Evaluating rigid motion-affected, U-NET-estimated Q-matrices with parallel RF transmission

Blanter, Katherine Anna, Plumley, Alix, Gungor, Alper, Malik, Shaihan and Kopanoglu, Emre ORCID: https://orcid.org/0000-0001-8982-4441 2025. Evaluating rigid motion-affected, U-NET-estimated Q-matrices with parallel RF transmission. Presented at: 2025 ISMRM & ISMRT Annual Meeting & Exhibition, Honolulu, Hawaii, USA, 10-15 May, 2025.

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Abstract

Motivation: Patient motion may exacerbate SAR exposure, and may necessitate large corrective safety factors. A position adaptive safety model would facilitate high-performance scanning without compromising safety. Goal(s): We test the efficiency of using neural networks for estimating the effect of patient motion on local SAR for ultrahigh-field MRI. Approach: We trained U-Nets to estimate the effect of patient motion on Q-matrices, and compared network-estimated SAR with ground-truth after-motion SAR for realistic parallel-transmit pulses. Results: Patient motion has a statistically-significant effect on local SAR, but network-estimated safety models can recover a faithful representation of the ground-truth after-motion local SAR. Impact: The proposed approach needs a smaller corrective safety factor, which may enable higher-performance scanning without compromising safety, when using ultrahigh-field MRI for subjects who may not remain still.

Item Type:	Conference or Workshop Item (UNSPECIFIED)
Status:	Unpublished
Schools:	Schools > Psychology Research Institutes & Centres > Cardiff University Brain Research Imaging Centre (CUBRIC)
Last Modified:	18 Sep 2025 10:45
URI:	https://orca.cardiff.ac.uk/id/eprint/181104

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