colonies formed (Forshier, 2008).
Figure 4.19 – Targeted theory (from Forshier, 2008).
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This information may be illustrated graphically by plotting the radiation doses
on a linear scale on the x-axis, and plotting the fraction of surviving cells on a
logarithmic scale on the y-axis. This graphical representation of the relationship
between the dose and surviving cells is a survival curve (Forshier, 2008).
It was stated previously that radiation interaction is random in nature.
Therefore, it must be determined how many hits are necessary to cause cell death.
This may be demonstrated using a cell survival curve (Forshier, 2008).
The model most used is the linear-quadratic model, whereby there are two
components responsible for cell death: a dose-proportional, which corresponds to the
initial portion of the curve and represents the cell death caused by lethal damage, and
another component proportional to the square of the dose, related to the steeper
region of the curve and is linked to the deaths caused by lethal damage, potentially
lethal damage, and especially the accumulation of sub-lethal damage (Suntharalingam,
2002).
In simple cells such as bacteria, if there are additional hits to the same cell,
these hits do not matter. In complex cells such as human cells, it is theorized that in
order to cause cell death, more than one hit is required (Forshier, 2008).
The graphs of simple versus complex cells are very different, Figure 4.20. Graph
A represents a survival curve for simple cells, represented by a straight line. Graph B
represents a survival curve for complex cells, represented by a line which displays a
shouldered area where effects are not apparent until some targets have received
enough multiple hits to be killed. The targeted theory can be used to explain this
shoulder section of the curve (Forshier, 2008).
The shoulder of the cell survival curve shows that some damage must accrue
before there can be cell death. The accumulated damage is called sub-lethal damage.
The wider the shoulder, the more sub-lethal damage the cell can endure.
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Figure 4.20 – Simple versus complex cell survival curves (from Forshier, 2008).
4.5 – CELL DEATH IN MAMMALIAN TISSUES
The clonogenic potential is the essential element for the maintenance of a cell
line, either in vitro or in organized tissues, although there are other important issues in
the maintenance associated with complex tissue systems. Normal senescence of cells
is one of these important issues and the other is the removal of cells that are in the
wrong place at the wrong time. Examples of this would be the metastatic arrival of
tumor cells transported from a primary tumor elsewhere or the resolution of
inflammatory processes (Alpen, 1998).
It is possible to define at least two different types of cell death that go beyond
the end point of clonogenic potential and involve the actual disappearance of the cell:
necrosis and apoptosis (Alpen, 1998).
Necrosis is characterized by a tendency for cells to swell and ultimately to lyse,
which allows the cell's contents to flow into the extracellular space, this is usually
accompanied by an inflammatory response. In the case of neoplasms, necrosis is most
often seen in rapidly growing tumors, where the tumor mass outgrows its blood supply
and regions of the tumor become undernourished in oxygen and energy sources. In
this case inflammation is not a characteristic of the necrotic process (Alpen, 1998).
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Apoptosis involves shrinkage of the nucleus and cytoplasm, followed by
fragmentation and phagocytosis of these fragments by neighboring cells or
macrophages. The contents of the cell do not usually leak into extracellular space, so
there is no inflammation. Since there is no inflammation accompanying apoptosis, the
process is histologically quite inconspicuous (Alpen, 1998).
Figure 4.21 - Structural changes of cells undergoing necrosis or apoptosis (from Goodlett, 2001).
The concept of apoptosis as a mechanism for the control of cell population
numbers and cell senescence has been around for several decades, but the
mechanisms of apoptosis have received extensive research attention only in the
nineties. This interest in apoptosis was engendered by the discovery that tumor
suppressor genes and oncogenes were central control agents for the process. The
principal focus of these studies has been the role of the p53 tumor suppressor gene,
already described in chapter II. The p53 gene is a transcriptional activator that may
include activation of genes that regulate genomic stability, cell cycle progression, and
cellular response to DNA damage. The synthesis of the p53 product is known to be
responsible for the induction of apoptosis in many cell lines in which this gene is
present in unmutated form. The mutational absence of this gene is often accompanied
by the inability of a cell line to initiate apoptosis. For radiation pathology, the
important finding is that even small amounts of DNA damage in G1 cells cause
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synthesis of the p53 product and ultimate apoptosis of the cells. It is pertinent for
radiation pathology that cells of the lymphoid system generate high concentrations of
p53 gene product after cell damage. This is particularly true for low doses of ionizing
radiation. Clearly, the generation of the p53 product is not sufficient for the onset of
apoptosis, but it is certainly necessary (Alpen, 1998).
Another significant gene involved in apoptosis is the bcl-2 gene (described in
chapter II). This gene encodes a protein that blocks physiological cell death (apoptosis)
in many mammalian cell types, including neurons, myeloid cells, and lymphocytes. This
gene is able to prevent cell death after the action of many noxious agents (Alpen,
1998).
The role of apoptosis as a mechanism for cell death following ionizing radiation
exposure remains unclear at this time, particularly the relative importance of the
agonistic role of p53 and the antagonistic role of bcl-2. However, it must be important,
as that the detection of small nicks and errors in the DNA of G1 cells is crucial to the
recovery of irradiated tissues and the reduction of genomic misinformation (Alpen,
1998).
4.6 – NATURE OF CELL POPULATIONS IN TISSUE
One of the earlier systematic overviews of the nature of cell population kinetics
in normal and malignant tissues was that of Gilbert, 1965. Their classification of the
various kinetic systems found in mammalian (and, incidentally, in other organisms)
organs and tissues is shown in Figure 4.22 (Alpen, 1998).
Figure 4.22 - Classification of cell kinetic types in the system of Gilbert, 1965 (from (Alpen, 1998)).
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From Figure 4.22, the definitions of each of the systems are the following (the
double arrows in classifications D, E, and F, are meant to signify the mitotic division of
one of the cells of the compartment, giving rise to two daughter cells):
A. Simple transit population. Fully functional cells are added to the
compartment while a population of either aging or randomly destroyed cells disappear
from the pool. There are many examples of functional end cells that are in this
category. Examples are spermatozoa, which are constantly being replaced, as well as
red cells or other end cells of the blood.
B. Decaying population. The cell numbers decrease with time without
replacement. The population of oocytes in the mammalian female is often quoted as
an example, if not the only example. Populations of this classification are rare in
mammalian systems, but not in insects.
C. Closed, static population. There is neither decrease nor increase in cell
numbers during life. It is unlikely that such a population truly exists. The differentiated
neurons of the central nervous system are quoted as an example of a static
population, but there is probably a decline in cell numbers even in this population.
D. Dividing, transit population. In addition to the transiting cells, division of the
cells within the compartment occurs that leads to a larger number leaving than
entering. It is assumed in this model that the number of cells in the compartment
remains more or less static. The differentiating and proliferating blood cell types (for
example, the proerythroblast of the bone marrow) that follow the stem cell are
examples of this type of population.
E. Stem cell population. A self-sustaining population, that relies on self-
maintenance for its continued existence. All the progeny of this type of cell line
depend upon the continued existence of the stem cell pool. Every self-maintaining,
dividing cell population must have such a precursor pool. Examples are the stem cells
responsible for sustained spermatogenesis or hematopoiesis.
F. Closed, dividing population. Such a population is best represented by
neoplastic growth. No cells enter or leave the compartment in the early stages of
tumor growth. In the long run, neoplastic growth is probably best represented as a
stem cell population, since as the tumor enlarges, there is cell death, suppression of
growth by metabolic and other nutrient shortages, and a highly variable rate of
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division. The epithelial cells responsible for cell renewal in the lens of the eye are
another example of this type of population (Alpen, 1998).
4.7 – CELL POPULATION KINETICS AND RADIATION DAMAGE
It should be almost self-evident that the kinetic types represented by D, E, and
F of Figure 4.22 will be most vulnerable to radiation damage. It has been established
that for clonogenic death of the cell the principal target of ionizing radiation is the
genome, and the genome is certainly at its most vulnerable to radiation damage during
G2 and mitosis (M), when replication has been completed. The principal outcome of
disturbances to the dynamic replicative activity of the genome is altered clonogenic
ability. That is indeed the case, and the most critically sensitive of these systems would
be the stem-cell-type tissue (E), which depends for its continuing function on its own
continued clonogenic potential, since there is no precursor compartment to replace
deficiencies (Alpen, 1998).
The ultimate functional viability of a tissue that is dependent on stem cell
activity will be determined by whether, after radiation exposure, there are adequate
numbers of surviving and still clonogenic stem cells to repopulate the compartment
and finally to produce functionally competent progeny. The most resistant tissues are
those that require neither input of cells from a prior compartment nor division within
the compartment. The closed static model is such a case, and in the case of the central
nervous system, its high degree of radioresistance can be attributed to its lack of need
for cell replication and replacement (Alpen, 1998).
4.7.1 – Growth Fraction and its significance
The concept of growth fraction as a descriptive parameter for the kinetics of
proliferating tissue appears to have been first proposed by Mendelsohn (1962) as the
result of his observations that all cells in a growing tumor are not in the active process
of proliferation as determined by the cellular incorporation of radioactive labels of
DNA synthesis. Lajtha (1963), based on his own studies as well as those of others,
proposed the concept of the G0 phase of the cell cycle, a state of the cell in which the
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cell was not engaged in active proliferation, but in which the cell could reenter the
proliferative state. The G0 cell was visualized as a cell that has been removed from the
actively dividing population by regulatory activities rather than as a result of metabolic
deprivation. Subsequently, it became apparent that cells also could be removed from
active division in a reversible manner by deprivation of oxygen, glucose, or other
metabolites (Hlatky et al., 1988). Restoration of the lacking nutrient led to reentry of
the cell into active proliferation (Alpen, 1998).
Figure 4.23 – Cell cycle phases (from (Goldwein, 2006)).
The growth fraction is defined as the fraction of the total cellular population
that is clonogenically competent and is actually in the active process of DNA replication
and cell division. The growth fraction may be estimated by any one of several
techniques, most of which depend on incorporation of a radioactively labeled DNA
precursor into those cells that are actively dividing. One of the simpler methods for
determination of the growth fraction is the exposure of a growing culture of cells, in
vitro or in vivo, to an appropriate radioactive label for the synthesis of DNA. A typical
and frequently used label is 3H-thymidine. The cells are exposed to the radioactive
label in the medium or by injection into the intact animal for at least the full length of a
cell cycle (and usually for half again as long). Under these conditions, all cells that
synthesize DNA, thus indicating their passage through the S period of the cell cycle, are
labeled and can be identified by autoradiography. The percentage of cells that is
labeled constitutes the growth fraction, since every cell in cycle will have passed
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through the S period at least once during exposure to the radioactive label (Alpen,
1998).
The radiobiological significance of the growth fraction was unclear until the
appearance of new data in the late 1980s. In 1980, Dethlefsen indicated that the role
of quiescent cells in radiobiological response was not satisfactorily delineated. Recent
studies indicate that cells that are out of cycle are capable of a more significant
amount of repair of potentially lethal damage, simply because there is more time
before the cell is called on to replicate its DNA. It is possible, but by no means proved,
that the concentration of enzymes necessary for repair of DNA damage may be
depleted in the noncycling cell, but, in spite of this, the additional time allows effective
repair to proceed with the lower concentration of repair enzymes (Alpen, 1998).
4.8 – CELL KINETICS IN NORMAL TISSUES AND TUMORS
Both normal and neoplastic tissues have a cellular kinetic pattern that follows
the accepted model of a G1-S-G2-M cycle, and, indeed, the cell cycle parameters are
not very different for tumors as compared to other growing tissues. The total cycle
time and the time devoted to DNA synthesis in the S period are very much alike for
both tissue types. However, there are significant differences in some of the
characteristics of the kinetic pattern as the tumor reaches a size where vascularization
is required for continued tumor growth. The orderly vascularization of normal tissues
that originates in embryonic life and that is maintained throughout the existence of
normal, nonpathological function assures that the supply of oxygen and nutrients is
adequate for survival of cells. Most, if not all, tumors, on the other hand, originate as
nonvascularized aggregations of cells and develop a vascular supply sometime after
the origination of tumor growth. The development of vascular supply in a tumor
depends on the activities of angiogenic factors that occur in normal tissues. The newly
developing vascular supply is, at best, chaotic and disorganized (Alpen, 1998).
Some parts of the tumor tissue will be so far from the source of oxygen and
nutrients that cell survival will be impossible, Figure 4.24. Other parts of the tumor will
have nutrient and oxygen supplies that are adequate only for survival of cells without
replication. The lack of oxygen and glucose can lead to a decrease in the growth
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fraction, and probably to cell death and necrosis. Several nutrients and metabolic
products, including oxygen, glucose, and lactic acid, play an important role in the
determination of quiescent and proliferating cells in tumors (Alpen, 1998).
One important difference between normal tissues and tumor tissues is the
determinant of the fraction of quiescent cells in the organ or tumor. Because of the
orderly vascular architecture of normal tissue, the movement of cells from the
proliferating to the quiescent compartment is probably not the result of nutrient lack,
but, rather, the result of the activity of normal soluble growth factors and naturally
occurring inhibitors that regulate the growth and development of the tissue (Alpen,
1998).
4.9 – MODELS FOR RADIOBIOLOGICAL SENSITIVITY OF NEOPLASTIC TISSUES
The earliest attempts to assay the sensitivity of organized tissue systems were
directed at establishing the radiosensitivity of tumor tissues. This was partly because
these tissues offered opportunities for analysis that were not available for normal
tissues. The possibility for syngeneic transplantation of the cell lines from host to
recipient animal was the most important characteristic of these in vivo tissue systems.
Figure 4.24 - Role of hypoxia in tumour angiogenesis (from Carmeliet, 2000).
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After irradiation of the tumor in the host in which it was growing, it was
possible to transplant the tumor cells to an unirradiated recipient animal and to
observe the growth response of the irradiated tumor cells. There was also strong
interest in understanding tumor biology arising from the treatment of cancer by
radiotherapy. It was important to establish the role of oxygen in the sensitivity of
cancer cells, as well as the importance of the fraction of G0 cells and repair or
repopulation in these tissues. The overall goal was practical: to maximize the
effectiveness of radiotherapy for cancer control in patients, while reducing damage to
normal tissues in the radiation field (Alpen, 1998).
4.9.1 – Hewitt Dilution Assay
Probably the first in vivo assay for mammalian tissues was that developed by
Hewitt and Wilson (1959) with a syngeneic mouse tumor system. At that time a
number of tumor cell lines that were grown in the peritoneal cavity of mice had been
developed. The cells from these ascites tumors could be harvested or allowed to
continue to grow in the peritoneal cavity of the host, which would cause the death of
the animal. It occurred to Hewitt and Wilson that this end point - death of the host
animal could be used to measure the clonogenic potential of the tumor cells after
irradiation. Figure 4.25 shows the essentials of a Hewitt assay for a single dose point at
10 Gy (Alpen, 1998).
Figure 4.25 - Typical data set for a Hewitt dilution assay (from Alpen, 1998).
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Cells harvested from the mouse ascites tumor P388 and unirradiated cells were
collected from the donor and a series of dilutions was prepared from a stock
suspension of the tumor cells. A typical microbiological-type binary dilution was
carried out to produce cell suspensions with low concentrations of cells that will allow
the recipient animal to be injected with cell numbers that are correct for killing about
half of the animals. For the tumor line used, the usual cell dose required to kill half of
the animals is about two to three cells. A small number of animals (5-10) are injected
with the same cell dose and the survival is followed. The same procedure is used for
several additional cell doses. The resulting data on percent survival at each of the cell
doses are plotted as shown in Figure 4.25, and the LD50 (lethal dose for 50% of the
animals) is determined by graphical or analytical means. The procedure is repeated,
but with the cell suspension prepared from animals that were irradiated before cell
collection. Animals are irradiated at several doses and injections proceed as just
described for each dose. The LD50 values can be used to construct a survival curve.
Figure 4.25 shows an example for only one radiation dose on the right panel and for
unirradiated cells on the left panel, with the calculated surviving fraction. The surviving
fraction is estimated for each of the other doses, and a survival curve of surviving
fraction against dose is plotted in the usual way (Alpen, 1998).
The Hewitt assay has been the tool used for a number of significant studies of
tumor cell sensitivity to radiation. Figure 4.26 is a very good example of such studies.
Andrews and Berry (1962) developed survival curves for three mouse tumors, two
leukemias, and a sarcoma. Some of the data were Berry's own previously unpublished
observations and some were provided by Hewitt. The clonogenic survival curves were
developed for both anoxic and oxic conditions. All three cell lines could be plotted on
the same curve for oxic cells or for anoxic cells as appropriate, and the line produced
was a good fit for the appropriate condition of oxygenation. The oxygen enhancement
ratio (OER) for these cells was about 2.4, which is not far from the 2.8 or so for cell
lines that are irradiated in vitro and analyzed for clonogenic survival in vitro. The Do for
the cells irradiated under oxic conditions was about 150 cGy, and the extrapolation
number was about 3-4 for this set of data (Alpen, 1998).
A significant shortcoming of the dilution assay system is that donor cells that
are grown in ascites fluid are usually irradiated when the cell number in the peritoneal
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cavity is very large. Under these conditions, it is not always clear that the cells are fully
oxygenated at the time of irradiation. If that is indeed the case, there is the possibility
of significant anoxic protection of the cells and, subsequently, there is an
overestimation of the resistance of the cells to the irradiation. The data reported in the
Berry study do not seem to be affected by such hypoxia. The Do (oxic) is about 150 cGy,
a number quite consistent with that found for many cell systems in vitro. The OER of
2.4 or so is, again, not very different from the 2.5-2.8 seen for in vitro systems. We
must conclude, at least for the cell lines reported in this study, that adequate
oxygenation probably existed at the time of irradiation (Alpen, 1998).
Another shortcoming of the Hewitt method is that the irradiated tumor cells
must be capable of expressing clonogenic potential while growing in the ascites
medium. For example, most leukemias grow readily in this environment, and usually
require an inoculum of only 1-3 cells to cause the death of 50% of the recipient
animals. For the Berry data just described, the sarcoma cells required an inoculum of
more than 80 cells to kill 50% of the recipients. In many cases no cell growth is seen
and no assay is possible. To avoid this shortcoming, other assays have been developed
(Alpen, 1998).
Figure 4.26 - The survival curve obtained by Berry (1964) via the Hewitt assay method for two mouse leukemias and a sarcoma (from Alpen, 1998).
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4.9.2– Lung Colony Assay System
A modification to the Hewitt assay was developed by Hill and Bush (1969) to
measure clonogenic survival of cells derived from solid tumors. In principle, the assay
measures the clonogenic survival of tumor cells by determining their ability to form
colonies in the lung of recipient syngeneic mice. The cells from a tumor, irradiated
either in vivo or, after dissection and cell dissociation, in vitro, are injected into a
recipient mouse, and after 18-20 days the animals are killed, the lungs are dissected,
and the number of tumor colonies in the lung is counted. Hill and Bush were able to
demonstrate a linear relationship between cell number injected and the number of
colonies formed in the lung. A very large enhancement of the number of colonies in
the lung was found if, along with the experimentally irradiated cells, a large number of
heavily irradiated, nonclonogenic cells were injected. Typically, such a procedure
produced a 10-50-fold increase in the number of colonies formed from the clonogenic
survivors. Hill and Bush were not able to establish the mechanism of this
enhancement, but it was not due to an immune response on the part of the recipient.
Very consistent survival curves were obtained, and, for the KHT transplantable
sarcoma, the Do was 134 cGy, with an extrapolation number of about 9.5. Again, these
data were found to be quite consistent with the values found for the same tumor with
the Hewitt assay. Such an agreement not only validates the lung colony assay, it also
demonstrates that there was little protection from radiation damage due to partial
hypoxia for the KHT cells irradiated as solid tumors and tested by the dilution assay
(Alpen, 1998).
A significant limitation of the lung colony assay is that cells must be injected
into syngeneic recipient mice, that is, inbred mouse lines of the same genotype as that
from which the tumor is derived (Alpen, 1998).
4.10 – TUMOR GROWTH AND TUMOR “CURE” MODELS
Since there is a very limited set of models for examining the clonogenic
potential of tumor cells, much of the radiation biology of tumors has been developed
using a set of tools that was developed for general use in tumor biology. Therefore,
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some of these tools have been more valuable than others for radiation effect studies
because of the inherent inability to effect precise quantitation.
4.10.1 – Tumor Volume versus Time
A widely used and relatively powerful tool in tumor radiobiology is the tumor
growth curve after implantation of an inoculum of cells, usually in the flank region of
recipient syngeneic mice or rats. The simplest application of the growth curve for
implanted tumors is the analysis on the increase rate of the tumor volume. For analysis
of the radiation effect we can measure the time for the tumor to reach a preselected
volume. The measurements of tumor volume are at best imprecise. The volume is
usually determined from a caliper measurement of two or more diameters of the
growing tumor and calculation of the volume from the average diameter (Alpen,
1998).
After the tumor has been irradiated, the time course of volume change is as
shown in Figure 4.27. There may be a slowing of growth for a brief time, followed by a
period of decreasing tumor volume. This decrease is due to lack of replacement of the
normal cell loss from tumors, associated with local necrosis, nutrient lack, or other
causes unrelated to the radiation exposure. It is not due to the interphase death of
cells as the result of irradiation. As the surviving clonogenic cells repopulate the tumor,
regrowth will be observed; the surviving clonogenic cells will ultimately produce
progeny exceeding the cell-loss factor (Alpen, 1998).
Figure 4.27 - Tumor volume versus time (from Alpen, 1998).
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The criterion for measurement of the radiation dependent response is the time
for the cell volume to again reach the value observed at the time of irradiation. This
time is shown in Figure 4.27, and it is measured, as shown, as the time from irradiation
until the tumor volume achieves the value existing at the time irradiation occurred.
This time value is called the growth delay. The important limitation of the growth delay
model for testing the radiobiological response of tumors is that a significant number of
transplantable tumors does not show any decrease in the volume of tumor after
irradiation (Alpen, 1998).
Presumably, this failure to decrease in volume is the result of a small cell-loss
fraction in the growing tumor. When irradiation takes place, clonogenic activity is
reduced until repopulation from competent clonogenic cells occurs. During the period
before regrowth commences as the result of repopulation, the normally small cell-loss
fraction of the tumor does not lead to reduction in tumor volume. In these cases it is
necessary to revert to the simpler measure of tumor volume versus time and the use
of the time to reach a preset volume. Alternatively, differences in this time for control
and irradiated tumors may be taken as the end point (Alpen, 1998).
4.10.2 – TCD50, Tumor Cure
Another end point that is widely used in tumor biology is the dose required to
"cure" an implanted tumor. For this model, a large number of implanted tumors are
irradiated with graded doses at the same time period after implantation of the tumor
inoculum. The end point is the fraction of animals that has received a given dose in
which the growth of the tumor is controlled. This local control index can be plotted for
each of the doses, and the dose required to control tumor growth in 50% of the
animals is estimated by a variety of statistical techniques. This value is usually called
the 50% tumor cure dose -TCD50 (Alpen, 1998).
4.11 – RADIOBIOLOGICAL RESPONSES OF TUMORS
Using a number of end points, including dilution assay, lung colony assay,
primary cell cultures, and tissue derived in vitro cultures, it has been possible to define
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rather clearly the radiobiological responsiveness of various tumor lines, both animal
and human. With only a few important exceptions, the various tumor cell lines in wide
and long term experimental use have been found to have clonogenic survival
characteristics that are generally stable and for which the relevant survival parameters
are not very variable, considering the range of cell types and tissues from which these
transformed and immortal cell lines have been derived (Alpen, 1998).
Rather different findings have been reported for the survival curve parameters
of freshly derived culture systems grown from naturally occurring malignant tumors.
Extensive efforts have been devoted to characterization of the radiosensitivity of cell
lines from human tumors. The best fit to the data for a large number of human cell
lines, both nontransformed fibroblasts and tumors, is the linear-quadratic (LQ) model.
The radiosensitivity of the various cell lines can be divided into three groups with a
very good correlation with the known responsiveness of the tumors to radiotherapy:
lymphomata, known to be highly curable, were the most radiosensitive of the derived
cell lines, and melanomata revealed to be the most resistant for tumor curability and
the most radioresistant in the survival of the cell lines in culture (Alpen, 1998).
It is important to realize that the immediate responsiveness of a tumor to
radiation, as determined by reduction in the tumor volume, does not necessarily
predict the curability of the tumor with high efficiency. The degree of responsiveness
will be determined by many of the cell kinetic parameters of the tumor system. A high
cell-loss factor and a high growth factor associated with a small fraction of cells out of
cycle and associated with inherent cellular radiosensitivity, will assure a high degree of
responsiveness of the tumor, as measured by volume changes. Curability, on the other
hand, will depend in a complex way on the ability of the few remaining clonogenic cells
to repopulate the tumor after irradiation is over (Alpen, 1998).
4.12 – HYPOXIA AND RADIOSENSITIVITY IN TUMOR CELLS
Under circumstances where severe anoxia can occur in tissues or cellular
preparations, one should expect to see significant protection from the effects of
ionizing radiation. It is expected to find conditions of moderate to severe anoxia in
growing tumors in vivo. For cells grown in suspension, careful attention to culture
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conditions usually will prevent the development of such anoxic conditions with
concomitant radioprotection. For the tissue assay systems, such as the Hewitt dilution
assay and others, there is clearly a protective effect of oxygen lack under the correct
conditions. Figure 4.26 shows such radioprotection for cells deliberately made anoxic
by killing the host animal or by allowing the cell number for cells growing in the
peritoneal cavity to reach very high levels. Figure 4.28 demonstrates methods by which
the fraction of hypoxic cells in a mixture with fully oxygenated cells can be detected
and measured quantitatively. The radioresistant "tail" for the dashed line survival
curve shown in Figure 4.28 (10% anoxic cells) is a common observation for cells from
tumors and indicates the presence of a mixed population of cells, part of which have a
radioresistance relative to the remainder of the population. This resistant fraction may
be due to hypoxia and the radioprotection that this state affords (Alpen, 1998).
Figure 4.28 - Survival curve for the irradiation of a cell suspension containing a fraction of hypoxic cells (from Alpen, 1998).
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The well known work of Thomlinson and Gray (1955) laid the foundations for
our understanding of hypoxia as well as reoxygenation in tumors during growth and
regrowth. Figure 4.29 (from Thomlinson, 1967) illustrates the processes proposed by
this author. The very young tumor is well oxygenated, since it is so small that no cells
are beyond the effective diffusion distance of oxygen from nearby capillaries. As the
tumor continues to grow, portions of the tumor volume may be beyond easy access to
diffusing oxygen. The tumor must depend for its supply of oxygen on the development
of newly formed vessels that arise from the adjacent normal tissue and penetrate the
tumor volume. This neovascularization of the tumor is not as well organized as the
blood supply in normal tissues, and the expanding volume of tumor will contain
regions in which oxygen is inadequate for the maintenance of metabolism, and some
fraction of the cells will be anoxic. Figure 4.29 illustrates that the fraction of anoxic
cells in the growing tumor may rise to several percent and in some tumor types, to as
much as 10%. According to the model of Thomlinson, when the tumor is irradiated
(position R1 in the figure) the more radiosensitive, fully oxygenated cells are killed, and
the remaining hypoxic cells are in an environment of dead and dying cells with lesser
demand for metabolic oxygen (Alpen, 1998).
Figure 4.29 - Development of hypoxia and reoxygenation in an irradiated tumor (from Alpen, 1998).
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Shrinking of the tumor volume and lowered oxygen demand allow for
reoxygenation of the hypoxic cells, which is indicated by a rapid fall to near zero for the
anoxic fraction. After this period of reoxygenation, tumor regrowth commences and
the complete cycle is repeated. The significance of the reoxygenation phase in
fractionated radiotherapy of human tumors is undergoing careful reexamination,
partly because treatment modalities designed to optimize the kill of anoxic cells (high
linear energy transfer (LET) radiation, radiation under hyperbaric oxygen conditions,
and so on) have not been particularly successful. According to Figure 4.29, the
optimum time for a second irradiation of a fractionated scheme would be at point H in
the curve, when the population of hypoxic clonogenic cells is at a minimum. Recent
data suggest that the reoxygenation phenomenon actually occurs very soon after
irradiation, and indeed may take place while the irradiation is in progress (Alpen,
1998).
4.13 – SUMMARY
Human tumors strongly differ in radiosensitivity and radiocurability and this is
thought to stem from differences in capacity for repair of sub-lethal damage.
Radiosensitivity varies along the cell cycle, S being the most resistant phase and G2 and
M the most sensitive. Therefore, cells surviving an exposure are preferentially in a
stage of low sensitivity (G1), i.e. synchronized in a resistant cell cycle phase. They
progress thereafter together into S and then to the more sensitive G2 and M phases. A
new irradiation exposure at this time will have a larger biological effect (more cell kill).
However, while this synchronization effect has explained some experimental results,
redistribution has never been shown to play a measurable role in the clinic of
radiotherapy (Mazeron, 2005).
Cells surviving an irradiation keep proliferating, increasing the number of
clonogenic cells, i.e. the number that must eventually be sterilized to eradicate cancer.
An inappropriate development of intratumoral vasculature leads to a large proportion
of poorly oxygenated cells and the proportion of hypoxic cells increases with the tumor
size (Mazeron, 2005).
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Acutely hypoxic cells are far more radioresistant than well oxygenated cells.
Hypoxic cells usually survive irradiation, but they progressively (re)oxygenate due to
the better supply of oxygen available after well oxygenated cells have died. This
restores radiosensitivity in the tumor by several mechanisms, but re-oxygenation
occurring at long intervals is probably due to tumor shrinkage leading to a reduction of
the intercapillar distance (Mazeron, 2005).
The effects of ionizing radiation, even at low doses, are potentially capable of
causing serious and lasting biological damage. The potentially harmful effects of
ionizing radiation must be recognized and understood. It is important that radiologists
should have a good appreciation of the risks associated with the examinations they
carry out.
CHAPTER V
CELL CULTURE AND FLOW CYTOMETRY
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 126
5.1 – INTRODUCTION
Cell culture is an invaluable tool for researchers in numerous fields. It facilitates
the analysis of biological properties and processes that are not readily accessible at the
level of the intact organism. Successful maintenance of cells in culture, whether
primary or immortalized, requires knowledge and practice of a few essential
techniques (Helgason, 2005).
The use of cells in analytical chemistry, engineering, and biology requires a
dedicated space for cell culture and maintenance. The proper handling of cells and
tissues requires a level of diligence and constant education, to mitigate health and
safety risks. Cell culture requires a system of mutual separation of sample and scientist
to avoid contamination of either. Each time a culture flask and the dish is opened is, in
essence, an opportunity for a single bacterium or fungal cell to ruin an experiment.
Likewise, every time cell cultures or tissues are handled, there is a risk to the scientist.
It is therefore needed to understand the protective countermeasures required to
handle cells properly (Pappas, 2010).
This chapter presents the importance of the laboratory conditions in the
manipulation and maintenance of cell culture. Subsequently, it is explained the
cytogenetic analysis of cell line and I performed a description of the methods to induce
cell cycle checkpoints. In the end of the chapter, it is presented a description of the
methods for synchronizing mammalian cells and the analysis of the mammalian cell
cycle by flow cytometry.
5.2 - CELL-CULTURE LABORATORY
Setting up a laboratory (or space within an existing lab) for cell culture is not a
daunting task, but requires some planning and strict adherence to regulations. Most
universities, research institutes, and hospitals have a safety committee (some
committees specialize in biosafety) that is in place in part to help a research establish a
cell lab. While the government guidelines typically set the standard for safety rules, the
research institution may have additional guidelines to follow. Therefore, the safety
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committee is therefore indispensable in the planning and setting up of a cell lab, as
well as in the subsequent (and often frequent) safety inspections. The main issues
when setting up and maintaining a culture lab are safety, sterility, and contamination.
All three of these issues are linked by the common safe practices and proper use of
equipment, and all three require that individuals working in the lab are properly
educated (Pappas, 2010).
Working in the lab requires universal precautions, assuming that all cell cultures
and related materials may contain hazardous pathogens. This assumption maintains a
more vigilant attitude, and reduces the risk of accidental exposure to a real pathogen.
Moreover, the possibility that cultures can be cross-contaminated requires additional –
albeit similar – precautions. In short, careful procedures will result in productive
research in a safe environment for cells and individuals. For those new to cells and cell
culture, this chapter will not only serve as an introduction to the tools required for a
cell lab, but will also detail some of the practical aspects to setting up a culture facility.
For those with cell culture experience, the discussion of analytical equipment should
prove useful (Pappas, 2010).
5.3 – MAINTAINING CULTURES
The proper maintenance of cells includes homeostasis during culture, cell
storage and the correct preparation of cells for analysis. The latter case is of the most
importance, as often analysis and homeostasis are incongruent. Buffers must be
changed, different media used, and the cells, at times, are exposed to drastically
diverdse conditions for analysis. In some cases, the change in conditions can affect the
outcome of the experiment negatively. In other instances, the conditions suitable for
cell analysis are fatal to the cell (e.g., electron microscopy). There are many works
available on the culture of almost every cell type imaginable (Pappas, 2010).
When culturing primary or immortal cells for analysis, sterility and cross-
contamination must also be monitored at all times. A few bacteria in a sample can
wreak havoc in a short time, rendering any analytical data useless. The cross-
contamination of cultures is at best a nightmare, as extensive genetic testing is
required to purify cell populations and yield accurate data. Considering the cost of
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cells, reagents, instrumentation, and lab upkeep, at least as much thought should be
placed on the maintenance of cell cultures for appropriate analysis. The type of
environment the cell encounters can directly affect the outcome of an analytical
experiment: cell-growth conditions, analysis buffers and reagents can affect the cell
phenotype, cell signaling, and a host of other parameters. By careful maintenance of
primary and immortal cells, accurate and reproducible cell analyses can be conducted
(Pappas, 2010).
5.3.1 – Medium
More than any other reagent in a cell-analysis laboratory, a steady supply of
culture medium – and the choice of correct medium type – is essential for cell analysis.
There are, in general, two classes of medium one can consider for cell analysis. First,
medium that is used to maintain a culture in between experiments, and second,
medium used in the analysis itself. Often these two can be one in the same, although
in some cases a modified medium or supplemented buffer is needed during the
analysis or processing phase (Pappas, 2010).
There are many types of medium available and the supplements that can be
added to them expand the palette of options even further. Table 4.1 lists some
medium types that are common to cellular analysis, by cell type. The table is not
inclusive, but serves to highlight the differences in medium types, and that some
medium formulations are applicable to many cell lines. In most cases, the medium in
Table 4.1 is used during the culture (maintenance) phase, and a different buffer or
medium may be used during the analysis itself (Pappas, 2010).
Medium can be classified as basic or complete, depending on whether or not
serum is included, respectively. Basic medium has many of the components required
for cell metabolism. Basic media, such as DMEM and RPMI 1640 (see Table 4.1),
contain salts (partly from buffer action), amino acids, vitamins (such as biotin, folic
acid, B-12, etc.), and molecules involved in energy production (glucose, pyruvate).
Basic medium also often contains other buffers (such as HEPES) and a colorimetric
acid–base indicator, such as phenol red. The latter serves as a quick visual inspection
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of the “age” of the medium in culture. As cells consume nutrients and produce waste,
the culture medium acidifies, resulting in a shift in color for the pH indicator. The
formulations of most culture media are available and should be examined for potential
interference in the analysis. For example, staining using Annexin-V-based apoptosis
probes requires relatively high Ca2+ concentrations and at the same time, the presence
of phenol red in the medium will interfere with fluorescence measurements of
fluorescein, green fluorescent protein (GFP), and other fluorophores with similar
emission spectra. Fluorescence from phenol red itself makes sensitive fluorescence
measurements nearly impossible (Pappas, 2010).
Table 1 – Medium types common to cell analysis (from (Pappas, 2010))
Medium Serum Additives Cell lines
RPMI 1640 10% FBS Antibacterial-Antifungal
Jurkat, HuT 78, RPMI
8226, CCRF-CEM, U937,
HL-60
Dulbecco`s modified
Eagle Medium (DMEM) 10% FBS
Antibacterial-Antifungal,
L-Glutamine
NIH 3T3, RBL-1, HT-29,
HeLa
Clavcomb`s Medium 10% FBS
Antibacterial-Antifungal,
Norepunephrine, L-
Glutamine
HL-1
Cell Mab 0-10% FBS Varies
Designed for
monoclonal antibody
production
Leibovitz`s L-15 Hemolymph Bag neuronal cells
Eagle`s Minimum
Essential Medium 0-10% FBS L-Glutamine
F-12 0-10% FBS L-Glutamine Designed for primary
cells
Iscove`s Modified
DMEM 0-10% FBS L-Glutamine HuT 78 T Cells
FBS = Fetal Bovine Serum
Medium is, in essence, a man-made attempt to mimic the life support found in
vivo. It is, therefore, lacking in many essential compounds for cell growth. Many cell
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lines can function in basic medium without additional materials, but for the most
routine culture and analysis, serum must be added to form the complete medium
(Pappas, 2010).
Serum is typically derived from animal sources, the most common being fetal
bovine serum (FBS). FBS and other sera contain growth factors such as epidermal
growth factor (EGF), some interleukins, and transferrin. Furthermore, present are
adhesion-promoting proteins and peptides, for example, fibronectin and laminin and
other components including insulin and various minerals. FBS and other animal-based
sera are by far the most common supplements used for culture maintenance (Pappas,
2010).
Being derived from animal sources, serum is inherently difficult to use from a
quality-control perspective and since it is derived from different animal types this can
affect experiment outcome. For example, the use of FBS instead of native rat serum
was shown to affect the outcome of rat leukocyte immunological response. In addition
to species variability, serum varies from lot to lot, as well as by country of origin, so if
cell products are to be analyzed over long time periods (months of experimentation) it
is best to purchase a large quantity of serum from one particular lot. Given the high
cost of medium, this may not always be practical since serum cost increases as the
level of quality control improves. The more consistent and well characterized the
medium, the higher the cost (Pappas, 2010).
Another negative aspect of dealing with serum is that the serum, or animal of
origin, is subject to contamination, just like any other primary derived material. Certain
viruses, bacteria, and mycoplasma have been shown to be transmitted via serum.
There are several replacement sera that can be substituted for FBS. For example, the
FetalClone series and Bovine Growth Serum, both from HyClone, are non-fetal animal
sera supplemented with various growth factors, minerals, and other compounds. Since
they are not derived from fetal animals, there is less variability between lots (especially
for the added compounds). None of the alternative sera offers much relief as far as
cost is concerned, but the increase in quality control is a major improvement (Pappas,
2010).
Some cells readily grow in serum-free medium; most, however, must be
acclimated to a serum-free environment. This requirement is especially true if the cell
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line in question is already being cultured in serum-enriched medium (typically 10%
v/v). It is possible to reduce serum content in medium; in some cases, it is advisable to
do so, because reducing the amount of serum added can reduce costs, as serum is the
most expensive component of the complete medium. Reducing serum also lowers the
total protein content of the medium, facilitating collection of cell products, and
minimizing sources of contamination. For cells growing in serum-enriched medium, a
method of systematically reducing medium can be implemented (Pappas, 2010).
One must first consider the growth of cells in culture, before discussion of how
to achieve serum reduction can initiate, Figure 4.1. Cell growth in culture – whether
the cells are adherent or suspended – is characterized by several stages. The lag phase,
during which minimal or no cell division occurs, is a brief period after inoculation. The
lag phase occurs as cells adjust to a new cell-culture environment, and as adherent
cells begin the process of reattaching to the culture substrate. The lag phase is
followed by the log or exponential phase. This is the major phase of cell division. The
doubling time, an indicator of cell growth, is determined during this period (Pappas,
2010).
Figure 5.1 - Cell growth in culture (from (Pappas, 2010)).
The time for the cell population to double, Figure 5.1, can be determined at any
point during the log phase, although it is most accurate at the center of that phase.
After the log phase, the culture reaches the stationary phase (Pappas, 2010).
High cell density, contact inhibition, and consumption of nutrients signal a
slowing of the cell cycle, and the cell concentration remains constant. Cell crowding,
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depletion of nutrients and accumulation of waste eventually causes a sharp drop in cell
concentration, called the death phase. This latter phase can be confirmed by
microscopy, where the presence of a large number of dead cells, cell debris, and
acidified medium (if an indicator is present) can be observed (Pappas, 2010).
The glucose content of basic medium varies and is sometimes supplemented
with additional glucose. The high glucose content of many medium types is intended
to stimulate growth of the culture. However, some cell lines change phenotypic
properties in high or low glucose. When culturing for conditions close to those
encountered in vivo, the glucose concentration should be adjusted to reflecting the
physiological value as much as possible. Like serum reduction, the impact of changes in
glucose concentration can be monitored using the culture doubling time (Pappas,
2010).
When formulating complete medium, care must be taken to preserve sterility
of the final mixture. If all components are sterile to begin with, then aseptic handling in
the biosafety cabinet will prevent contamination of the complete medium. If any of
the reagents are not sterile at the onset, then filtration can be employed to remove
contaminating organisms.
5.3.2 – The use of medium in analysis and alternatives
Medium is primarily used to maintain cultures and samples before analysis. The
medium can also be used during the analysis; in other instances, components of the
medium may produce artifacts or otherwise interfere. The presence of several
components of medium can interfere with fluorescence measurements. Phenol red,
one of the most common pH indicators added to medium, has a broad absorption
band that interferes with most green fluorescence. Phenol red is also weakly
fluorescent, creating an additional problem for green-emitting fluorophores. If the cell
homeostasis is not required, then any buffer devoid of phenol red will work for
fluorescence. On the other hand, if the cells are to be kept alive for long periods, then
phenol-red-free medium is available from most medium manufacturers. In addition to
the weakly fluorescent properties of phenol red, other compounds present at
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relatively high concentrations can interfere with fluorescence detection. Riboflavin is
also weakly fluorescent, but the relatively large volume of the medium contributes to
an unacceptable background signal. Proteins such as albumin, one of the major
components of serum, also contribute strongly to autofluorescence of medium. The
exact medium used for culture depends on the cell type, the culture conditions, and
the desired end result. For analysis, a similar selection process must be undertaken.
The final medium or buffer used for analysis must be of low background, minimal
interference, and – when possible – capable of sustaining cell viability and function for
the experiment duration (Pappas, 2010).
5.4 – CYTOGENETIC ANALYSIS OF CELL LINES
5.4.1 - The Utility of Cytogenetic Characterization
Countless cell lines have been established—more than 1000 from human
hematopoietic tumors alone —and the novelty and utility of each new example should
be proven prior to publication. For several reasons, karyotypic analysis has become a
core element for characterizing cell lines, mainly because of the unique key
cytogenetics provides for classifying cancer cells. Recurrent chromosome changes
provide a portal to underlying mutations at the DNA level in cancer, and cell lines are
rich territory for mining them. Cancer changes might reflect developmentally
programmed patterns of gene expression and responsiveness within diverse cell
lineages. Dysregulation of certain genes facilitates evasion of existing antineoplastic
controls, including those mediated by cell cycle checkpoints or apoptosis. The
tendency of cells to produce neoplastic mutations via chromosomal mechanisms,
principally translocations, duplications, and deletions, renders these changes
microscopically visible, facilitating cancer diagnosis by chromosome analysis. Arguably,
of all neoplastic changes, those affecting chromosomal structures combine the
greatest informational content with the least likelihood of reversal. This is particularly
true of the primary cytogenetic changes that play key roles in neoplastic
transformation and upon the presence of which the neoplastic phenotype and cell
proliferation ultimately depend. Nevertheless, the usefulness of karyotype analysis for
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the characterization of cell lines lies principally among those derived from tumors with
stronger associations with specific chromosome rearrangements (i.e., hematopoietic,
mesenchymal, and neuronal, rather than epithelial tumors) (Helgason, 2005).
Cytogenetic methods facilitate observations performed at the single-cell level,
thus allowing detection of intercellular differences. Accordingly, a second virtue of
cytogenetic data lies in the detection of distinct subclones and the monitoring of
stability therein. Except for doublings in their modal chromosome number from 2n to
4n “tetraploidization,” cell lines appear to be rather more stable than is commonly
supposed. Indeed, chromosomal rearrangement in cells of the immune system could
reach peak intensity in vivo during the various phases of lymphocyte development in
vivo. A further application of cytogenetic data is to minimize the risk of using false or
misidentified cell lines. At least 18% of new human tumor cell lines have been cross-
contaminated by older, mainly “classic,” cell lines, which tend to be widely circulated.
This problem, first publicized over 30 years ago but neglected of late, poses an
insidious threat to research using cell lines (Helgason, 2005).
In the event of cross-contamination with cells of other species, cytogenetic
analysis provides a ready means of detection. Although modal chromosome numbers
were formerly used to identify cell lines, their virtue as descriptors has declined along
with the remorseless increase in the numbers of different cell lines in circulation. Thus,
species identification necessarily rests on the ability to distinguish the chromosome
banding patterns of diverse species. Fortunately, cells of the most prolific mammalian
species represented in cell lines (primate, rodent, simian, as well as those of domestic
animals) are distinguishable by experienced operators (Helgason, 2005).
5.5 – METHODS TO INDUCE CELL CYCLE CHECKPOINTS
The way cells respond to radiation or chemical exposure that damages
deoxyribonucleic acid (DNA) is important because induced lesions left unrepaired, or
those that are misrepaired, can lead to mutation, cancer, or lethality. Prokaryotic and
eukaryotic cells have evolved mechanisms that repair damaged DNA directly, such as
nucleotide excision repair, base excision repair, homology-based recombinational
repair, or nonhomologous end joining, which promote survival and reduce potential
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deleterious effects. However, at least eukaryotic cells also have cell cycle checkpoints
capable of sensing DNA damage or blocks in DNA replication, signaling the cell cycle
machinery, and causing transient delays in progression at specific phases of the cell
cycle. These delays are thought to provide cells with extra time for mending DNA
lesions before entry into critical phases of the cell cycle, such as S or M, events that
could be lethal with damaged DNA (Lieberman, 2004).
The precise mechanisms by which checkpoints function is under intensive
investigation and details of the molecular events involved are being pursued
vigorously. This owes not only to the complexity and the intellectually and technically
challenging aspects of the process but also to the relevance of these pathways to the
stabilization of the genome and carcinogenesis. Nevertheless, it is clear that
checkpoint mechanisms are very sensitive and can be induced by the presence of
relatively small amounts of DNA damage. For example, in the yeast Saccharomyces
cerevisiae, as little as a single double-strand break in DNA can cause a delay in cell
cycle progression. One important aspect of studying cell cycle checkpoint mechanisms
is an understanding of how to induce the process (Lieberman, 2004).
The application of radiations, such as gamma rays and ultraviolet (UV) light, are
capable of causing DNA damage, and thus leading to the induction of cell cycle
checkpoints. Certain chemicals or the use of temperature- sensitive mutants to disrupt
DNA replication, are also used routinely to induce checkpoints. Gamma rays cause
primarily single- and double-strand breaks in DNA but can infrequently induce
nitrogenous base damage as well. In contrast, UV light (i.e., 254 nm) causes a
preponderance of bulky lesions, such as pyrimidine dimers, although single-base
damage and strand breaks are a smaller part of the array of lesions that can be
produced. Regulation of cell cycle checkpoints induced by ionizing radiation versus UV
light is mediated by overlapping but not identical genetic elements (Lieberman, 2004).
5.6 – METHODS FOR SYNCHRONIZING MAMMALIAN CELLS
When studying cell cycle checkpoints, it is often very useful to have large
numbers of cells that are synchronized in various stages of the cell cycle. A variety of
methods have been developed to obtain synchronous (or partially synchronous) cells,
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all of which have some drawbacks. Many cell types that attach to plastic culture dishes
round up in mitosis and can then be dislodged by agitation. This mitotic shake-off
method is useful for cells synchronized in metaphase, which on plating into culture
dishes move into G1 phase in a synchronous manner. A drawback to the mitotic shake-
off method is that only a low percentage (2–4%) of cells are in mitosis at any given
time, so the yield is very small. Also, cells rapidly become asynchronous as they
progress through G1 phase, so the synchronization in S phase and especially G2 phase is
not very good. The first limitation can be overcome by plating multiple T150 flasks with
cells, using roller bottles, or blocking cells in mitosis by inhibitors such as Colcemid or
nocodazole (Lieberman, 2004).
Mitotic cells that are collected can be held on ice for an hour or so while
multiple collections are done to obtain larger numbers of cells. To obtain more highly
synchronous populations of cells in S phase, the mitotic shake-off procedure can be
combined with the use of deoxyribonucleic acid (DNA) synthesis inhibitors, such as
hydroxyurea (HU) or aphidicolin (APH), to block cells at the G1/S border (but probably
past the G1 checkpoint). APH inhibits DNA polymerase α, whereas HU inhibits the
enzyme ribonucleotide reductase, though it may operate by other mechanisms also.
On release from the block, cells move in a highly synchronized fashion through S phase
and into G2 phase. In terms of the number of synchronized cells, this method has the
same limitation as discussed above, because the starting cell population derives from
the mitotic shake-off procedure. In addition, the block of cells with drugs can cause
unbalanced cell growth, so one cannot necessarily conclude that all biochemical
processes are also synchronized (Lieberman, 2004).
Large numbers of synchronous cells can be obtained using centrifugal
elutriation, Figure 5.2. This method requires the use of a special rotor in a large floor
centrifuge and separates cells into the cell cycle based on cell size. Cells may be
obtained in early or late G1 phase, or primarily in S phase. However, the cell
populations are not highly synchronous in S phase but instead have significant
populations of G1- and G2-phase cells included. Nevertheless, it is possible to
synchronize very large numbers of cells using this method, and biochemical processes
are not perturbed (Lieberman, 2004).
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Figure 5.2 - Centrifugal elutriation (from (Wahl, 2001)).
Another method that results in highly synchronous populations is based on
labeling cells with a viable dye for DNA (Hoechst 33342). Cells stained with this dye can
then be sorted by cell cycle phase. Sorted G1 cells will be distributed throughout G1,
cells in S phase can be sorted into a small window in S phase and thus will be highly
synchronized, but only a small number of cells can be obtained. G2 phase cells will be
contaminated with late S phase cells. Furthermore, some cell types do not stain well
with Hoechst 33342, so sufficiently good DNA histograms cannot be obtained Hoechst
33342 (Lieberman, 2004).
5.7 – ANALYSIS OF THE MAMMALIAN CELL CYCLE BY FLOW CYTOMETRY
One of the most common uses of flow cytometry is to analyze the cell cycle of
mammalian cells. Flow cytometry can measure the deoxyribonucleic acid (DNA)
content of individual cells at a rate of several thousand cells per second and thus
conveniently reveals the distribution of cells through the cell cycle (Lieberman, 2004).
The DNA-content distribution of a typical exponentially growing cell population
is composed of two peaks (cells in G1/G0 and G2/M phases) and a valley of cells in S
phase, Figure 5.3. G2/M-phase cells have twice the amount of DNA as G1/G0-phase
cells, and S-phase cells contain varying amounts of DNA between that found in G1 and
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G2 cells. Most flow-cytometric methods of cell cycle analysis cannot distinguish
between G1 and G0 cells or G2 and M cells, so they are grouped together as G1/G0 and
G2/M. However, there are flow cytometric methods that can distinguish four or even
all five cell cycle subpopulations: G0, G1, S, G2, and M. Furthermore, each
subpopulation can be quantified. Obviously, flow cytometry with these unique
features is irreplaceable for monitoring the cell cycle status and its regulation
(Lieberman, 2004).
Figure 5.3 - A typical cell cycle distribution of DNA content (from (Cooper,2004)).
Cell cycle checkpoint genes are key elements in cell cycle regulation.
Checkpoint gene mutation can lead to defects in one or more cell cycle checkpoint
controls, which can then result in cell death or cancer. Many of the cell cycle
checkpoint genes are tumor suppressors, such as p53, ataxia-telangiectasia mutant
(ATM), ataxia-telangiectasia and Rad3 (ATR), and BRCA1 (Lieberman, 2004).
In mammalian cells, the cell cycle checkpoint controls that can be analyzed by
flow cytometry are G1 arrest, suppression of DNA replication, and ATM dependent as
well as independent G2 arrest. Exposure to a genotoxic agent can activate some or all
the checkpoints (Lieberman, 2004).
5.8 – CONCLUSION
Effective in vitro maintenance and growth of animal cells requires culture
conditions similar to those found in vivo with respect to temperature, oxygen and
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carbon dioxide concentrations, pH, osmolality, and nutrients. Within normal tissue in
vivo, animal cells receive nutrients through blood circulation. For growth in vitro,
animal cells require an equivalent supply of a complex combination of nutrients. For
this reason, the first attempts in animal cell culture were based on the use of biological
fluids such as plasma, lymph and serum, as well as on extracts from embryonic-derived
tissue (Castilho, 2008).
Medium composition is one of the most important factors in the culture of
animal cells. Its function is to provide appropriate pH and osmolality for cell survival
and multiplication, as well as to supply all chemical substances required by the cells
that they are unable to synthesize themselves. Some of these substances can be
provided by a culture medium consisting of low molecular weight compounds, known
as basal media. However, most basal media fail to promote successful cell growth by
themselves and require supplementation with more complex and chemically
undefined additives such as blood serum (Castilho, 2008).
Some cultivation processes are based on operational strategies that allow cells
to remain viable, but in a nonproliferative state, so as to prolong the productive phase
and to increase the productivity of the process. By these strategies cell proliferation
may be controlled by adding chemical additives that arrest the cell cycle, usually in the
G1 phase, increasing specific productivity. However, concomitantly undesirable effects
such as cytotoxicity may be observed, which result in a decrease in cell viability and in
the impossibility of maintaining the culture in a nonproliferative state for long periods
of time. Deprivation of specific nutrients and growth factors can also stop cell
proliferation, but in this case cell viability decreases and programmed cell death –
apoptosis – is activated. Currently, much research on the biochemical control of cell
cultures based on preventing the cell death mechanisms, to avoid cell death instead of
inhibiting cell growth, is being carried out with the aim of prolonging the productive
period of a cell culture process (Castilho, 2008).
Any process, industrial or laboratory-based, presents a series of important
variables that represent its state. In the case of cell culture, there are the variables
related to the environment to which the cells are exposed, such as temperature, pH,
dissolved oxygen, nutrients in the culture medium, and metabolite concentrations, as
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well as those related to the cell itself, such as concentration, average size, or the
profile of intracellular enzyme activities (Castilho, 2008).
CHAPTER VI
BRACHYTHERAPY
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6.1 – INTRODUCTION
Brachytherapy was for many years in a state of decline, principally because of
the radiation hazards to users and those associated with the management of patients.
The introduction of afterloading machines in the 1960s provided the means to control
the movement and position of individual radioactive sources and greatly reduced the
radiation exposure to staff. As a result, brachytherapy underwent a renaissance and
provided the necessary stimulus to promote the development of afterloading
brachytherapy techniques. These developments have been further supported by the
availability of nuclides, particularly cobalt-60, cesium-137, and iridium-192 and, more
recently, radioactive seeds of iodine-125 and palladium-105. In parallel with the
technological advances in afterloading machines, there have been major
developments in imaging techniques and computerized planning (Joslin, 2001).
Cancer management generally has undergone major advances since the 1960s
and brachytherapy has played an increasingly important role. The optimal
management of cancer patients requires expert teams who specialize in certain cancer
sites within which brachytherapy may have a specific place. Much of this work is now
being provided on an outpatient or day-care basis and prolonged hospital stay is
proving to be unnecessary (Joslin, 2001).
This chapter starts with a brief explanation of the brachytherapy fundaments to
further understand the mechanisms used by this technique to kill the cancer cells. So,
it will be made a description of the sources used in brachytherapy followed by an
approach of the radiobiology of brachytherapy. At the end of the chapter a description
is made about the dose-rate effect in human cells and a brief come up about predictive
assays for radiation oncology.
The present chapter is central in this thesis project since it is with this
technique that the cancer cells will be killed. The changes that occur in the cells will be
analyzed by image processing and analysis techniques.
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6.2 – BRACHYTHERAPY
The different types of radiation applied for radiobiological research has one
important issue: there the determination of the biological effectiveness of ionizing
photon radiation as a function of photon energy represents a major scientific
objective. Very intense, low-energetic, quasi-monochromatic, and energy tunable (10–
100 keV) channeling radiation (CR) is generated by channeling of relativistic electrons
in diamond crystals (Zeil, 2009).
Usually radiobiological studies are performed on conventional high-voltage X-
ray tubes or medical acceleration facilities. Both sources deliver broad polychromatic
bremsstrahlung with a high photon flux. Thus, therapeutic dose values (few Gy per
daily fraction) can be delivered in a sufficiently small irradiation duration (dose rate ≈1
Gy/min) to be independent from repairing processes in human cells. Due to the high
reproducibility of beam parameters of conventional radiation sources, a large number
of samples can be irradiated in stable conditions in order to cope with the biological
diversity. Considering the dosimetry a standardized radiation field is used. All changes
in the radiation geometry resulting in differences of beam absorption, scattering or
dose build up effect are taken into consideration by applying tabled correction factors.
In practical irradiation experiments, cell samples are irradiated at a vertical beam and
the delivered dose is controlled by presetting certain irradiation duration (Zeil, 2009).
Brachytherapy (sometimes referred to as curietherapy or endocurie therapy) is
a term used to describe the short distance treatment of cancer with radiation from
small, encapsulated radionuclide sources. This type of treatment is made by placing
sources directly into or near the volume to be treated. The dose is then delivered
continuously, either over a short period of time (temporary implants) or over the
lifetime of the source to a complete decay (permanent implants). Most common
brachytherapy sources emit photons; however, in a few specialized situations β or
neutron emitting sources are used. There are two main types of brachytherapy
treatment (Suntharalingam, 2002):
Intracavitary, in which the sources are placed in body cavities close to the
tumor volume;
Interstitial, in which the sources are implanted within the tumor volume.
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The biological effects of radiotherapy depend on dose distribution, treated
volume, dose rate, fractionation and treatment duration. However, these various
factors are of different importance in determining the outcome of external beam
radiotherapy or of brachytherapy (Suntharalingam, 2002).
In brachytherapy, the dose is prescribed to an isodose encircling a small
targeted volume with a very heterogeneous dose distribution. It is minimal at distance
of the radioactive sources, but much higher doses and dose rates are delivered in their
immediate vicinity (Suntharalingam, 2002).
Therefore, the average dose given to the targeted volume is always higher than
the prescribed dose, prescribed at the periphery of the target. This is an important
point to notice as the treatment report contains information regarding only the dose
and dose rate at the reference isodose (Suntharalingam, 2002).
Another distinct feature of brachytherapy is that the doses within an implant
are higher than the tolerance dose levels accepted in external beam irradiation, yet
they are well tolerated because of the volume-effect relationship (very small volumes
can tolerate very high dose levels) (Suntharalingam, 2002).
Finally, time-dose factors differ widely between external beam radiotherapy
and brachytherapy. In external beam radiotherapy, the total dose is delivered in small,
daily fractions of a few seconds or minutes, allowing for full repair between exposures.
The treatment is protracted over several weeks. In contrast, in brachytherapy the dose
is delivered continuously, and treatments tend to be short (several hours to several
days). However, there is a variety of schedules depending on the type of equipment
used (Suntharalingam, 2002).
According to International Comission on Radiation Units & Measurements
(ICRU) report 38, treatment dose rates fall into three categories (Mazeron, 2005):
Low Dose Rate (LDR) brachytherapy ranges between 0.4 and 2 Gy/h. On the
other hand, in routine clinical practice, LDR brachytherapy is usually delivered
at dose rates between 0.3 and 1 Gy/h. This is compatible with conventional
manual or automatic afterloading techniques.
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Medium Dose Rate (MDR) brachytherapy ranges between 2 and 12 Gy/h. MDR
can also be delivered by manual or automatic afterloading, although the latter
is far more frequent.
High Dose Rate (HDR) brachytherapy delivers the dose at 12 Gy/h or more, and
only automatic afterloading can be used because of the high source activity.
A new category is pulsed dose rate (PDR) brachytherapy, which delivers the
dose in a large number of small fractions with short intervals, allowing only for
incomplete repair, aiming at achieving a radiobiological effect similar to low dose rate
over the same treatment time, typically a few days. Finally, permanent implants
deliver a high total dose (for example, 150 Gy) at a very low dose rate, over several
months (Mazeron, 2005).
6.3 – SOURCES IN BRACHYTHERAPY
6.3.1 – RADIUM
Radium was discovered by Marie Curie in 1898. Within 3 years of this discovery,
the first patients were treated with radium implanted into their tumors (Joslin, 2001).
In the UK, St Bartholomew's Hospital received its first radium for clinical use in
1906. Early clinical experience with these sources led to radiation necrosis, and it
became clear that this was due, in part, to the intense beta-ray dose from the radium.
It was not until 1920 that successful filtration of the beta-rays was achieved (Joslin,
2001).
Radium was then used extensively throughout the world. Physicists in the
major clinical centers developed dosimetry systems for interstitial and intracavity
brachytherapy. However, in general, radium has been replaced by other radionuclides
because, although it has a long half-life, it has several disadvantages (Joslin, 2001):
Radium and several of its descendant products, including radon, are alpha
emitters. Radon is a noble gas which is soluble in tissue. This gas could escape
through a hairline crack - not easily detected by a visual check - in the radium
capsule. If an implanted radium source were to be ruptured within the patient's
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body, radium and its daughter products may become deposited more or less
permanently in the bone.
There is also the possibility of damage – by incineration or mechanical means -
when the sources are lost, or while they are being processed, with the
subsequent release of toxic radioactivity to the environment.
The gamma radiation from a radium source is of higher energy than is
necessary for brachytherapy. Radiation protection for these sources requires
large thicknesses of lead, which can cause problems when it comes to:
o transporting sources in heavy containers using very weighty protective
screens around the patient;
o the need for a heavy rectal shield in applicators used for gynecological
treatment.
The practical maximum activity concentration (the specific activity) of radium
salt is low (approximately 50 MBq mm-3 of active volume). Therephore, sources
of higher activity are bulky and u suitable for afterloading systems.
6.3.2 – RADIUM SUBSTITUTES
This was the phrase used to describe the first set of new (artificial)
radionuclides which were found useful for brachytherapy from about 1950 onwards,
though it is only very recently that most radiotherapy centers have stopped using
radium. It was found that there were very few radionuclides with the appropriate
properties of the ideal brachytherapy source. These properties are as follows (Joslin,
2001):
Photon energy should be low to medium (0.03-0.5 MeV) to minimize radiation
protection problems (with the proviso that low-energy radionuclides should not
be used near bone because of the enhanced dose to bone at these energies).
For permanent stock, a long half-life is desirable such that the radioactive
decay within the practical lifetime of the source and its container (typically 10
years) is small.
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For permanent implantation, a fairly short half-life is essential in order to
minimize the time over which special precautions, towards relatives of a
radioactive patient and members of the public, need to be in place.
The nuclide should be available at high specific activity.
There should be no gaseous disintegration product.
The nuclide should be available in a form which does not powder or otherwise
disperse if the source is damaged or incinerated.
The first sources to be used as alternatives to radium were cobalt-60, gold-198,
cesium-137 and iridium-192. These are all described briefly below. The most
commonly used sources at this time are cesium-137 and iridium-192, both of which are
used in after-loading systems. Iridium-192 has the possibility of high specific activity,
which allows it to be used as a high dose-rate (HDR) source (Joslin, 2001).
6.3.3 – NEW SOURCES
The newer sources are not known as radium substitutes, mainly because they
have very different properties from radium, namely very much higher specific activity
(for example, the HDR iridium-192 source) and very different energy. The only new
source that has been accepted into routine clinical use in certain centers throughout
the world is iodine-125. Palladium-103 is also now available as a standard commercial
source (Joslin, 2001).
The other sources that are still at the research stage of development, to find
out whether they can be of use clinically, are samarium-145, americium-241, and
ytterbium-169 (Joslin, 2001).
6.4 – RADIOBIOLOGY OF BRACHYTHERAPY
The biological damage inflicted by irradiation of human cells with ionizing
radiation can be divided into three consecutive steps (Mazeron, 2005):
A very short initial physical phase (about 10-18 s), during which photons interact
with orbital electrons, raising them to higher energy levels inside the atoms
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(excitation), or ejecting some of them from the atoms (ionization). This is the
energy deposition phase.
A chemical phase, again very short (about 10-3 s), during which ionized and
excited atoms interact, leading either directly or indirectly effects through the
formation of free radicals to the breakage of chemical bonds. Free radicals are
highly reactive and can induce chemical changes in biologically important
molecules like DNA. Single-strand or double-strand break in DNA appears to be
the basic damage leading to biological effects.
A biological phase, much longer (seconds to years), during which the cells react
to the inflicted chemical damage. Specific repair enzymes can successfully
repair the vast majority of lesions in DNA. However, few lesions however may
not be repaired and may consequently lead to cell death. Cell death is not
immediate and usually occurs during the next cell division (apoptosis is a minor
process in most human cells). On the other hand, death due to a lethal lesion
may be delayed for a limited number of mitotic divisions (up to 5 or 6). Because
the stem cells are the only cells which divide in normal tissues, the earliest
effect observed is a deficit in stem cells. Later, the loss of stem cells will lead to
a deficit in differentiated cells causing the observed clinical reactions. The early
reactions are seen during the first days or weeks after irradiation (for example,
diarrhea or acute mucositis). They are temporary because the cell deficit is
compensated for by the repopulation of stem cells and subsequently of
differentiated cells. Late reactions due to damage to the late-reacting tissues,
for instance blood vessel damage, fibrosis, telangiectasia, etc., may be seen
after months or years. Damage to these late reacting normal tissues is poorly
repaired and is responsible for most severe complications of radiotherapy.
Tolerance of these tissues is the limiting factor for radiation therapy.
6.4.1 – THE FOUR RS OF RADIOBIOLOGY
A number of biological processes take place during irradiation and modify the
radiation response. These processes are often described as the four Rs of radiobiology.
Each follows a specific time pattern (Mazeron, 2005):
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Repair of DNA damage - it is often referred as repair of “sub-lethal” damage.
Experimental and clinical studies have shown that human tumors strongly differ
in radiosensitivity and radiocurability. This is thought to stem from differences
in capacity for repair of sub-lethal damage. Similar differences are seen
between normal tissues, the haemopoetic system being more sensitive than
the kidney.
Reassortment or redistribution - the cell cycle is divided in four consecutive
stages: G1, S, G2 and M. G1 is a gap of apparent inactivity after a mitosis (M),
before DNA synthesis (S-phase) resumes in view of the following cell division.
G2 is a second gap of apparent inactivity between S phase and M, Figure 6.1.
Radiosensitivity varies along the cell cycle, S being the most resistant phase and
G2 and M the most sensitive. Therefore, cells surviving an exposure are
preferentially in a stage of low sensitivity (G1), i.e. synchronized in a resistant
cell cycle phase. They progress thereafter together into S and then to the more
sensitive G2 and M phases. A new irradiation exposure at this time will have a
larger biological effect (more cells killed). However, while this synchronization
effect has explained some experimental results, redistribution has never been
shown to play a measurable role in the clinic of radiotherapy.
Repopulation - cells surviving an irradiation keep proliferating. This increases
the number of clonogenic cells, i.e. the number that must eventually be
sterilized to eradicate cancer. Consequently, repopulation has a detrimental
effect as far as cancer control is concerned. Stem cells do also proliferate in
normal tissues, which has in this case a protective effect (it helps the tissue to
recover from radiation damage and it adds to DNA repair in cells).
Reoxygenation - because of an inappropriate development of intratumoral
vasculature, every tumor of clinically detectable size contains a large
proportion of poorly oxygenated cells. In addition, the proportion of hypoxic
cells increases with the tumor size. Acutely hypoxic cells are far more
radioresistant than well oxygenated cells. This is expressed by the oxygen
enhancement ratio (OER), i.e. the ratio between radiation doses required in
hypoxia and air to produce the same biological effect. Hypoxic cells usually
survive irradiation, but they progressively (re)oxygenate due to the better
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supply of oxygen available after well oxygenated cells have died, Figure 6.2.
This restores radiosensitivity in the tumor by several mechanisms, but re-
oxygenation occurring at long intervals is probably due to tumor shrinkage
leading to a reduction of the intercapillar distance.
Figure 6.1 - The cell cycle (from Murray, 1993).
Figure 6.2 - Re-oxygenation due to tumor shrinkage (from Mazeron, 2005).
6.4.2 – RADIOBIOLOGY OF LOW DOSE-RATE AND FRACTIONED IRRADIATION
For exposure to sparsely ionizing radiations such as X-rays or gamma-rays, the
degree of a biological effect produced can depend as much on the dose rate as on the
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total dose received. The importance of dose rate and dose fractionation effects has
been recognized for more than 70 years (Joslin, 2001).
Studies of Regaud and his collaborators were perhaps the first to show the
potential therapeutic advantages of dose fractionation in the treatment of patients
with cancer by radiation. Since that time, the evolution of treatment regimes involving
dose time variations have increasingly improved cancer radiotherapy and the evolution
continues even today. In cancer radiotherapy, the dose rate and dose fractionation are
not the only important factors, but also in connection with the mutagenic and
oncogenic hazards of radiation exposure (Joslin, 2001).
Normally, reducing the dose rate decreases the biological effectiveness, that is,
decreasing the dose rate generally increases the dose necessary to yield the same level
of effect. A number of factors can contribute to the dose rate or dose fractionation
effect, depending on the conditions and cell or tissue system involved. For example, in
a tissue or tumor exposed over a period of weeks or months, cells may migrate into or
out of the radiation field, or the oxygenation status may change to alter the intrinsic
radiosensitivity of the cells during the course of treatment (Joslin, 2001).
6.4.2.1 – SPLIT-DOSE RECOVERY FROM SUB-LETHAL DAMAGE IN MAMMALIAN CELLS
For ionizing radiation damage in mammalian cells, the first direct
demonstration of a cellular repair process affecting cell killing that could explain dose
rate and dose fractionation effects seen in mammalian tissues or tumors was provided
by Elkind and Sutton. These researchers reasoned that because the shouldered survival
curves for mammalian cells exposed to X-rays or gamma-rays indicate the involvement
of a damage accumulation process in cell killing, then cells surviving a dose beyond the
shoulder region of the curve (survivals below about 10%) would contain sub-lethal
damage capable of interacting with further damage to become lethal. Elkind and
Sutton questioned whether this sub-lethal damage might remain in surviving cells, in
which case their dose response at some later time would not be 'shouldered'.
Alternatively, if the sub-lethal damage were repaired, the cells would be expected to
respond as if they had never been irradiated, i.e., the surviving cells would display the
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same shouldered survival curve for subsequent irradiation. The latter was found to be
the case, as is illustrated in Figure 6.3 from their early work (Joslin, 2001).
The curve indicated by filled circles in Figure 6.3 illustrates a dose-response
curve for irradiations requiring only a few minutes each - high dose rate (HDR) or
'acute' exposures - over a range of doses from 0 (zero) to about 12.5 Gy. Curves
starting at a dose of 5.05 Gy illustrate dose-response curves for cells surviving a first
dose of 5.05 Gy followed by various additional doses given either immediately after
the first dose (filled circles) or 18 h following the first dose (open circles). During the
time interval between the first and second doses, the surviving cells 'restored
themselves to good (original) condition. They had repaired this so-called sub-lethal
damage so they again had to accumulate damage for cell killing (Joslin, 2001).
This sub-lethal damage repair (SLDR) is a repair process operationally defined in
terms of the observations demonstrating the phenomenon, i.e., the increase in the
fraction of cells surviving. It says nothing about what is being damaged and repaired
(Joslin, 2001).
Figure 6.3 – Initial survival curve (closed circles) and fractionation curve (open circles) for ‘clone A’ cultured Chinese
hamster cells (from Joslin, 2001).
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6.4.2.2 – CELL-CYCLE COMPLICATION: A HETEROGENEOUS POPULATION
In the early 1960s, Terasima and Tolmach first showed with synchronized
cultures of HeLa cells that cellular responses varied greatly throughout the cell cycle.
During mitosis cells become very loosely attached to the surface of the culture vessel
and these were collected by a 'shakeoff method', leaving the interphase cells behind in
the flask. Appropriate numbers of mitotic cell populations were inoculated into dishes.
After various periods of incubation, different sets of the synchronously progressing
cells were irradiated when they were (for the most part) at a particular stage of the
cycle. When the dose was the same for all cultures, but the time after mitotic shake-off
was varied, the proportion surviving to form colonies varied. Parallel cultures were
flash labeled with tritiated thymidine (3H TdR) to monitor the synchronous progression
of cells into and out of S phase.
For irradiation of mitotic cells survival was low, indicating a high sensitivity for
this cell cycle phase. As cells progressed into mid-G1 (2-6 h), the cells were more
resistant. At around the G1/S border and in early S phase cells were again more
sensitive, and as cells progressed toward late S phase and early G2 the cells again
became more resistant. Because there is some variation from one cell to the next in
the cell cycle transit times, particularly through G1, there is an increasing decay in
synchrony and therefore the resolution of experimental data on cycle-dependent
radiosensitivity with time. Nevertheless, there is clearly a large variation in the
radiation response of cells through the cell cycle. Other cells have shown similar cell-
cycle-dependent variations in radiosensitivity, although the peak of resistance in G1 is
not well resolved experimentally in cells with very short G1 transit times.
The sensitivity of cells in different parts of G2 is difficult to determine by the
synchronization procedure described above, because of synchrony decay during the
passage of the starting population of mitotic cells through their first G1 and S phase,
and because G2 transit times are relatively short (about 1-2 h). However, a
modification of the technique allows a much greater resolution for studying G2
sensitivity. This is sometimes called 'retroactive synchronization': cells are first
irradiated and then, as a function of time, cells arriving in mitosis are harvested by
mitotic shake-off and plated for survival (Joslin, 2001).
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6.4.2.3 – RADIATION AFFECTS CELL-CYCLE PROGRESSION ITSELF
Radiation effects on cell cycle progression are yet another factor that influences
dose rate effects. Ionizing radiation reduces the mitotic index within a short time after
exposure (mitotic delay). This delay has been studied extensively in more recent times,
and the timing for the reduction in mitotic index and subsequent recovery clearly
indicates the delay is reversible and occurs sometime during G2. The production of this
effect is very radiosensitive (Joslin, 2001).
Appreciable proportions of the cells are delayed by doses of the order of tens
of cGy. The G2 delay increases with dose and frequently corresponds to about 1-3 hGy1
depending on the particular cells and on the stage in the cycle when the cells are
irradiated. Most of the extensive work on cell cycle progression delays in cultured
mammalian cells was carried out in the 20-year period between about 1965 and 1985
using 'transformed' or tumorigenic cell lines. Delays in G1 or S phase were relatively
minor and, in many cases, undetectable in the 0-5 Gy dose range. As it turned out, the
generalization or extrapolation of the results to normal or untransformed cells was
unwarranted. Some investigators during this period, even as early as 1968, reported
appreciable delays in the progression of 'non-transformed' cells from G1 into S phase
or in the transition from the non-cycling G0 to the cycling state after low dose or low
dose-rate (LDR) irradiation (Joslin, 2001).
In a split-dose experiment, the first dose kills a fraction of the cells, but this
fraction is different in all portions of the cell cycle. Survival for cells in the most
sensitive phases will be much lower and, in resistant phases much higher than the
average. Thus, after the first dose the population of cells surviving will not be
distributed around the cell cycle as it normally is, but will be highly enriched in cells
from more radioresistant phases. It is these surviving cells that determine the further
reduction in survival measured by the second dose. If the first dose is of sufficient
magnitude to bring the survival down to, say, 10% or less, then these surviving cells
will still contain sub-lethal damage capable of interacting with an additional dose.
Thus, if the additional dose were given immediately after the first, the survival
reduction would effectively continue down along the single dose survival curve. With a
time delay, however, three things happen (Joslin, 2001):
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First, the sub-lethal damage begins to repair, and the half-time for this process
is relatively fast being 0.5-2h depending on the system. The effect of this repair
process on the surviving cells is to make them more resistant to a second dose,
so the proportion surviving will increase with an increasing time interval
between the first and second doses. This process is 90% or more complete
within about 2-4 h.
Second, the cells surviving the first dose which were already in the more
resistant phases of the cycle begin to progress and, at least for the first few
hours; this progression can only be toward a more sensitive state. For initially
log phase populations it is no longer surprising then that with increasing time,
between about 3 to 6 or 7 h after the first dose, the survival after the second
dose actually decreases. The first dose also produces a mitotic and division
delay, so the increase in number of surviving colonies with increasing time
before the second dose is not due to an actual increase in numbers of surviving
cells from cell division, at least for the first few hours. For example, after a first
dose of 5 Gy, there would be essentially no cell division for some 5-10 h,
depending on the cells.
Third, after the mitotic delay, cell division would resume, so instead of having
only one viable cell per surviving colony, as would be the case immediately
after the first dose, some, and eventually all, would have two or more viable
cells, both of which would have to be killed to prevent colony formation at that
locus.
Especially appropriate for cell culture applications are 'normal' or 'non-
transformed' cells, which form so-called contact-inhibited monolayers. In such
monolayers, the cells enter a non-cycling G0 state, where they are no longer a
heterogeneous population with respect to the radiosensitivity of subpopulations and,
of course, where cell cycle progression and cell division during treatment do not
complicate the picture. One additional issue that does arise with the use of contact-
inhibited monolayer systems as well as organized tissues in vivo is that another,
perhaps related, repair process known as 'potentially lethal damage' repair (PLDR),
also plays an important role (Joslin, 2001).
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6.4.2.4 – POTENTIALLY LETHAL DAMAGE
When contact-inhibited monolayers of non-transformed cells are irradiated for
a cell survival experiment, the flasks must, of course, be sub-cultured and plated at a
low enough density to allow surviving cells to form colonies for the surviving fraction
to be assessed. As it turns out, the proportion of irradiated cells surviving a single
acute dose in such cultures depends greatly on whether the cells are sub-cultured,
diluted, and plated for the colony forming assay immediately after irradiation, or the
sub-culture is delayed for some hours, in which case the survival is much higher. The
interpretation of this phenomenon is that because damage is lethal in some cells under
one set of circumstances (e.g., immediate subculture) but is not under another set
(e.g., delayed subculture), such damage must be considered not as 'inevitably lethal'
but only 'potentially lethal', depending on the circumstances (Joslin, 2001).
Another factor for the study of cellular radiation responses relevant to normal
tissue effects, is that virtually no normal tissue contains cells existing in the abundant
nutrient conditions of in vitro culture and which are proliferating with growth fractions
near 1.0 and doubling times of 12-24 h. Perhaps intestinal crypt stem cells come as
close to this unusual situation as any in vivo. The non-cycling contact-inhibited state for
normal cells in culture may fail to simulate all conditions in vivo, but the conditions are
perhaps a little closer in general to those in most cell renewal tissues, and much closer
with respect to the cell cycling status (Joslin, 2001).
6.5 – DOSE-RATE EFFECTS WITH HUMAN CELLS
The term 'dose-rate effect' refers to the change in sensitivity or tissue response
when the dose rate of irradiation is modified. Dose-rate effects are common in
mammalian cell systems, including human tumors and normal tissues. The response of
these tissues is complex, depending in part on the radiosensitivity of the stem cells (or
'clonogenic' cells) of the tissue, but also on the modifying effects of cell proliferation
and such physiological parameters as oxygenation and growth factors (Joslin, 2001).
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6.5.1 – TIME-SCALE OF RADIATION ACTION
Time-scale of biological effects of ionizing radiation is illustrated in Figure 6.4. It
is the operation of some of the processes represented in this chart that gives rise to
dose-rate effects. Immediately after exposure, free-radical processes take place
leading to damage of many constituents of the cell. Because of its vital nature and the
relative uniqueness of its genetic message, DNA is the most important of these
damaged molecules (Joslin, 2001).
Under physiological conditions the rapid free-radical reactions are complete
within around 1 ms, during the subsequent few minutes enzymatic processes begin to
operate on the damaged molecules. Some of these act to repair the damage; others
leave the molecules in a changed but stable form and this is described as 'misrepair.'
Within a few hours these enzymatic processes will be complete (Joslin, 2001).
Repair of radiation damage to DNA is highly effective in most cell types: a 1 Gy
dose will induce upwards of 1000 DNA strand breaks in every irradiated cell. Roughly
half of the cells will survive this dose, so strand-break rejoining must be a remarkably
error-free process. Most strand breaks are to one strand only of the double helix, but a
small proportion can be recognized as affecting both DNA strands (double-strand
breaks - dsb). There is evidence that these are much more serious for the viability of
the cell. Even so, the great majority of dsb are also successfully repaired, and of
particular importance are dsb that arise from clusters of ionizations at the end of the
tracks of secondary electrons: these can involve severe damage to the DNA molecule
(so-called 'multiply damaged sites') and, it may be that these events have a relatively
low probability of successful repair and a correspondingly high likelihood of leading to
cell death or mutation (Joslin, 2001).
At longer intervals after irradiation cell proliferation will take place within
tissues, leading to the replacement of radiation-damaged cells. In tumors this may lead
to recurrence or to a reduced likelihood of success as a result of subsequent treatment
(Joslin, 2001).
In normal tissues, proliferation may prevent tissue breakdown and the
observed early effects of irradiation will then be minimal. However, if the level of cell
killing is greater and of such a severity that it cannot be counteracted by proliferation,
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then serious tissue damage may appear. At even longer time intervals after irradiation
(months to years), the very long-term effects will become apparent, including tissue
failure, formation of new tumors and mutational effects in germ cells (Joslin, 2001).
Figure 6.4 - Time-scale of the effects of radiation exposure on biological systems (from Joslin, 2001).
6.5.2 – MECHANISMS OF THE DOSE-RATE EFFECT
Observed dose-rate effects derive from the operation of the processes just
described. Usually, clinical external-beam treatments are given within a few minutes.
These brief exposures are long enough for the initial chemical effects of irradiation to
be complete, but are too short for the subsequent enzymatic and proliferation
processes to take place. As radiation dose rate is lowered, the irradiation time for a
given dose, increases and it becomes possible for such processes to take place during
radiation exposure. These will modify the extent of damage and thus lead to a dose-
rate effect (Joslin, 2001).
Four main processes lead in this way to the dose-rate effect. They are the '4Rs
of radiobiology': repair, redistribution, repopulation, and reoxygenation, as described
before. Among these repair is the fastest, the time required to repair half the induced
damage is about 1 h. This means that as soon as the duration of exposure becomes a
significant fraction of an hour some repair will take place during irradiation. At the
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other extreme, repopulation is a much slower process: repopulation requires cell
multiplication and human cells cannot divide in less than about a day. Therefore,
repopulation will only have a significant effect when the exposure time is a day or
more. Redistribution and reoxygenation probably have a speed that is intermediate
between these two processes. Figure 6.5 illustrates the range of dose rates over which
each of these processes might be expected to influence radiation action. For dose
rates in excess of a few gray per minute none of the processes will take place
significantly during irradiation and there will be no dose-rate effect due to them
(Joslin, 2001).
At much higher dose rates than illustrated a further process, the consumption
of oxygen by radiochemical reactions leading to partial hypoxia, may have an effect. At
dose rates around 1 Gymin-1, sometimes used for 'high dose rate' or 'acute'
irradiations, there may be a small amount of repair during irradiation and such
treatments will be slightly less effective than if given at a higher dose rate (Joslin,
2001).
Figure 6.5 - Range of dose rates over which repair, reassortment, and repopulation may influence radiation effects
(from Joslin, 2001).
The curves drawn in Figure 6.5 to represent the effects of repopulation or
reassortment are diagrammatic. Repopulation is a much slower process than repair
and, only when the exposure time becomes a significant proportion of a cell cycle time
(perhaps 1-4 days in human tumor and normal tissue cells) will it have a significant
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effect during the period of irradiation. Reassortment (otherwise known as
redistribution) refers to the effects that derive from the movement of surviving cells
through the cell cycle after a first dose or increment of dose radiation (Joslin, 2001).
These effects may modify the response of a tissue or cell system to subsequent
irradiation and, occur over a dose rate range that is somewhere intermediate between
those of repair and repopulation. The comparative effects of repair and repopulation
are further illustrated in Figure 6.6. This figure shows actual calculations for a typical
human cell line, based on a repair half-time of 0.85 h and an α/β ratio of 3.7 Gy (Joslin,
2001).
Curves of Figure 6.6 are drawn for four different cell population doubling times
and the calculations show the radiation doses (i.e., ED50 values) for a survival of 0.01.
For these parameter values, there is no effect of proliferation at dose rates above 1
cGymin-1, but as dose rate is lowered to 0.01 cGymin-1 dramatic effects are predicted,
depending on the cell population doubling time. The implication for brachytherapy is
that above 1 cGymin-1 repopulation effects can be ignored, but below this dose rate
they can, under some circumstances, predominate over effects due to incomplete
repair (Joslin, 2001).
Figure 6.6 - In human cell systems proliferation probably affects radiation response for dose rates below about
1Gyh-1
(from Joslin, 2001).
6.5.3 – DOSE-RATE EFFECTS IN HUMAN TUMOR CELLS
Pioneering experimental studies of the dose-rate effect were made in a number
of publications by Hall, Bedford and Mitchell (“Dose rate: its effect on the survival of
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 162
HeLa cells irradiated with gamma rays”, Radiat Res 1964; 22: 305-15). The experiments
were performed on a variety of cell lines, mainly derived from experimental animals
but also including the long established HeLa cell line (derived from a human cervix
carcinoma). They showed that the dose rate effect mainly appeared over the range of
dose rates from 1 Gymin-1 down to 0.1 cGymin-1. There was considerable variation in
the magnitude of the dose-rate effect (i.e., the relative radiosensitivities at high and
low dose rates). Steel et al. analyzed these data and showed that derived values for
the half-time for repair of radiation damage ranged widely: from below 0.1 h to above
than 1 h (Joslin, 2001).
Studies on human tumor cell lines taken from a variety of tumor types were
reported by Steel et al (“The dose-rate effect in human tumor cells”, Radiother Oncol
1987; 9: 299-310). Most of the cell lines were newly established. In some cases the
cells were taken directly from human tumors that had first been grown as xenografts
in immune-deficient mice; other studies were made on cell lines established in tissue
culture. They were irradiated with cobalt-60 gamma-radiation at dose rates ranging
from 1 to 150 cGymin-1 at body temperature and under conditions of controlled
oxygenation. Cell survival was measured using a colony assay, either in soft agar or in
monolayer, depending on the growth characteristics of the cell line. Data on four cell
lines are shown in Figure 6.7, covering the range of responses seen in a larger group of
human tumor cell lines. Figure 6.7a shows results at high dose rate. The data are fitted
by a linear quadratic equation; there is a well-defined initial slope to the data, which
are clearly consistent with a continuously bending relationship. The range of
sensitivities is considerable (Joslin, 2001).
The doses required for a survival of 0.01 range from 3.6 Gy in the HX142
neuroblastoma to 10.9 Gy in the RT112 bladder carcinoma (i.e., by a factor of 3). In the
initial dose region the factor is greater. Figure 6.7b shows the results for the same cell
lines at the low dose rate of 1.6 cGy min '. The curves have fanned-out and become
straight or almost so on the semi-logarithmic plot. It can be seen that at low dose rate
the lines seem to extrapolate the initial slopes of the high dose-rate curves (Joslin,
2001).
The range of sensitivities among the cell lines is now larger: by a factor of
approximately 10. The data shown in Figure 6.7 indicate the range of sensitivities seen
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among tumors of different histological types. Less information is available about the
range of sensitivities among tumors of the same type, from diverse patients. Kelland
and Steel (“Differences in radiation response among human cervix carcinoma cell
lines”, Radiother. Oncol., 13,225-32) studied five cell lines newly established from
human cervical carcinomas. They found that at high dose rate the dose to produce a
surviving fraction of 0.01 ranged from 5 to 10.5 Gy. The dose-rate sparing factors (the
dose at 1.6 cGymin-1 compared with the dose at 150 cGymin-1) ranged from 1.1 to 1.6.
This showed that among tumors of the same type there were considerable
radiobiological differences that could be clinically significant. There may be a number
of causes of failure in brachytherapy and these include the inherent insensitivity of the
tumor cells to radiation. A so-far insufficiently explored aspect of brachytherapy is the
attempt to develop predictive tests of radiosensitivity in order to identify patients
most at risk of recurrence. The data in Figure 6.7 clearly indicate that such tests should
be made at low dose rate, where the differences among cell lines are greatest (Joslin,
2001).
Figure 6.7 - Cell survival curves for four human tumor cell lines irradiated at (a) 150 cGy min-1 or (b) 7.6 cGy min-1
HX142, neuroblastoma; HX58, pancreas carcinoma; HX156, cervix carcinoma; RT112, bladder carcinoma (from
Joslin, 2001).
6.5.4 – EFFECT OF IRRADIATION ON CELL CYCLE PROGRESSION
Irradiation at high dose rate blocks cell entry into mitosis. The cell cycle may be
interrupted at a number of so called 'check-points', and the biochemical processes
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 164
involved in these arrests are the subject of intense laboratory research at the present
time. At high dose rate, there are two reasons why proliferation effects during
irradiation are unimportant: irradiation times are too short, and the cells are subject to
mitotic delay and therefore inhibited from proliferating. As dose rate is reduced, both
these factors become less severe and cell cycling takes place during irradiation, thus
counteracting the effect of irradiation (Joslin, 2001).
Skladowski et al. (“Cell-cycle progression during continuous irradiation of a
human bladder carcinoma cell line” Radiother. Oncol., 28,219-27) concluded that cell-
cycle effects in tumor cells are unlikely to be of any great significance, in relation to the
cell-killing effect at different distances from an implanted radiation source. Overall
treatment times in brachytherapy tend to be short compared with external-beam
treatment and proliferation effects are correspondingly of less significance (Joslin,
2001).
6.5.5 –CELL KILLING AROUND AN IMPLANTED RADIATION SOURCE
The non-uniformity of radiation field around an implanted source has
important radiobiological consequences. Close to the source, the dose rate is high and
the amount of cell killing will be close to that indicated by the acute-radiation survival
curve. As the distance from the source is increased, two changes take place: cells will
be less sensitive to lower dose rates, and within a given period of implantation the
accumulated dose will also be less. These two factors lead to a very rapid change of
cell killing with distance from the source.
This is illustrated in Figure 6.8 for the case of a point radioactive source. A
source strength was chosen that gives 75 Gy in 6 days at a range of 2 cm. Three
different tumor-cell sensitivities were assumed, as shown in the upper panel. It is the
low dose-rate sensitivities that matter for this calculation. For spherical shells
containing 109 clonogenic cells at different distances from the source, it was possible
to calculate the surviving fraction from 6 days irradiation, the absolute number of
surviving clonogenic cells, and thus the probability that all cells in the shell would be
killed. The results are shown in the lower panel. For cells of any given level of
radiosensitivity there will be cliff-like change from high to low local cure probability,
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taking place over a radial distance of a few millimeters. Note that the order of the lines
in the upper and lower panels of this figure is reversed: very sensitive tumor cells (lines
A) can be cured out to a greater radius than less sensitive cells (B) or very
radioresistant cells (C). The steepness of the tumor control curves derives in part from
the underlying assumed Poisson relationship between the average number of surviving
cells per shell and the control probability. As is the case with tumor control by
external-beam irradiation, in reality, there will be factors that make the tumor control
curves less shallow: heterogeneity, for instance (Joslin, 2001).
Within tissues (tumor or normal) that are close to the source, the level of cell
killing will be so high that cells of any radiosensitivity will be killed. Further out, the
effects will be so low that even the most radiosensitive cells will survive. Between
these extremes there is a critical zone in which differential cell killing will occur. In this
critical region the radiation dose rate will be low. For this reason, one would argue that
the low dose-rate survival curves as shown in Figures 6.5 and 6.6 are more clinically
realistic than the high dose-rate curves, certainly for brachytherapy. Figure 6.9
contrasts this situation with external beam radiotherapy, where the aim is to deliver a
uniform radiation dose across the tumor. Only in a narrow zone around an implanted
source (where the surviving fraction changes from, say, 10-20 to 10-6) will
radiobiological considerations be of interest or importance in relation to tumor
control. The same principle will apply to normal tissue damage: serious damage to
normal structures depends on making sure that they are outside the corresponding
'cliff' (Joslin, 2001).
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 166
Figure 6.8 - The likelihood of cure varies steeply with distance from a point radiation source. The radius at which
failure occurs depends upon the steepness of the survival curve at low dose rate (upper panel) (from Joslin, 2001).
Figure 6.9 - Variation of cell kill around a point source of radiation (from Joslin, 2001).
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6.5.6 – IMPLICATIONS FOR CLINICAL BRACHYTHERAPY
The radiobiology of low dose-rate irradiation is now fairly well understood.
Although data are not available on a wide range of human tumors, the data that one
have do indicate the range of responses that are seen for human cells in tissue culture.
It is likely that these will be realistic for effects on well-oxygenated cells in the patient.
Much less is known about the effects of low dose-rate irradiation on hypoxic cells in
vivo. These are, of course, less sensitive to high dose-rate irradiation. The work of Ling
et al. (“The variation of OER with dose rate”, Int. J. Radial. Oncol. Biol. Phys.,11, 1367-
73) showed that the sparing effect of low dose-rate irradiation as a function of oxygen
concentration was complex. Lowering the dose rate initially had more effect on the
oxic cells than on the hypoxic cells. Further lowering of dose rate had consequently
more effect on the hypoxic cells. Although for such reasons there is much that still
needs to be understood about the tumor effects of brachytherapy, some simple
conclusions can be drawn:
1. In the dose-rate range from a few Gymin-1 down to a few cGymn-1, repair of
radiation damage is the main modifying process on radiosensitivity. The effects
are large, leading to a change in the isoeffective radiation dose by a factor of 2
or more. Below 1 cGymhr-1, cell proliferation will play an increasingly strong
role in making tumors or normal tissues less sensitive to radiation damage.
2. There is evidence for a dose-rate effect in the region of 1 Gymin-1. If, in
external-beam radiotherapy, a change of machine or of source-skin distance
leads to a substantial lowering of dose rate, then a dose rate correction should
be considered.
3. The biological effect of irradiation changes rapidly at dose rates around 10
cGymin-1. This may mean that greater precision in dosimetry and dose
prescription is required in high dose-rate brachytherapy than when a low dose
rate is used.
4. Tumor cells of different origins show very different response to low dose-rate
irradiation. Theoretical calculations suggest that as one move out from an
implanted radiation source the local tumor control probability will change
rapidly, i.e., there will be sudden failure to eradicate all clonogenic tumor cells.
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The prediction that the range at which this occurs will depend strongly on the
low dose-rate radiosensitivity of the tumor cells could be clinically important.
There is a strong case for predictive testing of tumors that are to be treated
with curative intent by brachytherapy in order to predict those that require a
greater or lesser range of dose distribution (Joslin, 2001).
6.6 – PREDICTIVE ASSAYS FOR RADIATION ONCOLOGY
Since the 1980s, radiation oncologists and biologists have recognized the need
for additional assays on an individual patient basis that would select the most
advantageous treatment approach. Hence, it should emphasize assays for individual
patients for several reasons (Joslin, 2001).
First, the cellular radiation sensitivity of the tumor may differ among
individuals, even for tumors of the same histological type. If the radiosensitivity of the
individual's tumor were precisely known, perhaps total radiation doses could be
adjusted before the end of therapy to maximize tumor response. Alternatively, the
option of using radiation sensitizers for 'radioresistant' tumors would have a more
rational basis (Joslin, 2001).
Second, normal-tissue radiation sensitivity may differ among individuals. This is
an important point because the total radiation dose that can be delivered to a
patient's tumor is often limited by normal tissue tolerance. Stated differently,
frequently radiation oncologists are compelled to treat a patient's tumor with
radiation doses that are dictated not by tumor sensitivity but by normal-tissue
tolerance, which in many instances results in inadequate dose to the tumor. If one
assumes there is a Gaussian distribution of normal-tissue radiosensitivities among
humans, then the most sensitive individuals in the population may well dictate
radiation tumor doses utilized in the clinic. Because the radiation tumor control dose
response curve is quite steep for many tumors, modest increases in the total radiation
dose delivered would be expected greatly to enhance tumor control. If it were
determined that the patient's normal-tissue radiation response were toward the
'radioresistant' edge of the Gaussian distribution, consideration could be given to
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administering higher radiation doses. Alternatively, if the patient's normal-tissue
radiation response was toward the 'radiosensitive' edge of the Gaussian distribution,
the use of radioprotectors could be considered. Unfortunately, selective normal-tissue
radioprotectors have yet to be identified (Joslin, 2001).
Third, biological, environmental, and physiological factors of tumors may differ
among individuals. Factors such as tumor pH, hypoxia, blood flow, and growth of the
tumor in terms of cell-cycle parameters and potential tumor doubling times (Tpot) can
influence the overall radiation responsiveness of the tumor. If these factors were
known prior to therapy, the use of hypoxic cell radiosensitizers or, in the case of Tpot
values, alteration of fractionation/time schedules could be considered (Joslin, 2001).
Numerous predictive assays have been developed over the past two decades to
address many of the points cited above and several have been evaluated in a clinical
setting (Joslin, 2001).
6.7– SUMMARY
Brachytherapy is an important radiation technique in the treatment of
malignant disease that allows conformal treatment without heavy technological
involvement. However, since it generally involves invasive procedures (interstitial
brachytherapy), except for special instances in which intracavitary techniques may be
employed, brachytherapy is relegated to second place behind external beam
radiotherapy in the treatment of malignant disease (Suntharalingam, 2002).
A typical radiation oncology department will treat about 80% of its patients
with the various external beam techniques and about 10–20% of its patients with
brachytherapy. The basic principles of brachytherapy have not changed much during
the past 100 years of radiotherapy; however, the advent of remote afterloading
brachytherapy has made brachytherapy much more efficient for the patient and safer
for staff from the radiation protection point of view. In terms of physics human
resource needs, a brachytherapy patient requires considerably more involvement than
an average external beam patient (Suntharalingam, 2002).
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Nearly every malignant disease in the human body has been treated with
brachytherapy; however, gynaecological cancer treatments provide the greatest
success and permanent prostate implants are becoming increasingly common.
(Suntharalingam, 2002)
There are also various sites for which brachytherapy has proven a complete
failure. The newest application of brachytherapy is intravascular (also referred to as
endovascular) brachytherapy, used for the prevention of restenosis in arteries
following coronary arterial angioplasty (Suntharalingam, 2002).
This radiation technique was used to kill the prostate and breast cancer cells
that will be studied by me in my dissertation thesis.
CHAPTER VII
BASIC CONCEPTS OF DIGITAL IMAGE PROCESSING
CHAPTER VII – BASIC CONCEPTS OF DIGITAL IMAGE PROCESSING
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 173
7.1 - INTRODUCTION
Digital image processing is an area characterized by the need for extensive
experimental work to establish the viability of proposed solutions to a given problem.
An important characteristic underlying the design of an image processing system is the
significant level of testing and experimentation that normally is required before
arriving at an acceptable solution. This characteristic implies that the ability to
formulate approaches and quickly prototype candidate solutions generally plays a
major role in reducing the cost and time required to arrive at a viable system
implementation (González, 2004).
MATLAB is a high-performance language for technical computing. It integrates
computation, visualization, and programming in an easy-to-use environment where
problems and solutions are expressed in familiar mathematical notation. Typical uses
include the following:
Math and computation;
Algorithm development;
Data acquisition;
Modeling, simulation and prototyping;
Data analysis, exploration and visualization;
Scientific and engineering graphics;
Application development, including graphical user interface building.
MATLAB is an interactive system whose basic data element is an array that
does not require dimensioning. This allows formulating solutions to many technical
computing problems, especially that involving matrix representation, in a fraction of
the time it would take to write a program in a scalar non-interactive language such as C
or Fortran (González, 2004).
The name MATLAB stands for matrix laboratory and was written originally to
provide easy access to matrix software developed by the LINPACK (Linear System
Package) and EISPACK (Eigen System Package) projects (González, 2004).
The Image Processing Toolbox is a collection of MATLAB functions (called M-
functions or M-files) has extended the capability of the MATLAB environment for the
solution of digital image processing problems (González, 2004).
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In this chapter, it is performed a description of the basic concepts of digital
image processing to provide background information of what is performed with the
cells images that I will study in my dissertation thesis. The cell images will be processed
using the image processing program MATLAB.
7.2 – PRE-PROCESSING EVALUATION OF DIGITAL IMAGES
After digital images have been captured, and prior to initiating processing
algorithm applications, each image should be evaluated with regard to its general
characteristics, including noise, blur, background intensity variations, brightness and
contrast, and the general pixel value distribution (histogram profile). Attention should
be given to shadowed regions to determine how much detail is present, as well as
bright features (or highlights) and areas of intermediate pixel intensity (Davidson,
2007).
Each image-editing program has a statistics or status window that enables the
user to translate the mouse cursor over the image and obtain information about
specific pixel values at any location in the image. For example, the Photoshop Info
Palette provides continuously updated pixel information, including x and y coordinates,
RGB (red, green, and blue) color values, CMYK (cyan, magenta, yellow, black)
conversion percentages, and the height and width of a marquee selection within the
image. Preference options in the palette display include selecting alternative color-
space models for information readout. Among the models available in Photoshop are
grayscale, HSB (hue, saturation, and brightness), web color (the 216 colors that overlap
in the Windows and Macintosh 8-bit or 256 color display palettes), actual color,
opacity, and Lab color (device-independent color space) (Davidson, 2007).
By evaluating the intensities (grayscale and color) and histogram positions of
various image features, the black and white set points for stretching and sliding of the
entire histogram for contrast adjustments can be determined. The image should also
be checked for clipping, which is manifested by the appearance of saturated white or
underexposed black regions in the image. In general, clipping should be avoided, both
during image acquisition, and while the image is being processed. Images that have
been adversely affected by background intensity variations should be corrected by flat-
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field techniques or background subtraction prior to applying histogram manipulations
(Davidson, 2007).
7.3 – LOOK-UP TABLES
Several of the fundamental digital image processing algorithms commonly
employed in optical microscopy function through a technique known as single-image
pixel point operations, which perform manipulations on sequential individual pixels
rather than large arrays. The general equation utilized to describe single-image pixel
point processes for an entire image array is given by the relationship:
where I(x,y) represents the input image pixel at coordinate location (x,y), O(x,y) is the
output image pixel having the same coordinates, and M is a linear mapping function. In
general, the mapping function is an equation that converts the brightness value of the
input pixel to another value in the output pixel. Because some of the mapping
functions utilized in image processing can be quite complex, performing these
operations on a large image, pixel-by-pixel, can be extremely time-consuming and
wasteful of computer resources. An alternative technique used to map large images is
known as a look-up table (LUT), which stores an intensity transformation function
(mapping function) designed so that its output gray-level values are a selected
transformation of the corresponding input values (Davidson, 2007).
Figure 7.1 – Inversion and threshold map look-up table operation (from Davidson, 2007).
(a) (b) (c)
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When quantized to 8 bits (256 gray levels) each pixel has a brightness value that
ranges between 0 (black) and 255 (white), to yield a total of 256 possible output
values. A look-up table utilizes a 256-element array of computer memory, which is
preloaded with a set of integer values defining the look-up table mapping function.
Thus, when a single-pixel process must be applied to an image using a look-up table,
the integer gray value for each input pixel is utilized as an address specifying a single
element in the 256-element array. The memory content of that element (also an
integer between 0 and 255) overrides the brightness value (gray level) of the input
pixel and becomes the output gray value for the pixel. For example, if a look-up table is
configured to return a value of 0 for input values between 0 and 127 and to return a
value of 1 for input values between 128 and 255, then the overall point process will
result in binary output images that have only two sets of pixels (0 and 1). Alternatively,
to invert contrast in an image, a look-up table can return inverse values of 0 for 255, 1
for 254, 2 for 253, and so forth. Look-up tables have a significant amount of versatility
and can be utilized to produce a wide variety of manipulations on digital images
(Davidson, 2007).
Image transformations that involve look-up tables can be implemented by
either one of two mechanisms: at the input so that the original image data are
transformed, or at the output so that the transformed image is displayed but the
original image remains unmodified. A permanent transformation of the original input
image may be necessary to correct for known defects in detector properties (for
example, nonlinear gain characteristics) or to transform the data to a new coordinate
system (from linear to logarithmic or exponential). When only the output image should
be modified, the image transformation is performed just before the digital image is
converted back to analog form by the digital-to-analog converter for display on a
computer monitor. In some cases, the results of the transformation specified by the
output look-up table(s) are displayed visually on the monitor, but the original image
data are not altered (Davidson, 2007).
Look-up tables are not restricted to linear or monotonic functions and a variety
of nonlinear look-up tables are utilized in signal processing to correct for camera
response characteristics or to emphasize a narrow region of gray levels. A good
example of the utility of a nonlinear look-up table is the correction of recorded images
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that have been inadvertently captured with an incorrect camera gamma adjustment.
In addition, monochrome or color images can also be converted to generate negatives
for photography. Other applications include pseudocoloring and sigmoidal look-up
tables that emphasize a selected range of gray values targeted to enhance desired
features or to adjust the amount of image contrast (Davidson, 2007).
Presented in Figure 7.1 are look-up table mapping functions for image contrast
inversion using both a 256-element memory pre-loaded register and a table map
(Figure 7.1(a)), and a thresholding operation using only a table map (Figure 7.1(b)). The
input pixel gray level is utilized to specify the address of the look-up table element
whose content provides the gray level of the output pixel in the memory register
(Figure 7.1(a)). The square look-up table map presents an alternative method of
calculating output pixel values based on those of the input pixel. To use the map, first
determine the input pixel gray-level value, and then extend a vertical line from the
input value to the mapping function. A horizontal line is then drawn from the
intersection of the vertical line and the mapping function to produce the output pixel
gray level on the vertical axis of the map (Figure 7.1(b) and 7.1(c)). In the case of the
thresholding operation (Figure 7.1(c)), all pixels having an input value below 100 are
mapped to black (0), while other input pixel intensities are unaltered (Davidson, 2007).
7.4 – FLAT-FIELD CORRECTION AND BACKGROUND SUBTRACTION
A digital image acquired from a microscope, camera, or other optical device is
often described as a raw image prior to processing and adjustment of critical pixel
values (see Figure 7.2). In many cases, the raw image is suitable for use in target
applications (printing, web display, reports, etc.), but such an image usually exhibits a
significant level of noise and other artifacts arising from the optical and capture
system, such as distortions from lens aberrations, detector irregularities (pixel non-
uniformity and fixed-pattern noise), dust, scratches, and uneven illumination. In
addition, improper bias signal adjustment can increase pixel values beyond their true
photometric values, a condition that leads to significant errors in measuring the
amplitudes of specific image features. Errors in the raw image are manifested as dark
shadows, excessively bright highlights, specks, mottles, and intensity gradients that
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alter the true pixel values. In general, these errors are particularly evident in digital
images having bright, uniform backgrounds, which are produced by a variety of
common microscope illumination modes, including brightfield, oblique, phase
contrast, and differential interference contrast (DIC). Fluorescence images having
medium gray or bright backgrounds, though relatively rare, may suffer from similar
errors (Davidson, 2007).
Figure 7.2 – Flat-field correction of a digital image (from Davidson, 2007).
Applying flat-field correction techniques to raw digital images can often ensure
photometric accuracy and remove common image defects to restore the fidelity of
features and achieve a visual balance. These correction steps should be undertaken
before measuring light amplitudes or obtaining other quantitative information from
pixel intensity values, although the corrections are not necessary in order to display or
print an image. Flat-field and background subtraction techniques usually require
collection of additional image frames under conditions similar to those employed to
capture the primary raw specimen image (Davidson, 2007).
Most of the flat-field correction schemes utilize two supplemental image
frames, in addition to the raw image, to calculate final image parameters (Figure 7.2).
A flat-field reference frame can be obtained by removing the specimen and capturing
the featureless view field at the same focus level as the raw image frame. Flat-field
reference frames should display the same brightness level as the raw image and take
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advantage of the full dynamic range of the camera system to minimize noise in the
corrected image. If both the raw image and flat-field reference frame have low signal
amplitudes and contain a significant amount of noise, the corrected image will also be
dark and noisy. In order to compensate for noise and low intensity, flat-field reference
frames can be exposed for longer periods than those used for capturing raw images.
Several averaged frames (3-20) can be added together to create a master flat-field
reference frame with a very low noise level (Davidson, 2007).
In addition to a flat-field reference frame, a dark reference frame is collected,
which effectively records the output level of each pixel when the image sensor is
exposed to a dark scene, absent microscope illumination. The dark frame contains the
pixel bias offset level and noise acquired from electronic and thermal sources that
contaminate the raw image. Offset pixel values derive from the positive voltage
applied to the image sensor in order to digitize analog intensity information from each
photodiode. Electronic noise originates from camera readout and related sources, and
thermal noise is generated by kinetic vibration of silicon atoms in the collection wells
and substrate of semiconductor-based sensors. Collectively, these noise sources are
referred to as dark noise, and are a common artifact in digital image sensors, which
can contribute up to 20 percent of apparent pixel amplitudes. In order to ensure
photometric accuracy, these sources must be subtracted from the flat-field reference
frame and raw image. Dark frames are generated by integrating the image sensor
output for the same period as the raw image, but without opening the camera shutter.
Master dark frames can be prepared by averaging several individual dark frames
together to increase signal intensity (Davidson, 2007).
Once the necessary frames have been collected, flat-field correction is a
relatively simple operation that involves several sequential functions. First, the master
dark frame is subtracted from both the raw image and flat-field reference frames,
followed by the division of the resulting values (Figure 3). In effect, the raw frame is
divided by the flat-field frame after the dark frame has been subtracted from each
frame and the quotient is multiplied by the mean pixel value in order to maintain
consistency between the raw and corrected image intensities. Individual pixels in the
corrected image are constrained to have a gray level value between 0 and 255, as a
precaution against sign inversion in cases where the dark reference frame pixel value
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exceeds that of the raw image. The flat-field correction illustrated in Figure 3 shows a
plot of intensity profile across a selected region of the image versus pixel number for
the raw, flat-field, and dark frames, as well as that for the corrected image (Davidson,
2007).
Background subtraction is a technique that results in localized alterations of
each pixel value in the raw image, depending upon the intensity of a corresponding
pixel at the same coordinate location in the background image. As a result, non
uniformities in detector sensitivity or illumination (including mottle, dirt, scratches,
and intensity gradients) can be compensated by storing a background image of an
empty microscope field as a reference image. Video-enhanced contrast (VEC)
microscopy is critically dependent on background subtraction for removal of both stray
light and artifacts from highly magnified images of specimens having poor contrast. In
this case, the background image is obtained by defocusing or displacing the specimen
from the field of view. The resulting background image is stored and continuously
subtracted from the raw image, producing a dramatic improvement in contrast. This
technique is also useful for temporal comparisons to display changes or motion
between view fields (Davidson, 2007).
Figure 7.3 – Surface function background subtraction technique (from Davidson, 2007).
When it is not feasible to capture a background image in the microscope, a
surrogate image can be created artificially by fitting a surface function to the
background of the captured specimen image (see Figure 7.3). This artificial background
image can then be subtracted from the specimen image. By selecting a number of
points in the image that are located in the background, a list of brightness values at
(a) (b)
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various positions is obtained. The resulting information can then be utilized to obtain a
least squares fit of a surface function that approximates the background. In Figure 7.3,
eight adjustable control points are used to obtain a least squares fit of the background
image with a surface function B(x, y) of the form:
where c(0) ... c(5) are the least squares solutions, and (x, y) represents the coordinates
of a pixel in the fitted background image. The specimen presented in Figure 7.3 is a
young starfish captured digitally with an optical microscope configured to operate in
oblique illumination. The control points should be chosen so that they are evenly
distributed across the image, and the brightness level at each control point should be
representative of the background intensity. Placing many points within a small region
of the image while very few or none are distributed into surrounding regions will result
in a poorly constructed background image. In general, background subtraction is
utilized as an initial step in improving image quality, although (in practice) additional
image enhancement techniques must often be applied to the subtraction image in
order to obtain a useful result (Davidson, 2007).
Images modified by flat-field correction appear similar to those obtained with
background subtraction, but performing the operation by division (flat-field correction)
is preferred because the technique yields images that are photometrically more
accurate. The primary reason for this difference is that images result from light
amplitude values derived by a multiplicative process that combines the luminous flux
and exposure time. After application of flat-field correction techniques (but not
necessarily background subtraction algorithms), the relative amplitudes of specimen
features will be photometrically accurate. As an added benefit, flat-field correction
removes a majority of the optical defects that are present in the raw image (Davidson,
2007).
7.5 – IMAGE INTEGRATION
Because a digital image is composed of a matrix of integers, operations such as
the summation or integration of images can readily be conducted at high speed. If the
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original images were digitized with 8-bit resolution, the storage region, or digital frame
memory, which holds the accumulated images, must have sufficient capacity to
accommodate a sum that exceeds 8 bits. If it is assumed that a few pixels in an 8-bit
digital image have the maximum gray-level value of 255, then summation of 30 frames
would result in a local pixel gray-level value of 7650 and require a storage register with
13-bit capacity. To sum 256 frames, the storage capacity must equal 65,536 gray levels,
or 16 bits, to accommodate the brightest pixels (Davidson, 2007).
Although modern computer monitors are capable of displaying images having
more than 256 gray levels, the limited response of the human eye (35-50 gray levels)
suggests that 16-bit digital images should be scaled to match the limitations of the
display and human visual ability. When the useful information of the image resides
only in a subregion of the 16-bit stored image, only this portion should be displayed.
This is a beneficial approach when displaying images captured by a slow-scan CCD
camera of a view field with a large intrascene range of intensities. The process involves
searching through the 16-bit image for the visually meaningful portion (Davidson,
2007).
When images obtained with a video-rate analog or CCD camera are summed
into a 16-bit frame memory, display of a meaningful 8-bit image is usually
accomplished by dividing the stored sum by a constant. For example, a 96-frame
summation of a view field can be divided by 96, 64, 32, or 24. Division by 32 is
equivalent to a threefold increase in gain and results in utilization of the full 255 gray-
level range. However, division by 24 is equivalent to a fourfold gain increase and
results in image saturation and loss of information (Davidson, 2007).
Image integration using digital image processing techniques often enables
visualization of a faint object that is barely detectable above the camera noise.
Integration may be of particular value in low-light-level imaging when the brightness of
the image cannot be increased by additional image intensification. However, it is
important to realize that, from signal-to-noise considerations, integration directly on
the sensor is always preferable to integration in the processing software. Each image
integration step in the software introduces analog-to-digital noise as well as camera
readout noise (Davidson, 2007).
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7.6 – DIGITAL IMAGE HISTOGRAM ADJUSTMENT
A majority of the digital images captured in an optical device, such as a camera
or microscope, require adjustments to either the look-up table or the image histogram
to optimize brightness, contrast, and general image visibility. Histograms of digital
images provide a graphical representation of image contrast and brightness
characteristics, and are useful in evaluating contrast deficiencies such as low or high
contrast, and inadequate dynamic range. An image histogram is a graphical plot
displaying input pixel values on the x-axis (referred to as a bin) versus the number (or
relative number) of pixels for any given bin value on the y axis. Each bin in a grayscale
histogram depicts a subgroup of pixels in the image, sorted by gray level. The numeric
range of input values, or bins, on the x-axis usually corresponds to the bit depth of the
captured image (0-255 for 8-bit images, 0-1023 for 10-bit images, and 0-4095 for 12-bit
images). Mathematical operations may be performed on the histogram itself to alter
the relative distribution of bins at any gray level. Manipulation of the histogram can
correct poor contrast and brightness to dramatically improve the quality of digital
images (Davidson, 2007).
Histogram stretching involves modifying the brightness (intensity) values of
pixels in the image according to a mapping function that specifies an output pixel
brightness value for each input pixel brightness value (see Figure 7.4). For a grayscale
digital image, this process is straightforward. For an RGB color space digital image,
histogram stretching can be accomplished by converting the image to a hue,
saturation, intensity (HSI) color space representation of the image and applying the
brightness mapping operation to the intensity information alone. The following
mapping function is often utilized to compute pixel brightness values:
In the above equation, the intensity range is assumed to lie between 0.0 and
1.0, with 0.0 representing black and 1.0 representing white. The variable B represents
the intensity value corresponding to the black level, while the intensity value
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corresponding to the white level is represented by the variable W. In some instances, it
is desirable to apply a nonlinear mapping function to a digital image in order to
selectively modify portions of the image (Davidson, 2007).
Histogram equalization (also referred to as histogram leveling) is a related
technique, which results in the reassignment of pixel gray-level values so that the
entire range of gray levels is utilized and the number of counts per bin remains
constant. The process yields a flat image histogram with a horizontal profile that is
devoid of peaks. Pixel values are reassigned to ensure that each gray level contains an
equal number of pixels while retaining the rank order of pixel values in the original
image. Equalization is often utilized to enhance contrast in images with extremely low
contrast where a majority of the pixels have nearly the same value, and which do not
respond well to conventional histogram stretching algorithms. The technique is
effective in treating featureless dark, and flat-field frames, and to rescue images with
low-amplitude gradients. In contrast, histogram stretching spaces gray-level values to
cover the entire range evenly. The auto-enhance or automatic levels (contrast)
features of many image processing software packages utilize one of these histogram-
based transformations of the image (Davidson, 2007).
Figure 7.4 – Contrast enhancement by histogram stretching (from Davidson, 2007).
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Digital image histograms can be displayed in several motifs that differ from the
conventional linear x and y plots of pixel number versus gray level value. Logarithmic
histograms chart the input pixel value on the x-axis versus the number of pixels having
that value on the y-axis, using a log scale. These histograms are useful to examine pixel
values that comprise a minority of the image, but exhibit a strong response to
histogram stretching. Another commonly employed variation, the integrated or
cumulative histogram, plots input pixel values on the x-axis and the cumulative
number of all pixels having a value of x, and lower, on the y-axis. Cumulative
histograms are often utilized to adjust contrast and brightness for images gathered in
phase contrast, DIC, and bright field illumination modes, which tend to have light
backgrounds (Davidson, 2007).
In some cases, images have regions of very high intensity, manifested by large
peaks near the histogram 255 gray level, where the video signal is saturated and all
pixels have been rendered at the maximum gray value. This situation is termed gray-
level clipping and usually indicates that a certain degree of detail has been lost in the
digital image because some regions of the original image that might have different
intensities have each been assigned to the same gray value. Clipping of the histogram
may be acceptable in some circumstances if detail is lost only from unimportant parts
of the image. Such a situation might occur, for example, if the system has been
adjusted to maximize the contrast of stained histological slides under brightfield
illumination, with the clipping occurring only in bright background regions where there
is no cellular structure (Davidson, 2007).
7.7 – SPATIAL CONVOLUTION KERNELS (OR MASKS)
Some of the most powerful image processing tools utilize multipixel operations,
in which the integer value of each output pixel is altered by contributions from a
number of adjoining input pixel values. These operations are classically referred to as
spatial convolutions and involve multiplication of a selected set of pixels from the
original image with a corresponding array of pixels in the form of a convolution kernel
or convolution mask. Convolutions are mathematical transformations of pixels, carried
out in a manner that differs from simple addition, multiplication, or division, as
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illustrated in Figure 7.5 for a simple sharpening convolution kernel mask (Davidson,
2007).
In the simplest form, a two-dimensional convolution operation on a digital
image utilizes a box convolution kernel. Convolution kernels typically feature an odd
number of rows and columns in the form of a square, with a 3 x 3 pixel mask
(convolution kernel) being the most common form, but 5 x 5 and 7 x 7 kernels are also
frequently employed. The convolution operation is performed individually on each
pixel of the original input image, and involves three sequential operations, which are
presented in Figure 7.5. The operation begins when the convolution kernel is overlaid
on the original image in such a manner that the center pixel of the mask is matched
with the single pixel location to be convolved from the input image. This pixel is
referred to as the target pixel (Davidson, 2007).
Figure 7.5 – The convolution operation sequence (from Davidson, 2007).
Next, each pixel integer value in the original (often termed the source) image is
multiplied by the corresponding value in the overlying mask (Figure 7.5). These
products are summed and the grayscale value of the target pixel in the destination
image is replaced by the sum of all the products, ending the operation. The
convolution kernel is then translocated to the next pixel in the source image, which
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becomes the target pixel in the destination image, until every pixel in the original
image has been targeted by the kernel (Davidson, 2007).
Convolution kernels may contain all positive, or positive and negative values,
and thus can result in negative totals, or results that exceed the maximum 255 limit
that a pixel can hold. Appropriate divisor and offset values are needed to correct this.
The smoothing convolution kernel illustrated in Figure 7.6(a) has a value of unity for
each cell in the matrix, with a divisor value of 9 and an offset of zero. Kernel matrices
for 8-bit grayscale images are often constrained with divisors and offsets that are
chosen so that all processed values following the convolution fall between 0 and 255.
Many of the popular software packages have user-specified convolution kernels
designed to fine-tune the type of information that is extracted for a particular
application (Davidson, 2007).
Convolution kernels are useful for a wide variety of digital image processing
operations, including smoothing of noisy images (spatial averaging) and sharpening
images by edge enhancement utilizing Laplacian, sharpening, or gradient filters (in the
form of a convolution kernel). In addition to convolution operations, local contrast can
be adjusted through the application of maximum, minimum, or median filters that rank
the pixels within each local neighborhood. Furthermore, the use of a Fourier transform
to convert images from the spatial to the frequency domain makes possible another
class of filtering operations. The total number of algorithms developed for image
processing is enormous, but several operations enjoy widespread application among
many of the popular image processing software packages (Davidson, 2007).
7.8 – SMOOTHING CONVOLUTION FILTERS (SPATIAL AVERAGING)
Specialized convolution kernels, often termed smoothing filters, are often used
for reducing random noise in digital images. A typical smoothing convolution filter is
illustrated in Figure 7.6(a), and is essentially a matrix having an integer value of 1 for
each row and column. When an image is convolved with this type of kernel, the gray
value of each pixel is replaced by the average intensity of its eight nearest neighbors
and itself. Random noise in digital images is manifested by spurious pixels having
unusually high or low intensity values. If the gray value of any pixel overlaid by the
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convolution kernel is dramatically different than that of its neighbors, the averaging
effect of the filter will tend to reduce the effect of the noise by distributing it among all
of the neighboring pixels (Davidson, 2007).
Figure 7.6 – Smoothing and sharpening convolution kernels (from Davidson, 2007).
The nine integers in each smoothing kernel illustrated in Figure 7.6 add to a
value of 1 when summed and divided by the number of values in the matrix. These
kernels are designed so that the convolution operation will produce an output image
having an average brightness that is equal to that of the input images (however, in
some cases, this may be only approximate). In general, the sum of terms in most
convolution kernels will add to a value between zero and one in order to avoid
creating an output image having gray values that exceed the dynamic range of the
digital-to-analog converter utilized to display the image (Davidson, 2007).
Smoothing convolution kernels act as low-pass filters to suppress the
contribution of high spatial frequencies in the image. The term spatial frequency is
analogous to the concept of frequency with respect to time (temporal frequency), and
describes how rapidly a signal changes with respect to position in the image. A low
spatial frequency might exhibit only a few cycles across the width of an image, while a
high spatial frequency often displays numerous cycles in the same linear dimensions.
An excellent example is the minute orderly arrays of miniature pores and striate
exhibited by diatom frustules, which alternate between very high and low intensities
over very short distances. A low spatial frequency might exhibit only a few cycles
across the width of an image (manifested as widely spaced stripes, for example),
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whereas a high spatial frequency undergoes numerous cycles across the lateral
dimensions of an image. The highest spatial frequency that can be displayed in a digital
image has a period equal to the width of two pixels (Davidson, 2007).
The type of random noise typically observed in digital images has a high spatial
frequency that can be effectively removed by applying a smoothing convolution kernel
to the image, pixel by pixel. However, other "real" image features that are desirable,
such as object boundaries and fine structural details, may also have high spatial
frequencies that can unfortunately be suppressed by the smoothing filter.
Consequently, application of a smoothing convolution kernel will often have the
undesirable effect of blurring an input image. Furthermore, the larger the kernel (5 x 5,
7 x 7, and 9 x 9), the more severe this blurring effect will be (Figure 8). For most
applications, the size and form of the smoothing kernel must be carefully chosen to
optimize the tradeoff between noise reduction and image degradation. A Gaussian
filter is a smoothing filter based on a convolution kernel that is a Gaussian function,
and provides the least amount of spatial blurring for any desired amount of random
noise reduction. Smoothing filters are good tools for making simple cosmetic
improvements to grainy images that have a low signal-to-noise ratio, but these filters
can also undesirably reduce the image resolution as a consequence (Davidson, 2007).
7.9 – SHARPENING CONVOLUTION FILTERS
In direct contrast to the action of smoothing convolution filters, sharpening
filters are designed to enhance the higher spatial frequencies in a digital image, while
simultaneously suppressing lower frequencies. A typical 3 x 3 convolution mask and its
effect on a digital image captured with an optical microscope is illustrated in Figure
7(c). In addition to enhancing specimen boundaries and fine details, sharpening filters
also have the effect of removing slowly varying background shading. Thus, these filters
can sometimes be utilized to correct for shading distortion in an image without having
to resort to background subtraction algorithms. Unfortunately, sharpening convolution
filters have the undesirable effect of enhancing random noise in digital images
(Davidson, 2007).
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 190
Figure 7.7 – Kernel size effects on smoothing convolution operations (from Davidson, 2007).
The kernel size can be adjusted to optimize the effects of sharpening filters and
to fine-tune the masks to operate on a specific range of spatial frequencies. A typical 3
x 3 mask (see Figures 7.5 and 7.6) has the greatest effect on image features that vary
over the spacing interval of a single pixel. Doubling or tripling the size of the kernel will
target lower spatial frequencies that extend over two or more pixels (Davidson, 2007).
7.10 – MEDIAN FILTERS
Median filters are primarily designed to remove image noise, but are also very
effective at eliminating faulty pixels (having unusually high or low brightness values)
and reducing the deterioration caused by fine scratches. These filters are often more
effective at removing noise than smoothing (low pass) convolution kernels. Median
kernels are applied in a manner that is different from standard smoothing or
sharpening kernels. Although the median filter operates in a local neighborhood that is
translated from pixel to pixel, there is no convolution matrix applied. At each
successive pixel location, the pixels under scrutiny are ordered in rank according to
their intensity magnitude. A median value is then determined for all of the pixels
covered by the neighborhood, and that value is assigned to the central pixel location in
the output image (Davidson, 2007).
Median filters are useful for removing random intensity spikes that often occur
in digital images captured in the microscope. Pixels contributing to the spike are
replaced with the median value of the local neighborhood pixels, which produces a
more uniform appearance in the processed image. Background regions that contain
infrequent intensity spikes are rendered in a uniform manner by the median filter. In
CHAPTER VII – BASIC CONCEPTS OF DIGITAL IMAGE PROCESSING
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 191
addition, because the median filter preserves edges, fine specimen detail, and
boundaries, it is often employed for processing images having high contrast (Davidson,
2007).
7.11 – SPECIALIZED CONVOLUTION FILTERS
Derivative filters provide a quantitative measurement for the rate of change in
pixel brightness information present in a digital image. When a derivative filter is
applied to a digital image, the resulting data concerning brightness fluctuation rates
can be used to enhance contrast, detect edges and boundaries, and to measure
feature orientation. One of the most important derivative filters is the Sobel filter,
which combines two orthogonal derivatives (produced by 3 x 3 kernel convolutions) to
calculate the vector gradient of brightness. These convolutions are very useful for edge
enhancement of digital images captured in the microscope. Edges are usually one of
the most important features in a microscopic structure, and can often be utilized for
measurements after appropriate enhancement algorithms have been applied
(Davidson, 2007).
Laplacian filters (often termed operators) are employed to calculate the second
derivative of intensity with respect to position and are useful for determining whether
a pixel resides on the dark or light side of an edge. The Laplacian enhancement
operation generates sharp peaks at the edges, and any brightness slope, regardless of
whether it is positive or negative, is accentuated, bestowing an omnidirectional quality
to this filter. It is interesting to note that in the human visual system, the eye-brain
network applies a Laplacian-style enhancement to every object in the viewfield.
Human vision can be simulated by applying a Laplacian-enhanced image to the original
image, using a dual-image point process, to produce a modified image that appears
much sharper and more pleasing (Davidson, 2007).
An important issue that arises within the convolution process methodology
centers on the fact that the convolution kernel will extend beyond the borders of the
image when it is applied to border pixels. One technique commonly utilized to remedy
this problem, referred to as centered, zero boundary superposition, is simply to ignore
the problematic pixels and to perform the convolution operation only on those pixels
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 192
that are located at a sufficient distance from the borders. This method has the
disadvantage of producing an output image that is smaller than the input image. A
second technique, called centered, zero padded superposition, involves padding the
missing pixels with zeroes. Yet a third technique regards the image as a single element
in a tiled array of identical images, so that the missing pixels are taken from the
opposite side of the image. This method is called centered, reflected boundary
superposition and has the advantage of allowing for the use of modulo arithmetic in
the calculation of pixel addresses to eliminate the need for considering border pixels as
a special case. Each of these techniques is useful for specific image-processing
applications. The zero padded and reflected boundary methods are commonly applied
to image enhancement filtering techniques, while the zero boundary method is often
utilized in edge detection and in the computation of spatial derivatives (Davidson,
2007).
7.12 – UNSHARP MASK FILTERING
Unsharp mask algorithms operate by subtraction of a blurred image from the
original image, followed by adjustment of gray level values in the difference image.
This operation enables preservation of high-frequency detail while allowing shading
correction and background suppression. The popular technique is an excellent vehicle
to enhance fine specimen detail and sharpen edges that are not clearly defined in the
original image. The first step in an unsharp mask process is to produce a slight blur (by
passage through a Gaussian low-pass filter) and a reduction in amplitude of the
original image, which is then subtracted from the unmodified original to produce a
sharpened image. Regions in the image that have uniform amplitude are rendered in a
medium gray brightness level, whereas regions with larger slopes (edges and
boundaries) appear as lighter or darker gradients (Davidson, 2007).
In general, unsharp mask filters operate by subtracting appropriately weighted
segments of the unsharp mask (the blurred original) from the original image. Such a
subtraction operation enhances high-frequency spatial detail at the expense
(attenuation) of low-frequency spatial information in the image. This effect occurs
because high-frequency spatial detail removed from the unsharp mask by the Gaussian
CHAPTER VII – BASIC CONCEPTS OF DIGITAL IMAGE PROCESSING
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 193
filter is not subtracted from the original image. In addition, low-frequency spatial detail
that is passed by the Gaussian filter (to the unsharp mask) is almost entirely subtracted
from the original image. Increasing the size of the Gaussian filter allows the smoothing
operation to remove larger size detail, so that those details are retained in the
difference image (Davidson, 2007).
One of the primary advantages of the unsharp mask filter over other
sharpening filters is the flexibility of control, because a majority of the other filters do
not provide any user-adjustable parameters. Like other sharpening filters, the unsharp
mask filter enhances edges and fine detail in a digital image. Because sharpening filters
also suppress low frequency detail, these filters can be used to correct shading
distortion throughout an image that is commonly manifested in the form of slowly
varying background intensities. Unfortunately, sharpening filters also have the
undesirable side effect of increasing noise in the filtered image. For this reason, the
unsharp mask filter should be used conservatively, and a reasonable balance should
always be sought between the enhancement of detail and the propagation of noise
(Davidson, 2007).
7.13 – FOURIER TRANSFORMS
The Fourier transform is based on the theorem that any harmonic function can
be represented by a series of sine and cosine functions, differing only in frequency,
amplitude, and phase. These transforms display the frequency and amplitude
relationship between the harmonic components of the original functions from which
they were derived. The Fourier transform converts a function that varies in space to
another function that varies with frequency. It should also be noted that the highest
spatial frequencies of the original function are found the farthest away from the origin
in the Fourier transform (Davidson, 2007).
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ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 194
Figure 7.8 – Fourier transform filtering (from Davidson, 2007).
Spatial filtering involving Fourier techniques can be utilized to manipulate
images through deletion of high or low spatial-frequency information from an image
by designing a Fourier filter that is nontransmitting at the appropriate frequency. This
technique is especially useful for removing harmonic noise from an image such as the
herringbone or sawtooth patterns often apparent in video images (see Figure 7.8).
Because the added noise is harmonic, it will be found in localized discrete regions of
the Fourier transform. When these local peaks are removed from the transform with
the appropriate filter, the re-formed image is essentially unaltered except that the
offending pattern is absent. Similar filtering techniques can also be applied to remove
sine wave, moiré, halftone, and interference patterns, as well as noise from video
signals, CCDs, power supplies, and electromagnetic induction (Davidson, 2007).
Illustrated in Figure 7.8(a) is a video image of a diatom frustule imaged in
darkfield illumination with a superimposed sawtooth interference pattern. Adjacent to
the diatom image (Figure 7.8(b)) is the Fourier transform power spectrum for the
image, which contains the spatial frequency information. After applying several filters
(Figure 7.8(d)) and re-forming the image, the sawtooth pattern has been effectively
eliminated (Figure 7.8(c)), leaving only the image of the frustules (Davidson, 2007).
The decision as to whether to utilize Fourier filtering or convolution kernel
masks depends on the application being considered. The Fourier transform is an
CHAPTER VII – BASIC CONCEPTS OF DIGITAL IMAGE PROCESSING
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 195
involved operation that takes more computer horsepower and memory than a
convolution operation using a small mask. However, the Fourier filtering technique is
generally faster than the equivalent convolution operation, especially when the
convolution mask is large and approaches the size of the original image. Appropriate
choice of equivalent Fourier and convolution operations may reduce the complexity of
their respective masks. For example, a simple Fourier filter, such as one designed to
remove harmonic noise, would produce a large and complex convolution mask that
would be difficult to use (Davidson, 2007).
Another useful feature of the Fourier transform stems from its relationship to
the convolution operation, which involves several multiplication and addition
operations, according to the contents of the convolution mask, to determine the
intensity of each target pixel. This operation can be compared to Fourier filtering,
where each value in the Fourier filter is simply multiplied by its corresponding pixel in
the Fourier transform of an image. The two operations are related because the
convolution operation is identical to the Fourier filtering operation when the Fourier
filter is the Fourier transform of the convolution mask. This equivalence indicates that
either of these two techniques can be employed to obtain identical results from an
image, depending only on whether the operator decides to work in image space or
Fourier space (Davidson, 2007).
7.14 – SUMMARY
The extent of the increased processing power of the digital approach may not
be appreciated at first glance, particularly in comparison to the older and apparently
simpler analog methods, such as traditional photomicrography on film. In fact, digital
image processing enables reversible, virtually noise-free modification of an image as a
matrix of integers instead of as a series of time-dependent voltages or, even more
primitively, using a photographic enlarger in the darkroom (Davidson, 2007).
Much of the recent progress in high-resolution transmitted optical microscopy
and low-light-level reflected fluorescence microscopy of living cells has relied heavily
on digital image processing. In addition, most confocal and multiphoton microscopes
depend strictly on high-speed, high fidelity digitization of the scanned image, and on
CHAPTER VII – BASIC CONCEPTS OF DIGITAL IMAGE PROCESSING
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 196
the subsequent digital manipulation of the view field to be displayed. Newer
microscope designs lacking eyepieces (oculars) and coupled directly to image capture
software also depend on image processing technology to produce high-quality digital
images from the microscope (Davidson, 2007).
The power of digital image processing to extract information from noisy or low-
contrast images and to enhance the appearance of these images has led some
investigators to rely on the technology instead of optimally adjusting and using the
microscope or image sensor. Invariably, beginning with a higher-quality optical image,
free of dirt, debris, noise, aberration, glare, scratches, and artifacts, yields a superior
electronic image. Careful adjustment and proper calibration of the image sensor will
lead to a higher-quality digital image that fully utilizes the dynamic range of both the
sensor and the digital image processing system (Davidson, 2007).
In the study that I will perform in the next year, in my dissertation thesis, the
digital image processing with MATLAB will be used as a work tool to enhance the
details in the cancer cell images of prostate and breast carcinomas. My goal is to
extract information from the referred images, obtaining data that is not possible to get
with biochemical methods of study.
CHAPTER VIII
CONCLUSIONS AND FUTURE WORKS
CHAPTER VII – CONCLUSIONS AND FUTURE WORKS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 199
8.1 – FINAL CONCLUSIONS
The main clinical advantages of brachytherapy are consequently based on the
sharp reduction of dose with distance; showing a reduction of both dose and dose rate
with distance. Therefore, a fall of dose and dose rate causes a larger reduction in cell
kill than a reduced dose or dose rate used in isolation.
Repair of sub-lethally damaged DNA can occur if the cell contains the full
complement of DNA damage detection proteins and repair enzyme systems, but there
must also be sufficient time for these mechanisms to operate. If successful sub-lethal
damage repair has not occurred at a particular site before further sub-lethal damage is
deposited in an appropriately near site, then sub-letal/unrepairable damage will form.
The lower the dose rate of radiation that a cell is exposed to, more likely it is
that repair will occur, because there will be more time for sub-lethal damage repair
before a second “hit” confers the unrepairable damage. Late reacting normal tissues
have a higher capacity for repair than do some tumor cells, probably because the latter
posses mutations that affect repair fidelity and cell cycle checkpoint control, so that
tumor is preferentially killed when compared with normal tissues.
The dividing cell is significantly more sensitive to damage and death from
ionizing radiation because of the need to replicate DNA during cell division. The
decision of G1-phase cells to proceed to S-phase is a critical regulatory step (designated
Start or the restriction point in late G1 cells) in both normal and neoplastic cell growth.
Once a cell reaches S-phase, progression to G2 becomes independent of extracellular
influences, that is, the cell becomes committed to completing DNA synthesis (S-G2
traverse).
One particularly important function of p53 is DNA damage signaling. Here, to
suppress tumorigenesis, p53 halts the cell cycle and induces apoptosis in primary cells
and in tumor cell lines. Since stem cells provide the pool of proliferative
pluri/toti/omni-potent cells within organisms, they are more likely to propagate DNA
lesions and mutations to daughter cells compared to differentiated cells.
From this research work, I expect to find morphological alterations in cancer
cells in comparison with normal cells and after the irradiation of the cancer cells I
CHAPTER VII – CONCLUSIONS AND FUTURE WORKS
ANALYSIS OF STRUCTURES IN BIOMEDICAL IMAGES 200
expect to find accumulation of p53 in the nucleus of irradiated cells to repair the sub-
lethal damage caused by radiation.
Once again, to highlight these results, the light microscopy photos obtained
with this study will be processed using MATLAB.
8.2 – FUTURE WORKS
The future prospect of this thesis is to continue the study with cells, performing
the analysis and image processing of breast and prostate cancer cells submitted to
brachytherapy. Hence, the study of morphological changes that occur in the irradiated
cells, as well as the modifications in the cellular environment to obtain the maximum
information of the electron microscopy images of these cells, will be done.
Additionally, computational algorithms will be developed to help that study in an
automate and robust manner.
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