Using U‐Nets to Predict the Effects of Head Motion on Simulated Specific Absorption Rate for Ultra‐High Field Magnetic Resonance Imaging With Parallel Transmission

作者：Katherine Anna Blanter, Alix Plumley, Alper Güngör, Shaihan Malik, Emre Kopanoğlu · 发表于：Magnetic Resonance in Medicine · 年份：2026 · DOI：10.1002/mrm.70363 · 研究领域：Advanced MRI Techniques and Applications、Electromagnetic Fields and Biological Effects、Advanced SAR Imaging Techniques

PURPOSE: Ultrahigh-field MRI requires careful management of the specific absorption rate (SAR), which is subject and subject-position dependent. Within-scan subject motion may exacerbate local SAR exposure, necessitating large safety margins to prevent SAR underestimation, which hampers imaging performance. This study proposes a U-Net architecture to adapt safety calculations to motion as it happens, to facilitate high-performance scanning without compromising safety. METHODS: Electromagnetic simulations were performed for five body models at multiple positions with an 8-channel parallel-transmit coil. Q-matrices were transformed into real-valued SAR distributions-to train U-Nets to estimate motion-induced effects on local SAR-which were then mapped back to Q-matrices. Separate U-Nets were trained for different types of body motion (rightward/leftward/anterior/posterior/yaw), which were then cascaded to predict the effect of composite (off-axis) and larger displacements on SAR. Finally, network-estimated local SAR distributions were compared with ground truth after-motion local SAR for realistic parallel-transmit pulses. RESULTS: Subject motion had a statistically significant effect on local SAR, but network-estimated safety models recovered a faithful representation of the ground truth after-motion local SAR. For the investigated parallel-transmit pulses, the proposed approach reduced the safety margin from 2.14-fold to 1.3-fold and ensured more than 68% of the imaging perfo...