gms | German Medical Science

61. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC) im Rahmen der Neurowoche 2010
Joint Meeting mit der Brasilianischen Gesellschaft für Neurochirurgie am 20. September 2010

Deutsche Gesellschaft für Neurochirurgie (DGNC) e. V.

21. - 25.09.2010, Mannheim

A method for rapid spectral pathological classification of human brain tumor borders during surgery

Meeting Abstract

  • Matthias Kirsch - Klinik und Poliklinik für Neurochirurgie, Carl Gustav Carus Universitätsklinikum, Technische Universität Dresden, Deutschland
  • Allison Stelling - Institut für Bioanalytische Chemie, Technische Universität Dresden, Deutschland
  • Edmund Koch - Clinical Sensoring and Monitoring, Carl Gustav Carus Universitätsklinikum, Technische Universität Dresden, Deutschland
  • Gabriele Schackert - Klinik und Poliklinik für Neurochirurgie, Carl Gustav Carus Universitätsklinikum, Technische Universität Dresden, Deutschland
  • Reiner Salzer - Institut für Bioanalytische Chemie, Technische Universität Dresden, Deutschland
  • Gerhard Steiner - Clinical Sensoring and Monitoring, Carl Gustav Carus Universitätsklinikum, Technische Universität Dresden, Deutschland

Deutsche Gesellschaft für Neurochirurgie. 61. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC) im Rahmen der Neurowoche 2010. Mannheim, 21.-25.09.2010. Düsseldorf: German Medical Science GMS Publishing House; 2010. DocV1566

DOI: 10.3205/10dgnc042, URN: urn:nbn:de:0183-10dgnc0423

Veröffentlicht: 16. September 2010

© 2010 Kirsch et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.de). Er darf vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.


Gliederung

Text

Objective: Optical spectroscopy, namely Fourier transformed infrared spectroscopy (FTIR) was shown to differentiate various brain tumors and their primaries with high accuracy. The method was limited to processed, dry samples and all data were retrospective so far. Here, we evaluated in a prospective series the use of FTIR spectroscopy using unprocessed samples.

Methods: 18 patients with primary and secondary brain tumors were included in this study. Random samples were taken during surgery. The samples were squeezed between two calcium fluoride glass slides into a thin, translucent layer and were directly imagined under the IR-microscope. The spectra were classified according to previously obtained data. 200 accumulations were recorded per spectrum with a spectral resolution of 4 /cm. A background spectrum was recorded using a blank portion of the CaF2 slide. The measurement time for each spectrum was approximately 90 seconds. Five spectra were recorded for each tissue sample at different locations. Spectra were averaged, baseline corrected and normalized in Matlab. Spectral classification was performed using at first a linear two-point baseline correction and a normalization of each absorbance value of a spectrum to the integral absorbance was performed. The second step was classification by linear discriminant analysis (LDA).

Results: All measurements were performed on a Nicolet 5PC spectrophotometer coupled to a SpectraTech IR microscope with a -20X objective, located in the operating theatre corridor and allowed for rapid classification of the spectroscopic data, and were usually 4-10x faster than frozen section histology. The white and gray tissues differ in their higher frequency lipid bands. Three types of tumor tissue were investigated in this study: metastases, high grade gliomas and low grade astrocytoma cases. The major spectral differences between normal and high grade tumor tissue for both metastases and high grade gliomas lie in the absorbencies from the phosphate moieties of glycolipids and nucleic acids. Accuracy of distinction between normal and neoplastic tissue was >89%.

Conclusions: FTIR spectroscopy might serve as a rapid and interpolative tool for the classification of healthy and neoplastic brain tissue during a surgical procedure and might be able to guide sample assessment for optimal histopathological diagnosis. This study demonstrates that FT-IR can aid histopathological diagnosis of semi-quantitatively display tumor cell content.