Abdulhamid ChaikhPhD, Jacques BalossoMD,PhD

Grenoble University Hospital, Department of Radiation OncologyUniversity Grenoble-Alpes, Grenoble, France

Micaela CunhaPhD, Etienne TestaPhD, Michaël BeuvePhD

Université de Lyon, Université Lyon 1, CNRS, FranceIN2P3, UMR 5822, IPNL, F-69622 Villeurbanne, France

Analysis by Monte-Carlo simulations of the characteristics of nano and micro dosimeters for

real time measurements in radiotherapy and medical physics

A.Chaikh et al®, August 11-13-2015 Frankfurt

E-mail: abdulhamedc@yahoo.com

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Context

Introduction and purpose

Conclusion and perspectives

Materials and methods

Results and discussion

• The goal of radiotherapy is to deliver a radiation dose to treat the cancer using X-

Ray generators :

Maximizing the Tumor Control Probability

Minimizing Probabilities of Normal Tissue Complications (organs at risk)

By using multiple “cross fired” beams varying from a technique to another

• A treatment plan must be calculated and validated, two methods are available:

Physical model: Using physical quantities and statistics (DVH)

Measurements : “In vivo dosimetry” in real time using a dosimeter

o Currently : at beam entrance using a macro semiconductor placed on the patient skin

o More recently : an implantable micro dosimeter placed in the target volumes

• Tolerance constrain between planned dose and measured dose: ± 5%

Radiotherapy & medical physics

3

Introduction

RL signal

Linked Optical fiber

Bi-channel Photo detection

Optical fiber

Fiber connector

Gallium Nitride

4

Dose (Gy)

Patient

Irradiation OffIrradiation ON

µ -dosimeter (900 µm)

In-vivo dosimetry with implanted micro dosimeter

• Example of dose measurement using a µ-dosimeter : DorGaN project -France

Introduction

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Available mico/macro dosimeters for radiotherapy

Purpose

• In practice radiotherapy: 93% of “In-vivo dosimetry” is based on diodes in France (ASN, 2013) Entrance dose

• The available dosimeters are imperfect and need a correction factors• Ideal in-vivo dosimeter desired

Implanted micro / nano dosimeter High accuracy and high precision < 5% Reproducibility < 2% No correction factors

• Intended clinical use: Real-time absolute dose monitoring at target volume in the patient Toward in-situ dosimetry and dose guided radiotherapy

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Why do we need an implantable µ/nano dosimeter?

Purpose

• Monte-Carlo simulation method, widely used for radiotherapy:

Modeling linear accelerator in medical physics

Tracks individual particle histories (photon /electrons)

Dose calculation

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Monte-Carlo simulations Materials & methods

• Monte-Carlo simulations were carried out to:

Evaluate the influence of the dosimeter size on the

measured dose

Characterize the size of micro / nano dosimeter for

radiotherapy

o As small as possible

o With high accuracy ( < 5%) and high

reproducibility

• Principle : Estimate the level of dose fluctuations Determine the probability p (%) of error in dose

measurements

8http://www.wienkav.at/kav/kfj/91033454/physik/emc/emc.htm

Monte-Carlo simulations Materials & methods

• Simulation of the irradiation of a water volume with photons

X = Y = Z: 50 to 200 µm

• Cylindrical targets simulate the dosimeters :

Placed in the irradiated water volume (“water space”)

Density equivalent to water

The target length was set as equal to the diameter :

Smallest radius (nm): < 1 µm

Intermediate radius (µm) : 1 µm to 9 µm

Largest radius (µm): ≥ 10 µm

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Simulations of micro/nano dosimeter Materials & methods

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Source modelling

X (µm)

Y (µm)

Z (µm)

60Cobalt

Beam

Water volume

• Scheme of the transversal view of the irradiated water phantom

• The nano dosimeter (circle) is placed• The dots represent the energy transfer points after the

interaction of the electrons with the medium

dosimeter

Dosimeter

Simulations of micro/nano dosimeter Materials & methods

• 60Cobalt source was simulated to generate the photon beam:

Irradiate the water phantom with 1.3 MeV photons

Doses simulated using only electrons generated by Compton effect

• The simulated doses were :

Lower dose : 0.1Gy – 1Gy: delivered dose by one beam

Intermediate dose : 1Gy – 2Gy: daily fraction on clinical routine

Higher dose : > 2 Gy : hypofractionated treatment plans

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electron

Scatteringphoton

Deposited dose

60Cobalt

Modelization of doses in the targetsMaterials & methods

• Using the concept of micro-dosimetry :

• The specific energy “zt” in the target is defined as the cumulated energy transferred by the radiation over the mass “mt” of the target : zt = ε / mt

<zt> is the mean specific energy in the targets over many irradiation configurations with the same dose D

• The probability (p%) that a measurement yields a value outside of confidence intervals :

[<z>- γ *<z> ; <z> + γ *<z>]

γ varied from to 3% to 10%

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Measurements of deposited doses in the targets

Materials & methods

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• Largest radius : 10 µm-dosimeter

• The effect of fluctuations is less significant than in the other cases

• The distributions of specific energy are Gaussian curves

• The zt values at the peak match the average specific energy in the targets

• The relative width of the distributions decreases as the irradiation dose increases

• The increase in the dose resulted in a higher number of energy-transfer points and thus

in a reduction of the relative statistical fluctuations

• Note: <zt > corresponds to 86 - 87% of the irradiation dose since a part of the

energy is converted to heat and is not considered

Results & discussion

Influence of dosimeter size on the measured doses

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• Intermediate radius: 1 µm < r < 10 µm dosimeter

• The dose distribution is no longer symmetrical, showing a tail at higher values of specific energy

• As the irradiation dose increases, the distribution peak shifts to higher values of specific energy, closer to the value of <zt>

• As the dose and radius increase the distribution of energy tends to a Gaussian curve

• Probability distribution of specific energies :

Influence of dosimeter size on the measured doses

1 µm, 1 Gy1 µm, 0.1 Gy

Results & discussion

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• For the smallest radius : r ≤ 0.1 µm nano-dosimeter The effect of fluctuations is very significant: very large range of specific

energies a nano-dosimeter may receive The dosimeter is very likely to receive no energy at all The shape of the distribution is:

o Characterized by one photon interactiono Independent of the irradiation dose

Influence of dosimeter size on the measured doses

Probability distribution of specific energies0.1 µm, 0.1 Gy

Results & discussion

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• Dose effect with a small radius of 0.3 μm

Lower doses ≤ 0.3 Gy :o Structure close to the one of 0.1 μm

dosimeters

Dose values ≥ 1 Gy :o The shape is similar to that of 1 μm

dosimeters

Influence of dosimeter size on the measured doses

• Probability distribution of specific energies

0.3 µm, 0.1 Gy

0.3 µm, 3 Gy

Results & discussion

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• Higher delivered dose using micro dosimeter

• Conditions:

Irradiated dose 10 Gy

Radius : 10 µm

• Gaussian curve

• Measured dose in the target 8.1 Gy

• Error of measurements 20 %

Influence of dosimeter size on the measured doses

10 µm, 10 Gy

Results & discussion

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• Probability p (%) to obtain dose measurements outside the range

[<z> -γ * <z> ; <z> + γ * <z>] with γ varing from 3 to 10%

Probability of dose measurements p (%)

0.1 Gy0.3 Gy1 Gy3 Gy10 Gy

• For the same radius: A smaller dose results in a higher p %,

which in turn decreases for a larger γ

• For the same dose: p % decreases as the radius increases p % is lower for a larger interval

around <z>

• In particular : p % is equal to zero when “r =10 μm”,

“D= 10 Gy” and γ is “5% or 10%” This means that in these cases all the

specific energies are contained in the interval considered.

Results & discussion

• Characterization of the size of an implantable dosimeter at µ and nano scales for

clinical use with radiation oncology

• The specific energy probability distributions is strongly dependent on :

Target size radius

Delivered dose level

A dose value < 0.3 Gy, none of the dosimeter radii would allow for a reproducible

measurement of the irradiation dose

• The best results obtained

With a µ-dosimeter “r = 10 µm”

Distributions of energy is close to Gaussian curve

But still ~ 20 % of the measurements would be outside the interval confidence

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Conclusion & perspectives

Characterization of µ/nano dosimeter

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• The ability of the dosimeter to yield measurements is dependent on Size Deposited dose

• Strong correlation between the accuracy of measured doses and the dosimeter size

• An excessively small radius renders the measurements chaotic and not statistically-

reproducible, even for a dose as high as 10 Gy

• A target radius of 10 μm may allow for a better reproducibility of the

measurements in a wider range of doses

• Recommended radius of dosimeter for radiotherapy “r > 10 µm” to

satisfy the dose tolerance of ± 5%

Characterization of µ/nano dosimeterConclusion & perspectives

• [1] Abdulhamid Chaikh, Michaël BEUVE, Jacques BALOSSO. Nanotechnology in Radiation Oncology.

Int J Cancer Ther Oncol 2015 ; 3(2): 3217; DOI: 10.14319/ijcto.32.17

• [2] Abdulhamid Chaikh, Arnaud GAUDU, Jacques Balosso. Monitoring methods for skin dose in

interventional radiology. Int J Cancer Ther Oncol; 3(1):03011. DOI: 10.14319/ijcto.0301.1.

• [3] Chaikh A, Balosso J, Giraud JY, Wang R, Pittet P, Luc GN. Characterization of GaN dosimetry for

6MV photon beam in clinical conditions. Radiation measurements; 2014: 392-395.

• [4] http://www.wienkav.at/kav/kfj/91033454/physik/emc/emc.htm

• [5] Gervais B, Beuve M, Olivera G H, Galassi M E. Numerical simulation of multiple ionization and high

LET effects in liquid water radiolysis. Radiat. Phys. Chem 2006; 75(4):493-513.

Reference

Acknowledgements

•The authors acknowledge the financial support of the French

National Research Agency (ANR-11-TECS-018)

Remerciements :

•France HADRON

•The PRIMES “LabEx”

•Dr. Patrick Pittet

•Dr. Jean Yves Giraud

A.Chaikh et al®, August 11-13-2015 Frankfurt

Thank you for your attention

abdulhamedc@yahoo.com