Morphing and Posing of Computational Anatomical Models: Enhanced Patient-Speci�c MRI RF Exposure Prediction

Synopsis The current MRI safety standards for exposure to radiofrequency �elds are conservative and intended to protect the entire patient population. Limits set on whole-body average speci�c absorption rate take the patient’s weight into consideration, which allows robust, but only very rudimentary patientspeci�c 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 re�ned morphing techniques and explored the bene�ts for estimating personalized radiofrequency absorption, which could substantially reduce the safety margins necessary for conservative assessment of radiofrequency exposure.