Improved empirical models for extraction of tissue optical properties from reflectance spectra

The use of empirical models for the extraction of optical and physiological properties from reflectance spectra is a relatively new approach, as compared to other techniques such as those based on the diffusion theory and inverse Monte Carlo algorithms. Empirical models are appealing for their ease of implementation and applicability to conditions for which analytical models are limited. Thus far, however, empirical models have been limited to only a handful of specific probe geometries. In this work, the relationship between reflectance and optical property values is explored for a wide range of geometry and tissue conditions. The influence of variation in scattering phase function, and numerical aperture of the optical fibers are investigated and incorporated into the empirical relationships for the first time. Reflectance data used in this work was simulated using an improved Monte Carlo model designed to run on a graphics processing unit (GPU). Improvements include a Modified Henyey-Greenstein and a Mie theory-based phase function in place of the conventional Henyey-Greenstein phase function, and assignment of probe-specific reflectivity conditions to better model the tissue-probe tip interface. These improvements are particularly important for probe geometries with small sourcedetector separations. Probe geometries that offer the most stable relationships between reflectance and optical property values, and hence, the best accuracy and reliability in extraction of physiological properties from tissue, are presented.