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Abstract #1126

Assembly of a PNS predicting “P-matrix” on a Huygens’ surface for rapid PNS assessment of 2D or 3D gradient coil windings

Mathias Davids1,2,3, Bastien Guerin1,2, and Lawrence L Wald1,2,4
1A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Dept. of Radiology, Charlestown, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, 4Harvard-MIT Health Sciences and Technology, Cambridge, MA, United States

Peripheral Nerve Stimulation (PNS) modeling has a potential role for designing and operating therapeutic and diagnostic devices (such as MRI), but is computationally demanding due to the required simulations of EM fields and neural responses. We describe compression of the PNS modeling framework into a single versatile PNS matrix (P-matrix) defined on a Huygens’ surface just outside the subject’s body to allow fast detailed PNS analysis on arbitrary coil windings/formers. This P-matrix can be translated to any coil former within seconds, allowing for rapid PNS assessment or optimization of gradient coil windings with explicit PNS constraints.

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