Hybrid method to estimate two-layered superficial tissue optical properties from simulated data of diffuse reflectance spectroscopy (original) (raw)

Validation of tissue optical properties measurement using diffuse reflectance spectroscopy (DRS)

Optical Methods for Tumor Treatment and Detection: Mechanisms and Techniques in Photodynamic Therapy XXVIII

The effectiveness of photodynamic treatment depends on several factors including an accurate knowledge of optical properties of the tissue to be treated. Transmittance and diffuse reflectance spectroscopic techniques are commonly used to determine tissue optical properties. Although transmittance spectroscopy technique is accurate in determining tissue optical properties, it is only valid in an infinite medium and can only be used for interstitial measurements. Diffuse reflectance spectroscopy, on the other hand, is easily adapted to most tissue geometries including skin measurements that involve semi-infinte medium. However, the accuracy of the measured optical properties can be affected by uncertainty in the measurements themselves and/or due to the uncertainty in the fitting algorithm. In this study, we evaluate the accuracy of optical properties determination using diffuse reflectance spectroscopy implemented using a contact probe setup. We characterized the error of the optical properties fitted using two fitting algorithms, a wavelength wise fitting algorithm and a full reflectance spectral fitting algorithm. By conducting systematic investigation of the measurements and fitting algorithm of DRS, we gained an understanding of the uncertainties in the measured optical properties and outlined improvement measures to minimize these errors.

Evaluation of a reflectance-based approach for optical property determination in layered tissue

Design and Quality for Biomedical Technologies II, 2009

In order to elucidate light propagation mechanisms involved in optical spectroscopy devices, the optical properties of layered mucosal tissues at ultraviolet and visible wavelengths are needed. Previous approaches to measuring this data have typically been based on spatially-resolved reflectance. However, these approaches have limitations, some of which are not well understood. Therefore, the objectives of this study were (1) to elucidate the relationship between spatiallyresolved reflectance distributions and optical properties in two-layer tissue models and (2) introduce and assess an unconstrained approach to optical property measurement. The first part of this study involved calculating reflectance from two-layer tissue for a wide variety of optical property combinations (μ a = 1-22.5, μ s ' = 5-42.5 cm-1) using a Monte Carlo scaling technique. In the second part, a neural network inverse model trained with the aforementioned results was evaluated using simulated reflectance data. This relationship between optical properties and reflectance provides fundamental insights into the strengths, weaknesses and potential limitations of strategies for optical property measurement based on spatially-resolved reflectance. The neural network approach estimated optical property values with a degree of accuracy that depended on the probe geometry (5-, 6-, 10-and 11-fiber probes were simulated). The average error in determination of μ a ranged from 15 to 51% and average error for μ s ' ranged from 8 to 32%. While computationally expensive to develop, neural network models calibrated with simulation data may prove to be a highly effective approach for rapid, unconstrained estimation of the optical properties of two-layer tissues.

Reflectance-based determination of optical properties in highly attenuating tissue

Journal of Biomedical Optics, 2003

Accurate data on in vivo tissue optical properties in the ultraviolet A (UVA) to visible (VIS) range are needed to elucidate light propagation effects and to aid in identifying safe exposure limits for biomedical optical spectroscopy. We have performed a preliminary study toward the development of a diffuse reflectance system with maximum fiber separation distance of less than 2.5 mm. The ultimate objective is to perform endoscopic measurement of optical properties in the UVA to VIS. Optical property sets with uniformly and randomly distributed values were developed within the range of interest: absorption coefficients from 1 to 25 cm −1 and reduced scattering coefficients from 5 to 25 cm −1. Reflectance datasets were generated by direct measurement of Intralipid-dye tissue phantoms at =675 nm and Monte Carlo simulation of light propagation. Multivariate calibration models were generated using feed-forward artificial neural network or partial least squares algorithms. Models were calibrated and evaluated using simulated or measured reflectance datasets. The most accurate models developed-those based on a neural network and uniform optical property intervals-were able to determine absorption and reduced scattering coefficients with root mean square errors of Ϯ2 and Ϯ3 cm −1 , respectively. Measurements of ex vivo bovine liver at 543 and 633 nm were within 5 to 30% of values reported in the literature. While our technique for determination of optical properties appears feasible and moderately accurate, enhanced accuracy may be achieved through modification of the experimental system and processing algorithms.