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Proceedings Paper

Confocal Raman imaging for cancer cell classification
Author(s): Evelien Mathieu; Pol Van Dorpe; Tim Stakenborg; Chengxun Liu; Liesbet Lagae
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Paper Abstract

We propose confocal Raman imaging as a label-free single cell characterization method that can be used as an alternative for conventional cell identification techniques that typically require labels, long incubation times and complex sample preparation. In this study it is investigated whether cancer and blood cells can be distinguished based on their Raman spectra. 2D Raman scans are recorded of 114 single cells, i.e. 60 breast (MCF-7), 5 cervix (HeLa) and 39 prostate (LNCaP) cancer cells and 10 monocytes (from healthy donors). For each cell an average spectrum is calculated and principal component analysis is performed on all average cell spectra. The main features of these principal components indicate that the information for cell identification based on Raman spectra mainly comes from the fatty acid composition in the cell. Based on the second and third principal component, blood cells could be distinguished from cancer cells; and prostate cancer cells could be distinguished from breast and cervix cancer cells. However, it was not possible to distinguish breast and cervix cancer cells. The results obtained in this study, demonstrate the potential of confocal Raman imaging for cell type classification and identification purposes.

Paper Details

Date Published: 8 May 2014
PDF: 6 pages
Proc. SPIE 9129, Biophotonics: Photonic Solutions for Better Health Care IV, 91290A (8 May 2014); doi: 10.1117/12.2052340
Show Author Affiliations
Evelien Mathieu, IMEC (Belgium)
Katholieke Univ. Leuven (Belgium)
Pol Van Dorpe, IMEC (Belgium)
Katholieke Univ. Leuven (Belgium)
Tim Stakenborg, IMEC (Belgium)
Chengxun Liu, IMEC (Belgium)
Liesbet Lagae, IMEC (Belgium)
Katholieke Univ. Leuven (Belgium)

Published in SPIE Proceedings Vol. 9129:
Biophotonics: Photonic Solutions for Better Health Care IV
Jürgen Popp; Valery V. Tuchin; Dennis L. Matthews; Francesco Saverio Pavone; Paul Garside, Editor(s)

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