Fluorescence spectroscopy of oral tissue: Monte Carlo modeling with site-specific tissue properties

Abstract

A Monte Carlo model with site-specific input is used to predict depth-resolved fluorescence spectra from individual normal, inflammatory, and neoplastic oral sites. Our goal in developing this model is to provide a computational tool to study how the morphological characteristics of the tissue affect clinically measured spectra. Tissue samples from the measured sites are imaged using fluorescence confocal microscopy; autofluorescence patterns are measured as a function of depth and tissue sublayer for each individual site. These fluorescence distributions are used as input to the Monte Carlo model to generate predictions of fluorescence spectra, which are 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 are 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.

Figures

Figure 1

(a–d) Fluorescence confocal images and (e) measured fluorescence spectra at UV excitation, showing neoplastic progression in the tongue. (a) Normal tongue; (b) normal tongue with severe stromal inflammation; (c) focal mild dysplasia; (d) moderately differentiated cancer. In (a–c), the white lines represent the basement membrane and the yellow lines represent the tissue surface. Scale bars represent 200 μm. (e) Fluorescence spectra at 350 nm excitation, measured from the same oral sites shown in the confocal images. Images (b, c) are reproduced from (6) with permission.

Figure 2

Comparison of Monte Carlo model predictions with clinical fluorescence spectra measured from four oral tongue sites in the same patient. Clinical data and predictions at 350 nm excitation from (a) normal tongue, (b) normal tongue with severe inflammation, (c) focal mild dysplasia, and (d) moderately differentiated cancer. Bar graphs showing the predicted fraction of detected photons originating from the epithelium and the stroma for the (e) normal, (f) inflammatory and (g) dysplastic simulations. (h) Bar graph showing the predicted fraction of detected photons originating from the cellular region (upper 400 microns) and the deeper fibrous region for the cancer simulation.

Figure 3

(a–b) Fluorescence confocal images and (c) measured fluorescence spectra at UV excitation, showing changes in autofluorescence patterns due to anatomic site variation. (a) Normal buccal mucosa; (b) normal palate. In (a–b), the white lines represent the basement membrane and the yellow lines represent the tissue surface. Scale bars represent 200 μm. (c) Fluorescence spectra at 350 nm excitation, measured from the same oral sites shown in the confocal images.

Figure 4

Comparison of Monte Carlo model predictions with clinical fluorescence spectra measured at different anatomic sites in the oral cavity. Clinical data and predictions at 350 nm excitation from (a) normal buccal mucosa and (b) normal palate. Bar graphs showing the predicted fraction of detected photons originating from the epithelium and stroma for (c) normal buccal mucosa and (d) normal palate.