Motivation: Achieving consistent B0 homogeneity in cardiac MRI at 3T remains challenging due to the impact of respiratory motion. Current clinical shimming protocols lack adequate motion compensation and require manual intervention. Goal(s): To develop a motion-adapted B0 shimming pipeline that autonomously adjusts for motion-induced field variations, thereby improving field homogeneity. Approach: A motion-resolved multi-echo GRE sequence was implemented and integrated with deep learning-based segmentation for automated shimming volume delineation. Results: Our approach demonstrated a 28% improvement in B0 field homogeneity compared to conventional scanner manual selected shimming, with a significant 15% reduction in T2* mapping inhomogeneity. Impact: This study develops a motion-adapted shimming technique for reliable, operator-independent CMR shimming at 3T. This approach holds particular promise for patients with compromised breath-hold capacity, providing the potential for more consistent image quality and accurate clinical CMR assessments.
Li et al. (Tue,) studied this question.