Abstract #0496

Accurate and Fast Reconstruction of Magnetic Resonance Fingerprinting for Water-Fat Separation in Neuromuscular Diseases

Fabian Balsiger^1,2,3, Olivier Scheidegger^4,5, Pierre G Carlier^2,3, Mauricio Reyes¹, and Benjamin Marty^2,3

¹Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland, ²NMR Laboratory, Institute of Myology, Paris, France, ³NMR Laboratory, CEA, DRF, IBFJ, MIRCen, Paris, France, ⁴Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland, ⁵Support Center for Advanced Neuroimaging (SCAN), Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

The MR fingerprinting sequence MRF-WF is tailored for water and fat separation imaging for neuromuscular diseases (NMDs). Currently, the adoption of MRF-WF in the clinics is hindered by the long MR map reconstruction time of four hours per image slice. We propose a spatiotemporal convolutional neural network (CNN) to reconstruct the MR maps. We show that our CNN is robust to a highly heterogeneous dataset including patients with various NMDs. The method might be a possible solution for clinical application of MRF-WF for NMDs due to the significantly lowered reconstruction time.

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