Robust RF shimming and small-tip-angle multispoke pulse design with finite-difference regularization.

Abstract

A new regularizer is proposed for the magnitude least-squares optimization algorithm, to ensure robust parallel transmit RF shimming and small-tip-angle multispoke pulse designs for ultrahigh-field MRI. A finite-difference regularization term is activated as an additional regularizer in the iterative magnitude-least-squares based pulse design algorithm when an unwanted flip angle null distribution is detected. Both simulated and experimental maps from different transmit arrays and different human subjects at 7 T were used to evaluate the proposed algorithm. The algorithm was further demonstrated in experiment with dynamic multislice RF shimming for a single-shot gradient-echo EPI for human functional MRI at 7 T. The proposed finite-difference regularizer effectively prevented excitation null to be formed for RF shimming and small-tip-angle multispoke pulses, and improved the latter with a monotonic trade-off relationship between flip angle error and RF power. The proposed algorithm was demonstrated to be effective with several head-array geometries by simulation and with a commercial head array with 12 healthy human subjects by experiment. During a functional MRI scan at 7 T with dynamic RF shimming, the proposed algorithm ensured high image SNR throughout the human brain, compared with near-complete local signal loss by the conventional magnitude-least-squares algorithm. Using finite-difference regularization to avoid unwanted solutions, the robustness of RF shimming and small-tip-angle multispoke pulse design algorithms are improved, with better flip angle homogeneity and a monotonic trade-off relationship between flip angle error and RF power.