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

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.