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Abstract #3319

Classification on Ex-Vivo MRS Signals of Glioma Samples

Bernd Merkel1, Frauke Nehen2, Yasemin Oezdemir1, Markus Thorsten Harz1, Dieter Leibfritz2, Rudolf Fahlbusch3, Horst Karl Hahn1

1Fraunhofer MEVIS, Bremen, Germany; 2Institute of Organic Chemistry, University of Bremen, Bremen, Germany; 3International Neuroscience Institute, Hannover, Germany

The goal of this work is the automated classification of glioma samples with high-resolution ex-vivo MR-spectroscopy. HR-MRS is a sensitive method to detect metabolite changes in different tumor and tissue types. Altogether 47 biopsates of healthy, tumor margin and tumor center tissue, measured on a 600 Mhz spectrometer, were analyzed. For further analysis, the lipophilic compounds were omitted and only the hydrophilic ones were analyzed. By the application of ICA and further classification and feature reduction techniques, we show that the tumor margin is distinctively different from the tumor center.