Abstract #3575

MRSaiFE: towards the real-time prediction of SAR in 3T and 7T MR RF coils - a feasibility study with 10 body models

Sayim Gokyar¹, Isabelle Saniour¹, Fraser Robb², Arthur Nghiem³, Wolfgang Kainz⁴, Akshay S. Chaudhari⁵, and Simone Winkler¹

¹Radiology, Weill Cornell Medicine, New York, NY, United States, ²General Electric Healthcare, Aurora, OH, United States, ³Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States, ⁴Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD, United States, ⁵Radiology, Stanford University, Stanford, CA, United States

Synopsis

Significant RF power deposition in the body causing local specific absorption rate (SAR) in the form of hotspots is an important safety concern at 3T (128 MHz) and, even more so, at 7T (298 MHz). In this work, we expand the proof-of-concept of artificial intelligence based real-time MRI safety prediction software (MRSaiFE) to 10 body models. We show that SAR patterns can be predicted with a mean squared error (MSE) of less than 1% and a structural similarity index of above 90% for 7T brain and above 85% for 3T body MRI.

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