Yan Zhou,1 Cheng-hui Liu,2 Jiyou Li,3 Lixin Zhou,3 Jingsheng He,3 Yi Sun,2 Yang Pu,2 Ke Zhu,4 Yulong Liu,4 Qingbo Li,5 Gangge Cheng,1 Robert R. Alfano2
1The General Hospital of the Air Force, PLA (China) 2The City College of New York (United States) 3Beijing Cancer Hospital (China) 4Institute of Physics (China) 5BeiHang Univ. (China)
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Resonance Raman (RR) has the potential to reveal the differences between cancerous and normal breast and brain tissues in vitro. This differences caused by the changes of specific biomolecules in the tissues were displayed in resonance enhanced of vibrational fingerprints. It observed that the changes of reduced collagen contents and the number of methyl may show the sub-methylation of DNA in cancer cells. Statistical theoretical models of Bayesian, principal component analysis (PCA) and support vector machine (SVM) were used for distinguishing cancer from normal based on the RR spectral data of breast and meninges tissues yielding the diagnostic sensitivity of 80% and 90.9%, and specificity of 100% and 100%, respectively. The results demonstrated that the RR spectroscopic technique could be applied as clinical optical pathology tool with a high accuracy and reliability.
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Yan Zhou, Cheng-hui Liu, Jiyou Li, Lixin Zhou, Jingsheng He, Yi Sun, Yang Pu, Ke Zhu, Yulong Liu, Qingbo Li, Gangge Cheng, Robert R. Alfano, "Resonance Raman spectroscopy for human cancer detection of key molecules with clinical diagnosis," Proc. SPIE 8577, Optical Biopsy XI, 85770B (19 March 2013); https://doi.org/10.1117/12.2002818