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Quantification of soft tissue parameters from spatially resolved diffuse reflectance finite element models.

Vysakh Vasudevan¹, Sujatha Narayanan Unni¹

¹Biophotonics Laboratory, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India.

International Journal for Numerical Methods in Biomedical Engineering

|October 31, 2021

Summary

Spatially resolved diffuse reflectance spectroscopy (SRDRS) uses finite element models to accurately quantify optical properties of layered tissues. This non-invasive technique aids in diagnosing skin conditions by analyzing light scattering.

Keywords:

diffuse reflectance spectroscopy finite element method look-up table skin modelling spatially resolved diffuse reflectance

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Area of Science:

Biomedical Optics
Medical Imaging
Computational Modeling

Background:

Spatially resolved diffuse reflectance spectroscopy (SRDRS) is a non-invasive optical technique for diagnosing tissue microcirculation and pigmentation disorders.
Extracting optical properties from reflectance spectra using analytical solutions is challenging.
Model-based light-tissue interaction studies are crucial for accurate optical property quantification.

Purpose of the Study:

To utilize finite element models (FEM) for light-tissue interaction to quantify optical properties.
To develop a robust method for analyzing SRDRS data for clinical applications.

Main Methods:

A bilayer finite element model simulating human skin was developed.
Diffuse reflectance spectra were generated using FEM for various optical parameters (melanin, thickness, blood fraction, oxygenation, scattering).
A look-up table (LUT) was created from simulated reflectance data for inverse modeling.

Main Results:

The LUT enabled accurate estimation of tissue optical parameters from simulated SRDRS data.
Inverse modeling using the LUT showed high agreement between estimated and expected tissue parameters.
The method was validated on a separate test dataset.

Conclusions:

Finite element modeling provides an effective approach for quantifying optical properties from SRDRS data.
The developed LUT-based inverse modeling technique offers a reliable tool for non-invasive tissue analysis.
This method holds potential for improved clinical diagnosis of skin conditions.