Michal Tepper Under the supervision of Prof. Israel Gannot

Michal TepperUnder the supervision of Prof. Israel Gannot

IntroductionSpectroscopy of biological tissues is a

powerful tool for evaluation of tissue composition and functionality.

Photothermal spectroscopy is a method for performing tissue spectroscopy, based on measuring tissue thermal changes due to light excitation.

Previous Photothermal ResearchPhotothermal spectroscopy was shown to

be valuable for surface measurements (Milner, 1998)

Single particles can be detected (Zharov, 2003)

Measurements through fiber bundles are a new field and offer new possibilities

The MethodThe temperature increase depends on tissue

composition, its optical properties and the exciting laser wavelength.

Using several wavelengths for the excitation will allow us to estimate tissue composition.

The method can be applied to internal cavities using a commercially available endoscope.

The Method

COHERENT WAVEGUIDE BUNDLE

TISSUE

LASER

THERMAL

CAMERA

ENDOSCOPE

OPTICAL FIBER

The GoalOne promising application is the

determination of the oxygenation of a tissue, a widely researched subject due to its clinical importance:Tumor detection (90% of human cancers arise

from epithelial cells)Cancer treatment adjustmentHypoxia detection

Research StagesCreating a theoretical modelDeveloping an algorithm suitable

for different types of tissueTissue-like-phantoms experimentsTissue engineered phantoms

experimentsIn-vivo experiments

WE ARE HERE

The Theoretical Model

Defining material concentration (water, melanin, hemoglobin)

Calculating optical properties of the tissue’s layers

Calculating absorption using MCML

Calculating tissue temperature distribution using COMSOL

Calculating the thermal image seen by the camera

• Simulating temperature rise in the tissue as a result of laser illumination:

Skin Tissue Model

ThicknessngH2O%Blood%

stratum corneum201.50.860.052.1*10-4

epidermis801.340.80.22.1*10-4

papillary dermis1501.40.90.50.02

upper blood net dermis801.390.950.60.3

reticular dermis15001.40.80.70.04

deep blood net dermis801.380.950.70.1

hypodermis60901.440.750.70.05

A seven layer skin tissue model was selected.

Results Monte-Carlo

Melanin absorption in epidermis

Hemoglobin absorption in dermis

Baseline absorption

J/cm3

r [cm]

z [cm]

Illumination

Results COMSOL

r [cm]

z [cm]

T [K]

Thermal Image SimulationT [K]

x [cm]

y [

cm]

Preliminary ResultsSelection of excitation wavelengths:

saturation evaluation is limited by skin color

5% melanin

25% melanin

15% melanin

Wavelength [nm] Wavelength [nm]

T [

K]

T [

K]

Hemoglobin Optical Absorption

LimitationsSolving the equation system is inaccurate

because of measurement errors.The model might be inaccurate and

parameters might change between people and between different locations.

We want to develop a generic algorithm suitable for different tissues and wavelengths.

IntuitionExamining the shape of the temperature

function and not the values.

Wavelength [nm]

Wavelength [nm]

T [

K]

µa

The SolutionThe measured temperature is a function of

several unknowns, including the saturation.The unknowns can be estimated using a

simple curve fitting algorithm.The curve fitting algorithm depends on the

initial guess for each of the unknowns. Therefore, an initial guess algorithm for the saturation was also developed.

Temperature Function

T1=f1()A1

T2=f2(A1 ,)A2

T3=f3(A1 , A2 ,)A3

The absorption of each layer is affected by the absorption of upper layers

A1=Σ µi·ci

Effective absorption of layer 1

Temperature FunctionThe temperature rise is the sum of

effective contributions of all the layers:

Each layer affects deeper layers:

The functions fi can be approximated using Taylor approximation:

( ) ( 1) ( 2) ( 3)T T layer T layer T layer

0 1 1 2 1 2 3 1 2 3( ) ,T T f A f A A f A A A

2' ''2 1 2 2 1 2 1

10 0 0

2f A f f A f A

22 1 1 2 1 3 1f A b b A b A

Temperature FunctionComparing computational results to the

theoretical equations enables us to estimate some of the coefficients:

For skin tissue (containing melanin):

For “internal” tissue (skin tissue without melanin):

0 1 2 3 4

1

Melanin Baseline Melanin Baseline Hemoglobin

Hemoglobin HbO Hb

T T a a a a

S S

20 1 2

2 2 23 4 5

Baseline Baseline

Baseline Hemoglobin Baseline Hemoglobin Hemoglobin

T T a a

a a a

Temperature Function

Results of the initial guess algorithm for skin tissue with 7.5-10% melanin:

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

True saturation

Est

imat

ed s

atur

atio

nEst

imate

d s

atu

rati

on

True saturation

Results

Results of the saturation estimation algorithm for the tissue:

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

True saturation

Est

imat

ed s

atur

atio

nEst

imate

d s

atu

rati

on

True saturation

Results

The results of the algorithm demonstrated considerable agreement with the model’s actual oxygenation values.

RMS of the error is reasonable. Hemoglobin:9g/l10.5g/l12g/l13.5g/l15g/lTotal

2.5% melanin8%7.6%6.8%7.7%8.1%7.7%

5% melanin8.7%5.1%6.3%5.4%6.8%6.6%

7.5% melanin5.2%6.4%5.9%6.4%8.1%6.5%

10% melanin9.1%6.4%7.1%8.4%5.7%7.5%

Results

Tumor Oxygenation ValuesTissueMedian satuationReference value

Spleen92.796

Subcutis8596-97

Gastric mucosa82.697

Uterine cervix6997

Liver42.798

Cervix cancer3-3297-98

Adenocarcinomas9-1396-97

Squamous cell carcinomas1996-98

Breast cancers2496-98

Results of the initial guess algorithm for skin tissue without melanin, representing internal tissue:

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

True saturation

Estim

ate

d s

atu

ration

Est

imate

d s

atu

rati

on

True saturation

Results

Results of the saturation estimation algorithm the tissue:

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

True saturation

Est

imat

ed s

atur

atio

nEst

imate

d s

atu

rati

on

True saturation

Results

Results for skin tissue without melanin.

RMS of the error is relatively small.

Hemoglobin:9g/l10.5g/l12g/l13.5g/l15g/lTotal

0% melanin5.3%4.8%4.2%5.3%5.2%5%

Results

The phantoms were created using various types of absorbers.

Experimental Setup

The agar used in the phantoms simulates the thermal properties of the skin.

Experimental Setup

Absorption spectraThe selected absorbers were

Methylene Blue, Indocyanine Green (ICG) and ink.

Experimental SetupThe phantoms are excited by 3900s

tunable laser, pumped by Millenia Vs Laser.

The relative intensity of the illumination is measured using an integration sphere.

Experimental Setup

The temperature is measured by thermoVision A40 IR camera.

The experiments can be monitored using MicroMax CCD camera.

Experimental Setup

The setup can be further simplified by using diodes and thermocouples.

Experimental Setup

Temperature measurement

0 500 1000 1500292.6

292.8

293

293.2

293.4

293.6

293.8

294

294.2

294.4

294.6

time [sec]

T [

K]

Calibration drift

Max temperature not reached

Noisy measurements

Temperature measurementThe temperature is estimated using a

curve fitting algorithm.

0 100 200 300 400 500 600 700292

292.2

292.4

292.6

292.8

293

293.2

293.4

150 200 250 300 350292.2

292.4

292.6

292.8

293

293.2

293.4

fit_ys vs. fit_xs

fit 1

T0

Tsat

Intensity CalibrationCalculated using measurements with the

integration sphere

Calibrated Measurement ResultsTemperature increase, normalized according

to intensity

Estimated temperature function

0 1 2

(1 )B G

T T I a a

S S

01 2

T TT a a

I

a1, a2 and S are unknowns and will be estimated using the curve fitting algorithm. a1 and a2 are a function

of the materials thermal and physical properties and concentrations. S is the saturation. (ratio between ICG and Methylene Blue)

Experimental StagesPreliminary measurements: Used to

fine-tune experimental procedures and algorithms and to adjust material concentrations.

Repeating measurements with a larger number of phantoms

Validating the algorithms

ResultsPreliminary measurements: Five agar

models containing two materials.For each sample there are 5 measurements

and 3 unknowns.

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.2

0.4

0.6

0.8

1

Real ratio

Est

imat

ed r

atio

ResultsThe adjusted procedures were used to

measure 11 phantoms.

ResultsPreliminary measurements of phantoms

with upper absorbing layer (simulating the epidermal layer).

Future ResearchLayered agar phantoms with increasing

complexityAdjusting the algorithmsTissue engineered phantomsFiber bundle experimentsIn-vivo experiments

Collaboration with Rabin Medical Center

Fiber Bundle ExperimentsInfrared imaging bundles can be used to detect tumors

in internal organs.

The bundles can be integrated to a commercially available endoscope.

900 fibers HGW

Fiber Bundle ExperimentsA preliminary experiment with 1mm fiber

bundle was performed on an agar model.

Results are satisfying for a first experiment:

The measured signal is clearly reduced

Reference value: 100%

Thank you..