bio-optical sensing dissertation

Title Slide

Depth Resolved Diffuse Reflectance SpectroscopyRicky Hennessy

The Biomedical Informatics Lab (BMIL)The Biophotonics Laboratory

UT Biomedical Informatics Lab

UT Biomedical Informatics Lab0

Committee1/60

Mia K. Markey, Ph.D. - AdvisorThe Biomedical Informatics Lab

James W. Tunnell, Ph.D. - AdvisorThe Biophotonics Lab

Stanislav Emelianov, Ph.D.Ultrasound Imaging and Therapeutics

Andrew K. Dunn, Ph.D.Functional Optical Imaging Lab

Ammar M. Ahmed, M.D.Dermatology at Seton

UT Biomedical Informatics LabDiffuse Reflectance Spectroscopy (DRS)2/60

UT Biomedical Informatics LabApplications of DRS3

Cancer Detection

Soil CharacterizationWearable Tech

Food Quality

Endoscopic Surgery

Cosmetic Applications

UT Biomedical Informatics LabCancer Detection with DRS4/60

Extract Features from DataUse Features to Create ClassifierRajaram et al. Lasers Surg Med 42:876-887 (2010)

UT Biomedical Informatics LabDRS Instrumentation5

SpectrometerLight SourceSource FiberDetector FiberComputerFiber Bundle

UT Biomedical Informatics LabLight Absorption in Tissue6/60

Other AbsorbersWaterBilirubinLipidProteinCollagen

UT Biomedical Informatics LabLight Scattering in Tissue7/60

UT Biomedical Informatics LabBiological Origins of Scattering8/60

Scattering is caused by index of refraction mismatches

Cells = ~10 mNuclei = ~1 mCollagen = 0.1 mMembranes = 0.01 m

UT Biomedical Informatics LabScattering Coefficient (s)9/60Scattering coefficient (s) is proportional to concentration of scatterers in a medium

s-1 is the average distance a photon travels between scattering eventss


Direction of Scattering10/60

Isotropic Scattering

Anisotropic ScatteringTissue scattering is in forward direction(g = ~0.9)

Henyey-Greenstein Phase Functiong = 0

UT Biomedical Informatics LabRadiative Transport Equation (RTE)11/60

Energy

Scattering inScattering out

Absorption


Reduced Scattering Coefficient12/60

12109876543

Using reduced scattering with isotropic scattering is equivalent to larger scattering with anisotropic scattering


Diffusion Approximation to the RTE13/60

Kienle et al., JOSA A, 1997, 14(1), 246-254Assumes isotropic scatteringScattering >> absorptionSource Detector Separation > ~ 1 mmBlood is highly absorbingEpidermis is ~100 m thick

UT Biomedical Informatics LabMonte Carlo Simulation14/60



UT Biomedical Informatics LabThe Monte Carlo Lookup Table (MCLUT) Method

Hennessy et al., JBO, 2013, 18(3), 037003



Tissue Properties Optical Properties

SCATTEREDABSORBED

TISSUE PROPERTIES OPTICAL PROPERTIES SIGNALFORWARD MODELSCATTERING PROPERTIES

ABSORBER CONCENTRATIONSHbO2HbMelanin

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Forward Model Flowchart

TISSUE PROPERTIES OPTICAL PROPERTIES SIGNALFORWARD MODEL

Light Transport ModelScattering at 0, Concentration of chromophoresCalculate absorption and scattering coefficients at each wavelengthScatteringAbsorptionUse light transport model to calculate diffuse reflectanceGenerate diffuse reflectance spectrum19/60


Monte Carlo on GPU

Modern processor w/ 4 cores = 4 times speedup

Modern GPU w/ 500 cores = 500 times speedup!< $300

Alerstam et al., Biomed. Opt. Express., 2010, 1, 658-67520/60


----- Meeting Notes (2/1/14 10:54) -----Monte Carlo simulation of photon migration in turbid media is a highly parallelable problem, where a large number of photons are propagated independently, but according to identical rules and different random number sequences.

Monte Carlo Lookup Table (1 Layer)

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----- Meeting Notes (2/1/14 10:54) -----One layer model. LUT created using GPU MCML. Sample modeled spectrum with melanin and hemoglobin

MCLUT Inverse ModelREFLECTANCE OPTICAL PROPERTIES TISSUE PROPERTIES

OptimizationRoutine22/60


----- Meeting Notes (2/1/14 10:54) -----Inverse model. Just explain the flow chart

CalibrationMCLUT Modeled SpectraRMC = photons countedMeasured SpectraRmeas = Iraw/Istandard

Modeled spectra and measured spectra have same optical properties

23/60


Validation of One-Layer Model

RMSPE = 2.42%RMSPE = 1.74%Validation with 3 X 6 matrix of phantoms containing hemoglobin and polystyrene beads.Decreased percent error of 3.16% and 10.86% for s' and a, respectively, when compared to experimental LUT method24/60


Errors Caused by One-Layer Assumption for Skin




Fit Two-Layer Data with One Layer Model26/60

Hb + HbO2melanin

melanin +Hb + HbO21. Create two-layer spectra2. Fit with one-layer model[mel][Hb]SO2ScatteringEpidermal thickness[mel][Hb]SO2ScatteringVessel radiusNotice that the fit is very good

UT Biomedical Informatics LabMelanin27/60

One-Layer model underestimates [mel]Magnitude of error is dependent on epidermal thickness (Z0)Z0 Error

UT Biomedical Informatics LabHemoglobin28/60

One-Layer model underestimates [Hb]Magnitude of error is dependent on epidermal thickness (Z0)Z0 Error

UT Biomedical Informatics LabOxygen Saturation29/60

One-Layer model overestimates SO2 when SO2 < 50%One-Layer model underestimates SO2 when SO2 > 50%Magnitude of error is dependent on epidermal thickness (Z0)Z0 Error

UT Biomedical Informatics LabPigment Packaging30/60

In tissue, blood is confined to vesselsThis significantly reduces the optical path length where absorption is high (Soret Band)Causes a flattening of the absorption spectrum

UT Biomedical Informatics LabVessel Radius vs. Epidermal Thickness31/60

Vessel radius (pigment packaging) factor is highly correlated with top-layer thicknessPigment packaging factor is likely a combination of vessel packaging and epidermal thickness

UT Biomedical Informatics LabCorrelation Between [Hb] and [mel]32/60

R = 0.04R = 0.80One-layer assumption causes artificial correlation between [Hb] and [mel]

UT Biomedical Informatics LabConclusions about One-Layer ErrorsCauses underestimation of [Hb] and [mel]Magnitude of error is function of epidermal thicknessCauses error in SO2 that is a function of epidermal thickness as well as SO2Vessel Packaging factor and epidermal thickness are highly correlatedCauses an artificial correlation in [Hb] and [mel]33/60

UT Biomedical Informatics LabThe Two-Layer Monte Carlo Lookup Table Method

Sharma, Hennessy et al., Biomed Optics Express, 2014, 5(1), 40-53



Motivation of Two-Layer Model

EpidermisDermisStratum Corneum

Melanin

Hemoglobin35/60


Motivation of Two-Layer ModelPigmentary disorder studiesDisease (rosacea, lupus, scleroderma, morphea, lymphederma) monitoringTreatment outcome measures for many cosmetic proceduresTopical medical absorption studiesMeasuring thickness of psoriatic plaqueDetermination of epidermal thickness

MelasmaMethod of melasma treatment depends on depth of melanin

Woods lamp is current method to determine location of melaninQualitative More contrast for epidermal melasma. Doesnt work for patients with dark skin.Asawansa et al., Int. J. Derm, 1999, 38, 801-80736/60


Two Layer MCLUTWe can create a 5D LUTTop layer absorptionBottom layer absorptionScatteringTop layer thicknessSDS37/60

Segment of 5D lookup tableZ0 = 200 mSDS = 200 mR1 = R2 = 100 m

Sharma, Hennessy et al., Biomed. Opt. Express, 2014, 5(1), 40-53


Two-Layer Forward Model38/60


Two-Layer MCLUT Inverse Model

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Two-Layer Phantom Construction

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Phantom Validation StudyPHANTOMs (mm-1)a,t (mm-1)a,b (mm-1)11.50.251.27521.50.251.27531.52.30.2541.52.30.2551.50.252.361.50.252.372.850.252.382.850.252.392.852.30.25102.851.2750.25112.851.2752.3120.750.251.275130.751.2750.25140.750.252.3

Set of Two Layer PhantomsRange of scattering and absorption in skin

s = 1-3 mm-1a = 0 2.3 mm-1

Nichols et al., JBO, 2012, 17(5), 05700141/60


Phantom Data42/60


Results: Top Layer Thickness43/60

Error = 10% for Z0 < 500 m

Photons are not sampling this deep.

UT Biomedical Informatics LabResults: All Optical Properties44/60

UT Biomedical Informatics LabResults: Dependence on SDS45/60

Main TakeawayAccuracy of extracted parameters is dependent on probe geometry. This is due to sampling depth of probe.

UT Biomedical Informatics LabSampling Depth of Diffuse Reflectance Spectroscopy Probes




Probe Geometry and Sampling Depth47

TissueSourceFiberDetectionFiberSDS

SamplingDepthZ(a,s,rS,rD,SDS)

rSrD a,s

rS,rD

SDS)

-Tissue Optical Properties-Source/Detector Fiber Sizes-Source/Detector Separation* Credit to Will Goth for this slide47/60

UT Biomedical Informatics LabDefining Sampling Depth48/60

This experiment was performed computationally (MC simulation) and experimentally (phantoms)

UT Biomedical Informatics LabExperimental Validation49/60

E = 1.71%E = 1.27%E = 1.24%SDS = 370 mSDS = 740 mSDS = 1110 mLook at axes to see deeper sampling for larger SDSs

UT Biomedical Informatics LabAnalytical Model of Sampling Depth50/60

This expression can be used to aid in the design of application specific DRS probesE = 2.89%Expression was found using TableCurve 3D. Free parameters [a1, a2, a3, a4] were selected using a least-squares fitting algorithm.

UT Biomedical Informatics LabChoice of g and Phase Function51/60

The choice for g and phase function had negligible impact on the sampling depth model

UT Biomedical Informatics LabApplying the Sampling Depth Model52/60

6-around-1 adjacent fiber orientation with medium (series 1), high (series 2), and low (series 3) absorption.Sampling depth changes with wavelength

UT Biomedical Informatics LabPilot Study: Two-Layer MCLUT Method Applied to In Vivo Data



Study Population and Data54/6080 SubjectsIRB approval from UT Austin - #0000203051 males, 29 FemalesAverage age of 25.7 yearsAges 18-46

Measured spectra from the following anatomical locationsBackCalfCheekForearmPalm

Measured the followingMelaninHemoglobinScattering Epidermal Thickness

This study is still unpublished

UT Biomedical Informatics LabInstrumentation55/60

x 2Source Diameter = 40 mRing 1 Diameter = 40 mRing 2 Diameter = 200 mRing 1 SDS = 55 mRing 2 SDS = 205 m

Unfortunately, data from ring 1 was unusable

UT Biomedical Informatics LabMelanin56/60

Palm has less melanin, which agrees with the expected result.

Average of 1.83 mg/ml is within range of published values for melanin concentration[0-5 mg/ml]

UT Biomedical Informatics LabHemoglobin57/60

Higher levels of hemoglobin in the face and forearm agrees with the expected results.

Average of 1.37 mg/ml is within range of published values for [Hb][0.5-10 mg/ml]

UT Biomedical Informatics LabScattering58/60

No significant difference between anatomical locations.

Average of 22.75 cm-1 is within range of published values for scattering at 630 nm[15 25 cm-1]

UT Biomedical Informatics LabEpidermal Thickness59/60

No significant difference between anatomical locations.

Average of 90 m is within range of published values for epidermal thickness.[40 200 m]

We expected to see a difference between anatomical locations.

UT Biomedical Informatics LabConclusions about Pilot StudyA two-layer model can be used to extract depth dependent properties from in vivo DRS dataThe results agree with previously published valuesHowever, we expected to see a difference between anatomical locations for epidermal thicknessThis could be due to the absence of data from the inner ring of fibers.60/60

UT Biomedical Informatics LabConclusions about Pilot StudyData should be recollected with multiple SDSsAdditional patient data such as race/ethnicity and skin color should be documented61

UT Biomedical Informatics LabOverall ConclusionsThe MCLUT method is an accurate and fast way to analyze DRS dataA one-layer assumption for skin causes significant errors in DRS data analysisThe MCLUT method can be extended to two-layers, allowing the extraction of depth dependent propertiesDepth sampling of DRS probes can be tuned by changing the probe geometryDRS can be used to measure the depth dependent properties of skin in vivo

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Contributions to Field63The MCLUT Method

Two-Layer MCLUT Method

One-Layer Errors Analysis

DRS Sampling Depth Analysis

UT Biomedical Informatics LabFundingThe NIH (R21EB0115892)The NSF (DGE-1110007)CPRIT (RP130702)64

UT Biomedical Informatics LabAcknowledgements65The Biophotonics LabJames W. TunnellWill GothBin YangManu SharmaSam Lim Sheldon BishXu FengVarun PataniThe Biomedical Informatics LabMia K. MarkeyNishant VermaGezheng WenClement SunNisha KumaraswamyHans HuangJuhun LeeGautam MuralidharDaifeng Wang

UT BME StaffMargo CousinsBrittain SobeyMichael Don


bio-optical sensing dissertation

Healthcare