Detection and grading of human gliomas by FTIR spectroscopy and a genetic classification algorithm

Gerald Steiner; R. A. Shaw; Lin-P'ing Choo-Smith; Wolfram Steller; Laryssa Shapoval; Gabriele Schackert; Stephan Sobottka; Reiner Salzer; Henry H. Mantsch

doi:10.1117/12.460789

27 March 2002 Detection and grading of human gliomas by FTIR spectroscopy and a genetic classification algorithm

Gerald Steiner, R. A. Shaw, Lin-P'ing Choo-Smith, Wolfram Steller, Laryssa Shapoval, Gabriele Schackert, Stephan Sobottka, Reiner Salzer, Henry H. Mantsch

Author Affiliations +

Proceedings Volume 4614, Biomedical Vibrational Spectroscopy II; (2002) https://doi.org/10.1117/12.460789
Event: International Symposium on Biomedical Optics, 2002, San Jose, CA, United States

Abstract

A new approach is presented to distinguish cancerous from normal brain tissue via linear discriminant analysis of Fourier transform infrared (FTIR) spectra. FTIR microspectroscopy was used to map various thin-section tumor samples with different malignancy grades (grades II-VI) and non-tumor samples obtained from various patients by surgical removal. Spectral analysis revealed features characteristic of tumors with increasing malignancy. A genetic region selection algorithm combined with linear discriminant analysis was used to derive classifiers distinguishing among spectra of control tissue, astrocytoma grade II, astrocytoma grade III and glioblastoma grade IV. Employing the World Health Organization histopathological diagnostic scheme as the gold standard, the spectra were classified with a success rate of approximately 85 percent. These results demonstrate the potential of the combination of FTIR spectroscopy and pattern recognition routines in providing a more objective method for brain tumour grading and diagnosis.

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Gerald Steiner, R. A. Shaw, Lin-P'ing Choo-Smith, Wolfram Steller, Laryssa Shapoval, Gabriele Schackert, Stephan Sobottka, Reiner Salzer, and Henry H. Mantsch "Detection and grading of human gliomas by FTIR spectroscopy and a genetic classification algorithm", Proc. SPIE 4614, Biomedical Vibrational Spectroscopy II, (27 March 2002); https://doi.org/10.1117/12.460789

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