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In India oral cancer ranks the top due to the habitual usage of tobacco in its various forms and remains the major burden. Hence priority is given for early diagnosis as it is the better solution for cure or to improve the survival rate. For the past three decades, optical spectroscopic techniques have shown its capacity in the discrimination of normal and malignant samples. Many research works have conventional Raman in the effective detection of cancer using the variations in bond vibrations of the molecules. However in addition polarized Raman provides the orientation and symmetry of biomolecules. If so can polarized Raman be the better choice than the conventional Raman in the detection of cancer? The present study aimed to found the answer for the above query. The conventional and polarized Raman spectra were acquired for the same set of blood plasma samples of normal subjects and oral malignant (OSCC) patients. Thus, obtained Raman spectral data were compared using linear discriminant analysis coupled with artificial neural network (LDA-ANN). The depolarization ratio of biomolecules such as antioxidant, amino acid, protein and nucleic acid bases present in blood plasma was proven to be the best attributes in the categorization of the groups. The polarized Raman results were promising in discriminating oral cancer blood plasma from that of normal blood plasma with improved efficiency. The results will be discussed in detail.
Rekha Pachaiappan,Aruna Prakasarao, andGanesan Singaravelu
"Polarized Raman spectroscopic characterization of normal and oral cancer blood plasma", Proc. SPIE 10054, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XV, 100541F (23 March 2017); https://doi.org/10.1117/12.2255600
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Rekha Pachaiappan, Aruna Prakasarao, Ganesan Singaravelu, "Polarized Raman spectroscopic characterization of normal and oral cancer blood plasma," Proc. SPIE 10054, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XV, 100541F (23 March 2017); https://doi.org/10.1117/12.2255600