Enhancing cardiac MRI reliability at 3 T using motion‐adaptive B0 shimming.
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| Title: | Enhancing cardiac MRI reliability at 3 T using motion‐adaptive B |
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| Authors: | Huang, Yuheng1,2,3 (AUTHOR), Malagi, Archana Vadiraj1 (AUTHOR), Li, Xinqi1 (AUTHOR), Guan, Xingmin2 (AUTHOR), Yang, Chia‐Chi1 (AUTHOR), Huang, Li‐Ting1 (AUTHOR), Long, Ziyang1,3,4 (AUTHOR), Zepeda, Jeremy1 (AUTHOR), Zhang, Xinheng1 (AUTHOR), Yoosefian, Ghazal2 (AUTHOR), Bi, Xioaming5 (AUTHOR), Gao, Chang5 (AUTHOR), Shang, Yun4 (AUTHOR), Binesh, Nader6 (AUTHOR), Lee, Hsu‐Lei1 (AUTHOR), Li, Debiao1,3 (AUTHOR), Dharmakumar, Rohan2 (AUTHOR), Han, Hui4 (AUTHOR), Yang, Hsin‐Jung R.1 (AUTHOR) hsin-jung.yang@cshs.org |
| Source: | Magnetic Resonance in Medicine. Jan2026, Vol. 95 Issue 1, p112-124. 13p. |
| Subjects: | Cardiac magnetic resonance imaging, Magnetic resonance imaging, Magnetic flux density, Magnetic susceptibility, Deep learning |
| Abstract: | Purpose: Magnetic susceptibility differences at the heart–lung interface introduce B0‐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 B0‐field fluctuations in the heart and evaluate a deep learning–enabled motion‐adaptive B0 shimming pipeline to mitigate them. Methods: A motion‐resolved B0 mapping sequence was implemented at 3 T to quantify cardiac and respiratory‐induced B0 variations. A motion‐adaptive shimming framework was then developed and validated through numerical simulations and human imaging studies. B0‐field homogeneity and T2* mapping accuracy were assessed in multiple breath‐hold positions using standard and motion‐adaptive shimming. Results: Respiratory motion significantly altered myocardial B0 fields (p < 0.01), whereas cardiac motion had minimal impact (p = 0.49). Compared with conventional scanner shimming, motion‐adaptive B0 shimming yielded significantly improved field uniformity across both inspiratory (post‐shim SDratio: 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 T2* 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). Conclusion: The proposed motion‐adaptive B0 shimming approach effectively compensates for respiration‐induced B0 fluctuations, enhancing field homogeneity and reducing off‐resonance artifacts. This strategy improves the robustness and reproducibility of T2* mapping, enabling more reliable high‐field cardiac MRI. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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