Discrimination of Squamous Cell Carcinoma of the Oral Cavity Using Raman Spectroscopy and Chemometric Analysis

66 samples from the human oral mucosa tissue, including 43 normal and 23 malignant tissue samples were measured by confocal Raman microspectroscopy. The low signal-to-background ratio spectra from human oral mucosa tissues were obtained by this technique without any sample preparation. A preprocessed algorithm based on wavelet analysis was used to reduce noise and eliminate background of Raman spectra. Then principal components analysis (PCA) was used as a classification method in order to identify whether the tissue is normal or not. The integrated areas of four normalized wavenumber regions 1004, 1156, 1360 1587 and 1660 cm^-1 were carried out for discrimination of the normal and malignant oral mucosa tissue samples. This could result in a new diagnostic method, which would assist the early diagnosis of squamous cell carcinoma of the oral cavity (OSCC).