Keywords: Prostate, Spectroscopy, multi-center, cancer, aggressiveness
Location and aggressiveness of cancer lesions in the prostate were assessed with a Multivariate Curve Resolution (MCR) approach. This data-driven method was trained on 3D 1H MRSI data from 63 patients from 6 institutions to extract common spectroscopic components without needing prior knowledge. MCR identified 5 components related to known prostate metabolites, residual lipid and water signals. The relative amounts of these components robustly separated cancer from benign tissue in a test set of 43 other subjects from 8 centers, and showed a strong correlation with cancer aggressiveness. This approach facilitates automatic analysis of prostate MRSI, avoiding subjective human intervention.
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