Enhancing cardiac MRI reliability at 3 T using motion-adaptive B<sub>0</sub> shimming.
Authors
Affiliations (6)
Affiliations (6)
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
- Department of Radiology & Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
- Bioengineering, University of California, Los Angeles, Los Angeles, California, USA.
- MRI Research Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA.
- MR R&D Collaborations, Siemens Medical Solutions Inc., Los Angeles, California, USA.
- Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Abstract
Magnetic susceptibility differences at the heart-lung interface introduce B<sub>0</sub>-field inhomogeneities that challenge cardiac MRI at high field strengths (≥ 3 T). Although hardware-based shimming has advanced, conventional approaches often neglect dynamic variations in thoracic anatomy caused by cardiac and respiratory motion, leading to residual off-resonance artifacts. This study aims to characterize motion-induced B<sub>0</sub>-field fluctuations in the heart and evaluate a deep learning-enabled motion-adaptive B<sub>0</sub> shimming pipeline to mitigate them. A motion-resolved B<sub>0</sub> mapping sequence was implemented at 3 T to quantify cardiac and respiratory-induced B<sub>0</sub> variations. A motion-adaptive shimming framework was then developed and validated through numerical simulations and human imaging studies. B<sub>0</sub>-field homogeneity and T<sub>2</sub>* mapping accuracy were assessed in multiple breath-hold positions using standard and motion-adaptive shimming. Respiratory motion significantly altered myocardial B<sub>0</sub> fields (p < 0.01), whereas cardiac motion had minimal impact (p = 0.49). Compared with conventional scanner shimming, motion-adaptive B<sub>0</sub> shimming yielded significantly improved field uniformity across both inspiratory (post-shim SD<sub>ratio</sub>: 0.68 ± 0.10 vs. 0.89 ± 0.11; p < 0.05) and expiratory (0.65 ± 0.16 vs. 0.84 ± 0.20; p < 0.05) breath-hold states. Corresponding improvements in myocardial T<sub>2</sub>* map homogeneity were observed, with reduced coefficient of variation (0.44 ± 0.19 vs. 0.39 ± 0.22; 0.59 ± 0.30 vs. 0.46 ± 0.21; both p < 0.01). The proposed motion-adaptive B<sub>0</sub> shimming approach effectively compensates for respiration-induced B<sub>0</sub> fluctuations, enhancing field homogeneity and reducing off-resonance artifacts. This strategy improves the robustness and reproducibility of T<sub>2</sub>* mapping, enabling more reliable high-field cardiac MRI.