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BACKGROUNDUnderstanding the development and progression of head and neck squamous cell carcinoma is key in the quest for the early diagnosis and prevention of this type of malignancy. The current study correlated early biochemical and histologic changes in oral tissue with spectral features in fluorescence, reflectance, and light scattering spectra acquired in vivo to diagnose early stages of oral malignancies.METHODSA total of 91 tissue sites from 15 patients with varying degrees of malignancy (normal, dysplastic, and cancerous sites) and 8 healthy volunteers were analyzed with 3 spectroscopic techniques. Direct biochemical information regarding oral tissue native fluorophores was obtained with intrinsic fluorescence spectroscopy by fitting a linear combination of collagen and the reduced form of nicotinamide adenine dinucleotide (NADH) fluorescence spectra to the intrinsic tissue fluorescence spectra excited with 337 nanometer (nm) and 358‐nm laser light. Diffuse reflectance spectroscopy was used to provide information regarding tissue absorption and structure, such as hemoglobin concentration and stroma density, by measuring the wavelength‐dependent absorption and scattering coefficients. By subtracting the diffusely reflected component from the measured reflectance, light scattering spectroscopy (LSS) information resulting from single backscattering from epithelial cell nuclei was obtained. LSS provides information concerning the size distribution of cell nuclei.RESULTSThese optically extracted tissue parameters provide biochemical or structural information in vivo without the need for tissue excision, and can be used to diagnose tissue abnormalities. By combining the information provided by the three techniques, a method known as trimodal spectroscopy, a sensitivity and specificity of 96% and 96%, respectively, in distinguishing cancerous/dysplastic (mild, moderate, and severe) from normal tissue was achieved. In addition, the authors were able to distinguish dysplastic from cancerous tissue with a sensitivity of 64% and a specificity of 90%.CONCLUSIONSThe results of the current study demonstrated that Trimodal spectroscopy is a highly sensitive and specific technique with which to diagnose tissue abnormalities. Cancer 2003;97:1681–92. © 2003 American Cancer Society.DOI 10.1002/cncr.11255

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Imatinib mesylate (STI-571, Gleevec Ò

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Cutaneous injections of CHA and PLA fillers may induce granulomatous reactions presenting as intraoral nodules distant from the injection sites.

In order to evaluate the impact of anatomy on the spectral properties of oral tissue, we used reflectance and fluorescence spectroscopy to characterize nine different anatomic sites. All spectra were collected in vivo from healthy oral mucosa. We analyzed 710 spectra collected from the oral cavity of 79 healthy volunteers. From the spectra, we extracted spectral parameters related to the morphological and biochemical properties of the tissue. The parameter distributions for the nine sites were compared, and we also related the parameters to the physical properties of the tissue site. k- Means cluster analysis was performed to identify sites or groups of sites that showed similar or distinct spectral properties. For the majority of the spectral parameters, certain sites or groups of sites exhibited distinct parameter distributions. Sites that are normally keratinized, most notably the hard palate and gingiva, were distinct from nonkeratinized sites for a number of parameters and frequently clustered together. The considerable degree of spectral contrast (differences in the spectral properties) between anatomic sites was also demonstrated by successfully discriminating between several pairs of sites using only two spectral parameters. We tested whether the 95% confidence interval for the distribution for each parameter, extracted from a subset of the tissue data could correctly characterize a second set of validation data. Excellent classification accuracy was demonstrated. Our results reveal that intrinsic differences in the anatomy of the oral cavity produce significant spectral contrasts between various sites, as reflected in the extracted spectral parameters. This work provides an important foundation for guiding the development of spectroscopic-based diagnostic algorithms for oral cancer.