A blind source separation method (cNMF) was used to extract characteristic metabolic patterns from PRESS MRSI 3T acquired from areas of contrast enhancement in a retrospective set of 31 glioblastoma patients, one month after the end of concomitant chemoradiotherapy with temozolomide. The aim was to evaluate whether these patterns were predictive of true progression or pseudoprogression. They were used as input for supervised classifiers, achieving a maximum of 81% balanced accuracy. A moderate association between extracted patterns and outcome was detected by Cramer’s V. Spatial source distribution with nosologic maps points to MRSI-detected metabolic heterogeneity as cause for classifiers’ performance.
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