Analytical and Bioanalytical Chemistry

, Volume 387, Issue 5, pp 1669–1677 | Cite as

Classification of malignant gliomas by infrared spectroscopic imaging and linear discriminant analysis

  • Christoph Krafft
  • Stephan B. Sobottka
  • Kathrin D. Geiger
  • Gabriele Schackert
  • Reiner Salzer
Original Paper
First Online:
Received:
Revised:
Accepted:

Abstract

Infrared (IR) spectroscopy provides a sensitive molecular fingerprint for tissue without external markers. Supervised classification models can be trained to identify the tissue type based on the spectroscopic fingerprint. Infrared imaging spectrometers equipped with multi-channel detectors combine the spectral and spatial information. Tissue areas of 4 × 4 mm2 can be analyzed within a few minutes in the macroscopic imaging mode. An approach is described to apply this methodology to human astrocytic gliomas, which are graded according to their malignancy from one to four. Multiple IR images of three tissue sections from one patient with a malignant glioma are acquired and assigned to the six classes normal brain tissue, astrocytoma grade II, astrocytoma grade III, glioblastoma multiforme grade IV, hemorrhage, and other tissue by a linear discriminant analysis model which was trained by data from a single-channel detector. Before the model is applied here, the spectra are shown to be virtually identical. The first specimen contained approximately 95% malignant glioma regions, that means astrocytoma grade III or glioblastoma. The smaller percentage of 12–34% malignant glioma in the second specimen is consistent with its location at the tumor periphery. The detection of less than 0.2% malignant glioma in the third specimen points to a location outside the tumor. The results were correlated with the cellularity of the tissue which was obtained from the histopathologic gold standard. Potential applications of IR spectroscopic imaging as a rapid tool to complement established diagnostic methods are discussed.

Keywords

Brain tumors Astrocytic gliomas FTIR imaging Tissue classification 

Abbreviations

H&E

hematoxylin and eosin

FPA

focal plane array

FT

Fourier transform

LDA

linear discriminant analysis

TFM

tissue freeze medium

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Notes

Acknowledgements

This work is financially supported by the Volkswagen Foundation within the project “Molecular Endospectroscopy” of the program “Junior research groups at universities”. The authors thank P.R. Griffith (University of Idaho, USA) for valuable suggestions to improve the manuscript.

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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Christoph Krafft
    • 1
    • 4
  • Stephan B. Sobottka
    • 2
  • Kathrin D. Geiger
    • 3
  • Gabriele Schackert
    • 2
  • Reiner Salzer
    • 1
  1. 1.Institute for Analytical ChemistryDresden University of TechnologyDresdenGermany
  2. 2.Clinic for NeurosurgeryUniversity Hospital, Dresden University of TechnologyDresdenGermany
  3. 3.Department of Neuropathology, Institute for PathologyUniversity Hospital Dresden, Dresden University of TechnologyDresdenGermany
  4. 4.Department of Materials and Natural ResourcesUniversity of TriesteTriesteItaly

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