Raman Spectroscopy and Oncology: Multivariate Statistics Methods for Cancer Grading

Authors: Francesco Niccoli, Mario D’Acunto
Journal: Engineering Proceedings
DOI: 10.3390/engproc2021008012
Over the last decade, Raman spectroscopy was demonstrated as a label-free and destructive optical spectroscopy that was able to improve diagnostic accuracy in cancer diagnosis. This ability is principally based on the great amount of biochemical information produced by the Raman scattering while investigating biological tissues. However, to achieve the relevant clinical requirements, the spectroscopic analysis and its ability to grade cancer tissues require sophisticated multivariate statistics. In this paper, we critically review multivariate statistics methods analyzed in light of their ability to process datasets generated by Raman spectroscopy in chondrogenic tumors, where distinguishing between enchondroma and the first grade of malignancy is a critical problem for pathologists.

Keywords: Raman spectroscopy; PCA and LDA; chondrogenic tumors; melanoma; diagnosis and grading

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