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Abstract #0476

Morphing and Posing of Computational Anatomical Models: Enhanced Patient-Specific MRI RF Exposure Prediction

Manuel Murbach1, Bryn A. Lloyd1, Esra Neufeld1, Wolfgang Kainz2, and Niels Kuster1,3

1ITIS Foundation, Zurich, Switzerland, 2US Food and Drug Administration (FDA), Silver Spring, MD, United States, 3ETH Zurich, Zurich, Switzerland

The current MRI safety standards for exposure to radiofrequency fields are conservative and intended to protect the entire patient population. Limits set on whole-body average specific absorption rate take the patient’s weight into consideration, which allows robust, but only very rudimentary patient-specific exposure estimation. The introduction of combined morphing and posing in computational anatomical human models will enable further improvements in the accuracy of in silico local exposure estimation. In this study, we developed refined morphing techniques and explored the benefits for estimating personalized radiofrequency absorption, which could substantially reduce the safety margins necessary for conservative assessment of radiofrequency exposure.

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