Raman spectroscopy (RS) is proving to be a valuable tool for real time noninvasive skin cancer detection via optical fiber probe. However, current methods utilizing RS for skin cancer diagnosis rely on statistically based algorithms to provide tissue classification and do not elucidate the underlying biophysical changes of skin tissue. Therefore, we aim to use RS to explore skin biochemical and structural characteristics and then correlate the Raman spectrum of skin tissue with its disease state. We have built a custom confocal micro-Raman spectrometer system with an 830nm laser light. The high resolution capability of the system allows us to measure spectroscopic features from individual tissue components in situ. Raman images were collected from human skin samples from Mohs surgical biopsy, which were then compared with confocal laser scanning, two-photon fluorescence and hematoxylin and eosin-stained images to develop a linear model of skin tissue Raman spectra. In this model, macroscopic tissue spectra obtained from RS fiber probe were fit into a linear combination of individual basis spectra of primary skin constituents. The fit coefficient of the model explains the biophysical changes spanning a range of normal and various disease states. The model allows for determining parameters similar to that a pathologist is familiar reading and will be a significant guidance in developing RS diagnostic decision schemes.
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