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Abstract #0778

Robust RF Shimming and Small-tip-angle Multi-spoke Pulse Design with Finite Difference Regularization

Zhipeng Cao1, Adrian Paez2, Chunming Gu2, and Jun Hua2
1Vanderbilt University, Nashville, TN, United States, 2Johns Hopkins University, Baltimore, MD, United States

This study presents a finite difference regularized magnitude-least-squares algorithm that ensures robust RF shimming and small-tip-angle multi-spoke pulse design against excitation nulls and sub-optimal pulse solutions. It also calculates a monotonic trade-off between flip angle error and RF power. It was validated in simulations and experiments, and was effective for brain and knee imaging. During an EPI-based fMRI at 7T with dynamic RF shimming, the algorithm ensured high SNR throughout the human brain, compared to a near-complete local signal loss by the conventional magnitude-least-squares algorithm. Overall, the algorithm streamlines the workflow for patient-tailored 2D multislice imaging at UHF.

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