j.paul robinson, purdue university ee 520 lecture 2000.ppt page 1 biomedical technologies for blood...
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J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 1
Biomedical technologies for blood cell measurements
Introduction to the terminology, types of measurements, capabilities of flow cytometry, uses & applications
• Comparison between flow cytometry and fluorescence microscopy• Scatter• Fluorescence• Sensitivity, precision of measurements, statistics,
populations•Speed, combinatorial measurements (multiparameter)
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 2
What can Flow Cytometry Do?
• Enumerate particles in suspension• Determine “biologicals” from “non-
biologicals”• Separate “live” from “dead” particles• Evaluate 105 to 5x106 particles/min• Measure particle-scatter as well as innate
fluorescence or 2o fluorescence• Sort single particles for subsequent analysis
Flow Cytometry Publications/year
YEARS
00
300300
600600
900900
12001200
15001500
18001800
21002100
2400
2700
0 13 2879
113223
480
611
811
940
1,078
1,232
1,494
1,855
2,713
2,332
2,445
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1991 19921989 1990
Papers
1993 1994
2899
3345
Data taken from Medline search using the keywords: “flow Cytometry”
1995 1996
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 4
Papanicolaou1941 - originally studies the reproductive system of primates during the estrous cycle and observed changes in cells exfoliated from the female genital tract during the the cycle- mixed a series of stains to identify changes he observed- Developed for using quantitative cytology and morphology for the exfoliative cytologic diagnosis of cervical carcinoma in humans- developed sets of critical stains and interpretations
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 5
Gucker - 1947
• Developed a flow cytometer for detection of bacteria in aerosols
• Published paper in 1947 (work was done during WWII and was classified).
• Goal was rapid identification of airborne bacteria and spores used in biological warfare
• Instrument: Sheath of filtered air flowing through a dark-field flow illuminated chamber. Light source was a Ford headlamp, PMT detector (very early use of PMT)
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 6
P.J. Crossland-TaylorSheath Flow Principle
A Device for Counting Small Particles Suspended in a Fluid through a Tube
P.J. Crosland-TaylorBland-Sutton Institute of Pathology
Middlesex Hospital, London, W.1. June 17, 1952 Nature 171: 37-38, 1953
A Device for Counting Small Particles Suspended in a Fluid through a Tube
P.J. Crosland-TaylorBland-Sutton Institute of Pathology
Middlesex Hospital, London, W.1. June 17, 1952 Nature 171: 37-38, 1953
“Provided there is no turbulence, the wide column of particles will then be accelerated to form a narrow column surrounded by fluid of the same refractive index which in turn is enclosed in a tube which will not interfere with observation of its axial content.”
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 7
Wallace Coulter
Wallace Coulter - Coulter orifice - 1956 - (as early as 1948) - measured changes in electrical conductance as cells suspended in saline passed through
a small orifice
• Cells are relatively poor conductors• Blood is a suspension of cells in plasma which is a relatively
good conductor• Previously it was known that the cellular fraction of blood
could be estimated from the conductance of blood• As the ratio of cells to plasma increases the conductance of
blood decreases
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 8
The Coulter Principle•2 chambers filled with a conductive saline fluid are separated by a small orifice (100m or less)
•Thus, most of the resistance or impedance is now in the orifice.
•By connecting a constant DC current between 2 electrodes (one in each chamber), the impedance remains constant. If a cell passes through the orifice, it displaces an equivalent volume of saline and so increases the impedance.
Wallace Coulter - Coulter orifice - 1948-1956
Cell counter
vacuum
orifice
1998 photo© J.Paul Robinson
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 10
Instrument Components
Fluidics: Specimen, sorting, rate of data collection
Optics: Light source(s), detectors, spectral separation
Electronics: Control, pulse collection, pulse analysis, triggering, time delay, data display, gating, sort control, light and detector control
Data Analysis: Data display & analysis, multivariate/simultaneous solutions, identification of sort populations, quantitation
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 11
What are the principles?
• Hydrodynamically focused stream of particles
• Light scattered by a laser or arc lamp• Specific fluorescence detection• Electrostatic particle separation for
sorting• Multivariate data analysis capability
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 12
Richard SweetRichard Sweet developed the electrostatic ink-jet printer which was the principle used by Mack Fulwyler to create a cell-sorter.
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 13
Mack Fulwyler Mack Fulwyler - sorter 1965 - electronic cell volume 1965 -
at Los Alamos National Labs - this instrument separated cells based on electronic cell volume (same principle as the Coulter counter) and used electrostatic deflection to sort. The cells sorted were RBC because they observed a bimodal distribution of cell volume when counting cells - the sorting principle was based on that developed for the inkjet printer by Richard Sweet at Stanford in 1965.
Electronic Cell Volume
After determining that the bimodal distribution was artifactual, this group were able to sort neutrophils and lymphocytes from blood.
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 14
The mysterous red cell problem
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 15
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 16
Kamentsky
Kamensky’s first benchtop instrument the Cytograph. This measured scatter using a He-Ne laser. This particular instrument was a model prior to the fluorescence detection model.
He also built a fluidic cell-sorter to evaluate the cells identified in his RCS An RCS was sent to Stanford for use by Leonard Herzenberg . The unit was also the model for the Technicon D instrument guilt by Technicon.
1970 Model“Cytograph” currentlyat Purdue University
1998 photo© J.Paul Robinson
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 17
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 18
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 19
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 20
Hydrodynamics and Fluid Systems
• Cells are always in suspension • The usual fluid for cells is saline• The sheath fluid can be saline or
water• The sheath must be saline for sorting• Samples are driven either by
syringes or by pressure systems
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 21
Fluidics• Need to have cells in suspension flow in single
file through an illuminated volume• In most instruments, accomplished by injecting
sample into a sheath fluid as it passes through a small (50-300 µm) orifice
• When conditions are right, sample fluid flows in a central core that does not mix with the sheath fluid
• This is termed Laminar flow (Sheath Flow Principle)
• The introduction of a large volume into a small volume in such a way that it becomes “focused” along an axis is called Hydrodynamic Focusing
[RFM]
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 22
• Whether flow will be laminar can be determined from the Reynolds number
• When Re < 2300, flow is always laminar
• When Re > 2300, flow can be turbulent
Fluidics - Laminar Flow
Re d v
whered tube diameter
density of fluidv mean velocity of fluid
viscosity of fluid
[RFM]
V. Kachel, H. Fellner-Feldegg & E. Menke - MLM Chapt. 3
Notice how the ink is focused into a tight stream as it is drawn into the tube under laminar flow conditions.
Notice also how the position of the inner ink stream is influenced by the position of the ink source.
[RFM]
Fluidics
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 24
Fluidics SystemsPositive Pressure Systems
• Based upon differential pressure between sample and sheath fluid. • Require balanced positive pressure via either air or nitrogen• Flow rate varies between 6-10 ms-1
+ + ++ + ++ + +
Positive Displacement Syringe Systems
• 1-2 ms-1 flow rate• Fixed volume (50 l or 100 l)• Absolute number calculations possible• Usually fully enclosed flow cells
100 l
Sample loop
Sample Waste
Flowcell3-way valve
Syringe
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 25
Syringe systems
• Bryte HS Cytometer
3 way valve
Syringe
1998 photo© J.Paul Robinson
Fluidics - Particle Orientation and Deformation
“a: Native human erythrocytes near the margin of the core stream of a short tube (orifice). The cells are uniformly oriented and elongated by the hydrodynamic forces of the inlet flow.
b: In the turbulent flow near the tube wall, the cells are deformed and disoriented in a very individual way. v>3 m/s.”
V. Kachel, et al. - MLM Chapt. 3[RFM]
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 27
Closed flow cells
Laser direction
1998 photo© J.Paul Robinson
Fluidics - Flow Chambers
H.B. Steen - MLM Chapt. 2
Flow through cuvette (sense in quartz)
[RFM]
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 29
Flow chamber blockage
A human hair blocks the flow cell channel. Complete disruption of the flow results.
1998 photo© J.Paul Robinson
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 30
The Elements of Flow Sorting
• Sample Preparation• Hardware Setup• Droplet formation• Timing• Coincidence - Purity and Efficiency• Sterile Sorting Concepts
Page 31J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt
488 nm laser
+-
Fluorescence Activated Cell SortingFluorescence Activated Cell Sorting
Charged Plates
Single cells sortedinto test tubes
FALS Sensor
Fluorescence detector
Purdue University Cytometry Laboratories
Page 32J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt
Droplet formation
T. Lindmo, D.C. Peters & R.G Sweet - MLM Chapt. 8
As liquid is ejected into air, it will form droplets. By vibrating the nozzle at a defined frequency, the size of these droplets and the position along the stream where they form can be controlled with great precision.
(Murphy)
Last Attached Droplet
Satelite droplet
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 33
Droplet break off
Video of the droplet formation in a sort stream from a Cytomation instrument. Source: Purdue CDROM vol 4, 1998
Video2.mpg
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 34
488 x 10-3
Laser power• One photon from a 488 nm argon laser has an energy of
E= 6.63x10-34 joule-seconds x 3x108
• To get 1 joule out of a 488 nm laser you need 2.45 x 1018 photons
• 1 watt (W) = 1 joule/second a 10 mW laser at 488 nm is putting out 2.45x1016 photons/sec
• UV Laser at 325 nm is putting out 1.63x1018 photons/sec• He-Ne laser at 653 nm is putting out 3.18x1018 photons/sec
E=h and E=hc/E=h and E=hc/
= 4.08x10-19 J
Shapiro p 77Shapiro p 77
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 35
Light Scatter• Materials scatter light at wavelengths at which they
do not absorb• If we consider the visible spectrum to be 350-850 nm
then small particles (< 1/10 ) scatter rather than absorb light
• For small particles (molecular up to sub micron) the Rayleigh scatter intensity at 0o and 180o are about the same
• For larger particles (i.e. size from 1/4 to tens of wavelengths) larger amounts of scatter occur in the forward not the side scatter direction - this is called Mie Scatter (after Gustav Mie) - this is how we come up with forward scatter be related to size
Shapiro p 79Shapiro p 79
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 36
Optics for forward scatter
scatterdetector
iris
blocker
Laser beam
Stream in air or a round capillary
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 37
Brewster’s Angle• Brewster’s angle is the angle at which the reflected light is linearly polarized
normal to the plane incidence• At the end of the plasma tube, light can leave through a particular angle
(Brewster’s angle) and essentially be highly polarized• Maximum polarization occurs when the angle between reflected and transmitted
light is 90o
thus Ør + Øt = 90o
since sin (90-x) = cos x
Snell’s provides (sin Øi / cos Øi ) = n2/n1
Ør is Brewster’s angle
Shapiro p 82Shapiro p 82
Ør = tan -1 (n2/n1)
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 38
Brewster’s Angle
1998 photo© J.Paul Robinson
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 39
Fluorescence• Excitation Spectrum
– Intensity of emission as a function of exciting wavelength
• Chromophores are components of molecules which absorb light
• They are generally aromatic rings
• The wavelength of absorption is related to the size of the chromophores
• Smaller chromophores, higher energy (shorter wavelength)
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 40
Fluorescence• Stokes Shift
– is the energy difference between the lowest energy peak of absorbance and the highest energy of emission
495 nm 520 nm
Stokes Shift is 25 nmFluoresceinmolecule
Flu
ores
cnec
e In
tens
ity
Wavelength
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 41
Properties of Fluorescent Molecules
Large extinction coefficient at the region of excitation High quantum yield Optimal excitation wavelength Photostability Excited-state lifetime Minimal perturbation by probe Dye molecules must be close to but below saturation
levels for optimum emission Fluorescence emission is longer than the exciting
wavelength The energy of the light increases with reduction of
wavelength
Page 42J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt
Fluorescence
Resonance Energy Transfer
Inte
nsi
ty
Wavelength
Absorbance
DONOR
Absorbance
Fluorescence Fluorescence
ACCEPTOR
Molecule 1 Molecule 2
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 43
Absorption• Basic quantum mechanics requires that molecules
absorb energy as quanta (photons) based upon a criteria specific for each molecular structure
• Absorption of a photon raises the molecule from ground state to an excited state
• Total energy is the sum of all components (electronic, vibrational, rotational, translations, spin orientation energies) (vibrational energies are quite small)
• The structure of the molecule dictates the likely-hood of absorption of energy to raise the energy state to an excited one
Shapiro p 84Shapiro p 84
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 44
Mercury Arc Lamps
Arc
Lens
Lens
1998 photo© J.Paul Robinson
1998 photo© J.Paul Robinson
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 45
Arc Lamp Excitation Spectra
Irra
dia
nce
at
0.5
m (
mW
m-2
nm
-1)
Xe Lamp
Hg Lamp
Shapiro p 99Shapiro p 99
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 46
Laser Power & NoiseLight Amplification by Stimulated Emission of
Radiation
• Laser light is coherent and monochromatic (same frequency and wavelength)
• This means the emitted radiation is in phase with and propagating in the same direction as the stimulating radiation
• ION lasers use electromagnetic energy to produce and confine the ionized gas plasma which serves as the lasing medium.
• Lasers can be continuous wave (CW) or pulsed (where flashlamps provide the pulse)
• Laser efficiency is variable - argon ion lasers are about 0.01% efficient (1 W needs 10KW power)
Shapiro p 106Shapiro p 106
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 47
Lasers
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 48
Goals of Light Collection
• Maximum signal, minimum noise• Maximum area of collection• Inexpensive system if possible• Easy alignment• Reduced heat generation• Reduced power requirement
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 49
Optical Collection systems
He-Cd Laser Argon LaserHe-Ne Laser
1998 photo© J.Paul Robinson
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 50
Interference in Thin Films
• Small amounts of incident light are reflected at the interface between two material of different RI
• Thickness of the material will alter the constructive or destructive interference patterns - increasing or decreasing certain wavelengths
• Optical filters can thus be created that “interfere” with the normal transmission of light
Shapiro p 82Shapiro p 82
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 51
Interference and Diffraction: Gratings
• Diffraction essentially describes a departure from theoretical geometric optics
• Thus a sharp objet casts an alternating shadow of light and dark “patterns” because of interference
• Diffraction is the component that limits resolution
Shapiro p 83Shapiro p 83
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 52
Interference filters
• They are composed of transparent glass or quartz substrate on which multiple thin layers of dielectric material, sometimes separated by spacer layers .
• Permit great selectivity.
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 53
Optical Filters
Dichroic Filter/Mirror at 45 deg
Reflected light
Transmitted LightLight Source
• Interference filters: Dichroic, Dielectric, reflective filters…….reflect the unwanted wavelengths
• Absorptive filters: Colour glass filters…..absorb the unwanted wavelengths
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 54
Transmitted LightTransmitted LightLight SourceLight Source
520 nm Long Pass Filter520 nm Long Pass Filter
>520 nm >520 nm LightLight
Transmitted LightTransmitted LightLight SourceLight Source
575 nm Short Pass Filter575 nm Short Pass Filter
<575 nm <575 nm LightLight
Standard Long and Short Pass Standard Long and Short Pass FiltersFilters
Standard Band Pass FiltersStandard Band Pass Filters
Transmitted LightWhite Light Source
630 nm BandPass Filter
620 -640 nm Light620 -640 nm Light
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 55
Transmission determination
• Constructive and destructive interference occurs between reflections from various layers
• Transmission determined by :– thickness of the dielectric layers– number of these layers – angle of incidence light on the filters
Optical DesignOptical Design
PMT 1
PMT 2
PMT 5
PMT 4
DichroicFilters
BandpassFilters
Laser
Flow cell
PMT 3
Scatter
Sensor
Sample
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 57
PMT• Produce current at their anodes when photons impinge upon
their light-sensitive cathodes• Require external powersource• Their gain is as high as 107 electrons out per photon in• Noise can be generated from thermionic emission of electrons
- this is called “dark current”• If very low levels of signal are available, PMTs are often cooled
to reduce heat effects• Spectral response of PMTs is determined by the composition of
the photocathode• Bi-alkali PMTs have peak sensitivity at 400 nm• Multialkali PMTs extend to 750 nm • Gallium Arsenide (GaAs) cathodes operate from 300-850 nm
(very costly and have lower gain)
Signal Detection - PMTs
Cathode Anode
Dynodes
Photons in
AmplifiedSignal Out
EndWindow
• Requires Current on dynodes• Is light sensitive• Sensitive to specific wavelengths• Can be end`(shown) or side window PMTs
Secondary emission
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 59
Diode Vs PMT• Scatter detectors are frequently diode
detectors
Back of Elite forward scatter detector showing the preamp
Front view of Elite forward scatter detector showing the beam-dump and video camera signal collector (laser beam is superimposed)
Sample stream
1998 photo© J.Paul Robinson
1998 photo© J.Paul Robinson
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 60
Review of Electronics• Reactance like resistance provides an impediment to the flow of
current, but unlike resistance is dependent on the frequency of the current
• If a DC current is applied to a capacitor a transient current flows but stops when the potential difference between the conductors equals the potential of the source
• The capacitance measured in Farads (F) is equal to the amount of charge on either electrode in Coulombs divided by the potential difference between the electrodes in volts - 1 Farad = 1 coulomb/volt
• DC current will not flow “through” a capacitor - AC current will and the higher the frequency the better the conduction
• In a circuit that contains both inductance and capacitance, one cancels the other out
• The combined effect of resistance, inductive reactance and capacitive reactance is referred to as impedance (Z) of the circuit
• Impedance is not the sum of resistance and reactance• z=(R2+(Xl-Xc)2)½ (Xl = inductive reactance, Xc = capacitive reactance)
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 61
Linear and Log circuits
• Linear circuits• Logarithmic circuits• Dynamic range• Fluorescence compensation
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 62
Why use linear amps?• The problem with compensation is that it needs to be
performed on linear data, not logarithmic data. Thus, either the entire electronics must be built in linear electronics, which requires at least 16 bit A-D converters, or a supplementary system must be inserted between the preamp and the display.
• We need the dynamic range for immunologic type markers, but we can’t calculate the compensation easily using log amps - certainly not without complex math.
• Flow cytometers amplify signals to values ranging between 0-10V before performing a digital conversion.
• Assuming this, with 4 decades and a maximum signal of 10 V we have:
10 100 1000 10000
1 100mv 10mv 1mv
Factor reduction
pulse output
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 63
How many bits?
• Assume we convert linear analog signals using an 8 bit ADC - we have 256 channels of range (2n) (28-256) corresponding to the range 0-10 V
• Channels difference is 10/256=40mV per channel
0 50 100 150 200 250
10V1V
100mV
Channels
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 64
Ideal log amp
0 50 100 150 200 250
10 V1 V
100 mV
0 50 100 150 200 250
10 V1 mV
Channels
Linear
Log
1 V100 mV10 mVLog amp
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 65
Log amps & dynamic range
Compare the data plotted on a linear scale (above) and a 4 decade log scale (below). The date are identical, except for the scale of the x axis. Note the data compacted at the lower end of the the linear scale are expanded in the log scale.
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 66
Data AcquisitionData Acquisition
• Each measurement from each detector is referred to as a “variable” or in flow parlance a “parameter”
• Data are acquired as a “list” of the values for each “parameter” (variable) for each “event” (cell)
[RFM]
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 67
Data Acquisition - Listmode
Data Acquisition - Listmode
Event Param1FS
Param2SS
Param3FITC
Param4PE
1 50 100 80 90
2 55 110 150 95
3 110 60 80 30
[RFM]
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 68
Data Presentation Formats
• Histogram• Dot plot• Contour plot• 3D plots• Dot plot with projection• Overviews (multiple histograms)
Page 69J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt
FITC Fluorescence
Mo1
CD4 CD8
CD8
CD45
leu11a
CD20 Tube
ID
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 70
Data Analysis
• Frequency Distributions• Gaussian distribution• Normal distributions• Statistics• Skewness and Kurtosis
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 71
Coefficient of Variation
Crucial in establishing:• Alignment• Fluidic stability• Staining of cells
MEAN
CV=3.0
CV=3.0
%CV Definition = St.Dev x 100MEAN
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 72
Precision - C.V.• Precision: CV• Sensitivity• MESF Units (Mean Equivalent Soluble Fluorescein)
• Accuracy and Linearity• Noise• Background• Laser noise• Shapiro’s 7th Law of Flow Shapiro’s 7th Law of Flow
Cytometry:Cytometry:
““No Data Analysis Technique Can No Data Analysis Technique Can Make Make
Good Data Out of Bad Data!!!”Good Data Out of Bad Data!!!”
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 73
One parameter frequency One parameter frequency histogramhistogram
establish regions and calculate coefficient of variation (cv)establish regions and calculate coefficient of variation (cv)cv = stdev/mean of half peakcv = stdev/mean of half peak
# of events for# of events forparticular particular parameterparameter
Page 74J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt
Histogram AnalysisNormalized Subtraction
• Very accurate• Assumption that control & test histogram are same shape• Match region finds best amplitude of control to match test histogram
False Negatives
Match region
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 75
Kolmogorov-SmirnovK-S Test
Flu
ores
cnec
e In
tens
ity
Channel Number
Cum
ulat
ive
Fre
quen
cy D
istr
ibut
ion
50
100
0 50 100 50 100
A good technique for estimating the differences between histograms
Page 76J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt
Histogram AnalysisIntegration
• Very subjective analysis• Not easily automated• Not good for weakly fluorescent signals
False PositivesFalse Negatives
Fre
quen
cy“Positive” histogram
Page 77J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt
Histogram AnalysisAccumulative Subtraction
• Very accurate• Assumption that control & test histogram are same shape• Match region finds best amplitude of control to match test histogram
Negative ControlActualNegatives
TestN
umbe
r of
Eve
nts
Cum
ulat
ive
Eve
nts
ActualPositives
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 78
Histogram OverlaysHistogram Overlays
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 79
Density Dot Plot Density Dot Plot Contour PlotContour Plot
Color of dots can give indicationColor of dots can give indication Identify subpopulationsIdentify subpopulationsof frequency of eventsof frequency of events with proper contour lineswith proper contour lines
Page 80J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt
log
PE Back gate
Forward gate
1P Fluorescence 2P Fluorescence 2P Scatter
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 81
Isometric Plot Isometric Plot 3 3 Parameter Parameter
- simulated surface is created- simulated surface is created - 3 parameter data- 3 parameter data- # of particles used as 3rd parameter- # of particles used as 3rd parameter - 3-D space- 3-D space
Multi-color studies generate a lot of data
1 2 3 4 5 6 7 8 9 10
3 color4 color 5 color
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
Log Fluorescence
QUADSTATS
Log
Flu
ores
cenc
e
++
-- +-
-+
J.Paul Robinson, Purdue University EE 520 lecture 2000.ppt Page 83
ANegativePositive
Decision Tree in Acute Leukemia
HLA-DR
TCD13,33
CD19
TdT
CD10
CD20
Mu
B,T
AMLL AML
T-ALL
AML-M3
AUL
?
PRE-BI
PRE-BII
PRE-BIII
PRE-BIVPRE-BV
CD13,33
From Duque et al, Clin.Immunol.News.