gms | German Medical Science

60th Annual Meeting of the German Society of Neurosurgery (DGNC)
Joint Meeting with the Benelux countries and Bulgaria

German Society of Neurosurgery (DGNC)

24 - 27 May 2009, Münster

Label-free classification of human glioma cells by infrared spectroscopic imaging

Meeting Abstract

  • M. Kirsch - Klinik für Neurochirurgie, Carl Gustav Carus Universitätsklinikum Dresden
  • S. Küchler - Klinik für Neurochirurgie, Carl Gustav Carus Universitätsklinikum Dresden
  • A. Hermann - Klinik und Poliklinik für Neurologie, Carl Gustav Carus Universitätsklinikum Dresden
  • G. Schackert - Klinik für Neurochirurgie, Carl Gustav Carus Universitätsklinikum Dresden
  • G. Steiner - Klinisches Sensoring und Monitoring, Universitätsklinikum Dresden

Deutsche Gesellschaft für Neurochirurgie. 60. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit den Benelux-Ländern und Bulgarien. Münster, 24.-27.05.2009. Düsseldorf: German Medical Science GMS Publishing House; 2009. DocP06-01

doi: 10.3205/09dgnc305, urn:nbn:de:0183-09dgnc3056

Published: May 20, 2009

© 2009 Kirsch et al.
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Outline

Text

Objective: The discrimination of cell types at different stages of development is a crucial task in cell biology. Available techniques, based on an irreversible treatment of the cells, do not allow a sensitive label free characterization under in situ conditions. Infrared spectroscopic imaging is a new and useful tool for studying individual cells. It has established itself as a powerful method to probe the molecular composition and to indicate the biochemistry of cells. The purpose of this study is to evaluate the ability of spectroscopic imaging to differentiate individual cells between different glioma cell populations.

Methods: Monolayers of cultivated U343, T1115 and T508 human glioma cells were characterized using infrared spectroscopic imaging. A classification algorithm based on linear discriminant analysis was developed to distinguish different cells without labeling. The classification is based upon spectral features which mainly arise from proteins, nucleic acids and cholesterol.

Results: An accuracy of 91% and 84% was obtained for cells of U343 and T1115, respectively. Cells of the T508 cell line exhibit some misclassifications resulting in a lower accuracy rate of 73%. Even different mixtures of these cell types were recognized and correctly classified.

Conclusions: As demonstrated, the potential of the infrared spectroscopic imaging method to assess the overall molecular composition of cells in a non-destructive manner opens the possibility to characterize cells on a molecular level without labels or an irreversible treatment. With characterization down to the level of individual cell lines, many different aspects with regard to treatment response and differentiation are now open for non-destructive analysis.