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Abstract #1522

Virtual Dynamic Contrast Enhanced MRI of the Breast using a U-Net

Hannes Schreiter1,2, Vishal Sukumar1,2, Lorenz Kapsner1, Lukas Folle2, Sabine Ohlmeyer1, Frederik Bernd Laun1, Evelyn Wenkel1, Michael Uder1, Andreas Maier2, Sebastian Bickelhaupt1, and Andrzej Liebert1
1Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany, 2Patter Recognition Lab, Department of Computer Science, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany


Magnetic resonance imaging (MRI) examinations of the breast require intravenous administration of gadolinium based contrast agents (GBCA) for comprehensive characterization of the tissue. Novel approaches reducing the need for GBCA might therefore be of value. Here a virtual dynamic contrast enhancement (vDCE) using a U-net architecture is investigated in a cohort of n=540 patients. The vDCE generates T1 subtraction images for five consecutive time points predicting the perfusion maps based on native T1-weighted, T2-weighted, and multi-b-value diffusion weighted acquisitions. A mean structural similarity index (SSIM) value over a test group of 82 patients of 0.848±0.025 was achieved.

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