Fluorescence Spectroscopy of Oral Tissue: Monte Carlo Modeling with Site-Specific Tissue Properties

摘要

A Monte Carlo model with site-specific input was used to predict depth-resolved fluorescence spectra from individual normal, inflammatory, and neoplastic oral sites. Our goal in developing this model was to provide a computational tool to study how the morphological characteristics of the tissue affect clinically measured spectra. Tissue samples from the measured sites were imaged using fluorescence confocal microscopy; autofluorescence patterns were measured as a function of depth and tissue sublayer for each individual site. These fluorescence distributions were used as input to the Monte Carlo model to generate predictions of fluorescence spectra, which were compared to clinically measured spectra on a site-by-site basis. A lower fluorescence intensity and longer peak emission wavelength observed in clinical spectra from dysplastic and cancerous sites were found to be associated with a decrease in measured fluorescence originating from the stroma or deeper fibrous regions, and an increase in the measured fraction of photons originating from the epithelium or superficial tissue layers. The simulation approach described here can be used to suggest an optical probe design that samples fluorescence at a depth that gives optimal separation in the spectral signal measured for benign, dysplastic and cancerous oral mucosa.