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Proceedings Paper

Characterization and discrimination of human breast cancer and normal breast tissues using resonance Raman spectroscopy
Author(s): Binlin Wu; Jason Smith; Lin Zhang; Xin Gao; Robert R. Alfano
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Paper Abstract

Worldwide breast cancer incidence has increased by more than twenty percent in the past decade. It is also known that in that time, mortality due to the affliction has increased by fourteen percent. Using optical-based diagnostic techniques, such as Raman spectroscopy, has been explored in order to increase diagnostic accuracy in a more objective way along with significantly decreasing diagnostic wait-times. In this study, Raman spectroscopy with 532-nm excitation was used in order to incite resonance effects to enhance Stokes Raman scattering from unique biomolecular vibrational modes. Seventy-two Raman spectra (41 cancerous, 31 normal) were collected from nine breast tissue samples by performing a ten-spectra average using a 500-ms acquisition time at each acquisition location. The raw spectral data was subsequently prepared for analysis with background correction and normalization. The spectral data in the Raman Shift range of 750- 2000 cm-1 was used for analysis since the detector has highest sensitivity around in this range. The matrix decomposition technique nonnegative matrix factorization (NMF) was then performed on this processed data. The resulting leave-oneout cross-validation using two selective feature components resulted in sensitivity, specificity and accuracy of 92.6%, 100% and 96.0% respectively. The performance of NMF was also compared to that using principal component analysis (PCA), and NMF was shown be to be superior to PCA in this study. This study shows that coupling the resonance Raman spectroscopy technique with subsequent NMF decomposition method shows potential for high characterization accuracy in breast cancer detection.

Paper Details

Date Published: 19 February 2018
PDF: 7 pages
Proc. SPIE 10489, Optical Biopsy XVI: Toward Real-Time Spectroscopic Imaging and Diagnosis, 104890X (19 February 2018); doi: 10.1117/12.2288094
Show Author Affiliations
Binlin Wu, Southern Connecticut State Univ. (United States)
Jason Smith, Southern Connecticut State Univ. (United States)
Lin Zhang, The City College of New York (United States)
Xin Gao, LaGuardia Community College (United States)
Robert R. Alfano, The City College of New York (United States)


Published in SPIE Proceedings Vol. 10489:
Optical Biopsy XVI: Toward Real-Time Spectroscopic Imaging and Diagnosis
Robert R. Alfano; Stavros G. Demos, Editor(s)

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