Classification of colonic tissues using Raman spectroscopy and multivariate techniques

Zhiwei Huang; Wei Zheng; Effendi Widjaja; Jianhua Mo; Colin Sheppard

doi:10.1117/12.647384

27 February 2006 Classification of colonic tissues using Raman spectroscopy and multivariate techniques

Zhiwei Huang, Wei Zheng, Effendi Widjaja, Jianhua Mo, Colin Sheppard

Proceedings Volume 6093, Biomedical Vibrational Spectroscopy III: Advances in Research and Industry; 60930Q (2006) https://doi.org/10.1117/12.647384
Event: SPIE BiOS, 2006, San Jose, California, United States

Abstract

The purpose of this study was to explore the feasibility of using near-infrared (NIR) Raman spectroscopy and multivariate techniques for distinguishing cancer from normal and benign tissue in the colon. A total of 105 colonic specimens were used for Raman studies including 41 normal, 18 polyps, and 46 malignant tumors. The multivariate statistical techniques such as PCA-SVM were utilized to extract the significant Raman features and to develop effective diagnostic algorithms for tissue classification. The results showed that high-quality Raman spectra in the 800-1800 cm^-1 range can be acquired from human colonic tissues in vitro, and Raman spectra differed significantly between normal, benign and malignant tumor tissue. PCA-SVM yielded a diagnostic sensitivity of 100%, 100%, and 97.7%, and specificity of 99.8%, 100%, and 100%, respectively, for differentiation between normal, polyp, and malignant tissue. Therefore, NIR Raman spectroscopy associated with multivariate techniques provides a significant potential for the noninvasive diagnosis of colonic cancers in vivo based on optical evaluation of biomolecules.

Citation Download Citation

Zhiwei Huang, Wei Zheng, Effendi Widjaja, Jianhua Mo, and Colin Sheppard "Classification of colonic tissues using Raman spectroscopy and multivariate techniques", Proc. SPIE 6093, Biomedical Vibrational Spectroscopy III: Advances in Research and Industry, 60930Q (27 February 2006); https://doi.org/10.1117/12.647384

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