In vivo Native Fluorescence spectroscopic characterization of oral tissue and saliva of same group of normal, and patients with oral squamous cell carcinoma conditions were studied at 350 nm excitation. The measured fluorescence emission spectra exhibit broad emission with peaks due to NADH, FAD and Porphyrin. To resolve the emission from individual fluorophores, the measured fluorescence spectra were subjected to spectral deconvolution. Further, the variations in relative distribution, peak shifts and spectral broadening were analyzed with respect to the fluorophores, NADH, FAD, and porphyrin. The changes in the above photophysical characteristics of various native fluorophores between normal and cancer group in both tissue and saliva confirms that there is a significant molecular level changes during the transformation of normal into cancer. The extracted spectral signatures of tissues and saliva were also subjected to linear discriminant analysis and the diagnostic accuracy between tissue and saliva were compared.
During metabolism the metabolites such as hormones, proteins and enzymes were released in to the blood stream by the cells. These metabolites reflect any change that occurs due to any disturbances in normal metabolic function of the human system. This was well observed with the altered spectral signatures observed with fluorescence spectroscopic technique. Previously many have reported on the significance of native fluorescence spectroscopic method in the diagnosis of cancer. As fluorescence spectroscopy is sensitive and simple, it has complementary techniques such as excitation-emission matrix, synchronous and polarization. The fluorescence polarization measurement provides details about any association or binding reactions and denaturing effects that occurs due to change in the micro environment of cells and tissues. In this study, we have made an attempt in the diagnosis of oral cancer at 405 nm excitation using fluorescence polarization measurement. The fluorescence anisotropic values calculated from polarized fluorescence spectral data of normal and oral cancer subjects yielded a good accuracy when analyzed with linear discriminant analysis based artificial neural network. The results will be discussed in detail.
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