Predicting artifacts in maximum intensity projections of high b-value DWI of the breast using neural networks.
Andrzej Liebert1, Lorenz Kapsner1, Lukas Folle2, Hannes Schreiter1,2, Badhan Kumar Das1,2, Sabine Ohlmeyer1, Andreas Maier2, Evelyn Wenkel1, Frederik B. Laun1, Michael Uder1, and Sebastian Bickelhaupt1
1Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, 2Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
DWI acquisitions in MRI are prone to artifacts caused e.g. by insufficient fat saturation and can significantly impede the diagnostic assessment. We investigated the ability to predict the occurrence of these artifacts in maximum intensity projections (MIPs) of high b-value DWI using a neuronal network that analyses T2w images, which were acquired prior to the DWI sequence. An AuRoC of 0.83 with sensitivity of 0.82 and specificity of 0.61 was achieved. Investigation of the regions of the T2w images most important for the decision of the neural network showed a good correlation with artifact-affected areas in the DWI MIP images.
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