Influence of fiber optic probe geometry on the applicability of inverse models of tissue reflectance spectroscopy: computational models and experimental measurements

Abstract

Accurate recovery of tissue optical properties from in vivo spectral measurements is crucial for improving the clinical utility of optical spectroscopic techniques. The performance of inversion algorithms can be optimized for the specific fiber optic probe illumination-collection geometry. A diffusion-theory-based inversion method has been developed for the extraction of tissue optical properties from the shape of normalized tissue diffusion reflectance spectra, specifically tuned for a fiber probe that comprises seven hexagonally close-packed fibers. The central fiber of the probe goes to the spectrometer as the detecting fiber, and the surrounding six outer fibers are connected to the white-light source as illumination fibers. The accuracy of the diffusion-based inversion algorithm has been systematically assessed against Monte Carlo (MC) simulation as a function of probe geometry and tissue optical property combinations. By use of this algorithm, the spectral absorption and scattering coefficients of normal and cancerous tissue are efficiently retrieved. Although there are significant differences between the diffusion approximation and the MC simulation at short source-detector (SD) separations, we show that with our algorithm the tissue optical properties are well retrieved within the SD separation of 0.5-3 mm that is compatible with endoscopic specifications. The presented inversion method is computationally efficient for eventual real-time in vivo tissue diagnostics application.