In vivo Raman spectroscopic characteristics of different sites of the oral mucosa in healthy volunteers.

Abstract

Investigate the biochemistry of in vivo healthy oral tissues through Raman spectroscopy. We aimed to characterize the biochemical features of healthy condition in oral subsites (buccal mucosa, lip, tongue, and gingiva) of healthy subjects. More specifically, we investigated Raman spectral characteristics and biochemical content of in vivo healthy tissues on Brazilian population. This characterization can be used to better define normal tissue and improve the detection of oral premalignant conditions in future studies. For spectroscopic analysis a Raman spectrometer (Kaiser Optical Systems imaging spectrograph Holospec, f / 1.8i-NIR) coupled with a laser 785nm, 60mW was used. Raman measurements were obtained by means of an optical fiber (EMVision fiber optic probe) coupled between the laser and the spectrometer. Three spectra per site were acquired from the lip, buccal mucosa, tongue, and gingiva of ten healthy volunteers. This resulted in 30 spectra per oral sub-site and in total 120 spectra. We report detailed biochemical information on these subsites and their relative composition based on deconvolution studies of their spectra. Finally, we also report classification efficiency of 61, 83, 41, and 93% for buccal, gingiva, lip, and tongue respectively after applying multivariate statistical tools. We quantitated the contribution of various biochemicals in terms of percentage, and this will enable comparison not only across anatomical sites but also across studies. Raman spectroscopy can rapidly probe tissue biochemistry of healthy oral regions. Moreover, the study suggests the possibility of using Raman spectroscopy combined with signal processing and multivariate analysis methods to differentiate the oral sites in healthy conditions and compare with pathological conditions in future studies. The spectral characterization of the healthy condition of oral tissues by a noninvasive, label-free, and real-time analytical techniques is important to create a spectral reference for future diagnosis of pathological conditions.