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Abstract #0826

MCR-ALS application for prostate cancer localization

Angeliki Stamatelatou1, Carlo Giuseppe Bertinetto2, Jeroen Jansen2, Geert Postma2, Arend Heerschap1, and Tom Scheenen1
1Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, Netherlands, 2Analytical Chemistry & Chemometrics, Institute for Molecules and Materials, Nijmegen, Netherlands


Three-dimensional MRSI data of the prostate was analyzed with a Multivariate Curve Resolution-Alternating (MCR) approach for rapid automated localization and classification of cancer and healthy tissue. This data-driven method was used to extract common spectroscopic components without a need of prior knowledge, and compared to fitting a linear combination of prior knowledge models (LCModel). The MCR method identified components with known prostate metabolites and residual lipid and water signals Altogether, our approach can be considered as a step towards the development of an automated tool for classification of prostate MRSI spectra, avoiding subjective human intervention.

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