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Abstract #1390

An Objective Method for Automated Classification of Brain Tumors using Proton MR Spectroscopy

Yu Zhang1, Sanjeev Chawla1, Sumei Wang1, Sangeeta Chaudhary1, Jaroslaw Krejza1, E. R. Melhem1, Harish Poptani1

1Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States

We investigated whether LC Model and linear discriminant analysis of the 1H MRS data from the contrast enhancing and peri-tumoral regions of the tumor can be used as an objective method for better classification of brain tumors. Linear discriminant analysis correctly classified 85% of 138 patients from six different brain tumor subtypes. Classification accuracies of glioblastomas versus metastases and astrocytomas versus oligodendrogliomas were 83% and 94% respectively. In comparison to previous 1H MRS studies, our study proposes a fully automated 1H MRS data analysis approach with minimum operator intervention and high diagnostic accuracy in brain tumor classification.