Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
560-01-001 ISMRM Abstract

Motion-induced B0 Field Perturbation Prediction and Correction for Susceptibility Weighted Imaging at 5T

Primary: Acquisition & Reconstruction - Motion Correction: Non-Neuro
Secondary: Acquisition & Reconstruction - Artifacts and Correction Strategies
560-01-001 · New Developments in QSM I · Wednesday, 13 May, 8:20 AM–9:15 AM · Digital Posters Row A
Keywords: Motion Correction Susceptibility-weighted Imaging B0 correction 5T MRI
Accepted
Bingbing Zhao1, Yichen Zhou1, Xiaopeng Zong 1,2
1School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China
2Shanghai Clinical Research and Trial Center, Shanghai, China
Presenting Author: Xiaopeng Zong

Synopsis

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References

1. Liu, J., de Zwart, J. A., van Gelderen, P., Murphy-Boesch, J., & Duyn, J. H. (2018). Effect of head motion on MRI B0 field distribution. Magnetic resonance in medicine, 80(6), 2538–2548. https://doi.org/10.1002/mrm.27339 [doi]
2. Daval-Frérot, G., Massire, A., Mailhe, B., Nadar, M., Vignaud, A., & Ciuciu, P. (2022). Iterative static field map estimation for off-resonance correction in non-Cartesian susceptibility weighted imaging. Magnetic resonance in medicine, 88(4), 1592–1607. https://doi.org/10.1002/mrm.29297 [doi]
3. Wallace, T. E., Afacan, O., Kober, T., & Warfield, S. K. (2020). Rapid measurement and correction of spatiotemporal B0 field changes using FID navigators and a multi-channel reference image. Magnetic resonance in medicine, 83(2), 575–589. https://doi.org/10.1002/mrm.27957 [doi]
4. Brackenier, Y., Wang, N., Liao, C., Cao, X., Schauman, S., Yurt, M., Cordero-Grande, L., Malik, S. J., Kerr, A., Hajnal, J. V., & Setsompop, K. (2024). Rapid and accurate navigators for motion and B0 tracking using QUEEN: Quantitatively enhanced parameter estimation from navigators. Magnetic resonance in medicine, 91(5), 2028–2043. https://doi.org/10.1002/mrm.29976 [doi]
5. Hewlett, M., Oran, O., Liu, J., & Drangova, M. (2025). Prospective motion correction for R2* and susceptibility mapping using spherical navigators. Magnetic resonance in medicine, 93(4), 1642–1656. https://doi.org/10.1002/mrm.30385 [doi]
6. Meng, Y., Allen, J. W., Sharghi, V. K., & Qiu, D. (2025). Motion and temporal B0-shift corrections for QSM and R2* mapping using dual-echo spiral navigators and conjugate-phase reconstruction. Magnetic resonance in medicine, 93(1), 199–212. https://doi.org/10.1002/mrm.30266 [doi]
7. Wang, N., Brackenier, Y., Nurdinova, A., Zhou, Z., Abraham, D. R., Lin, Y., Cao, X., Liao, C., & Setsompop, K. (2025). Scout-based Multi-Echo NAvigating (SMENA) for high temporal resolution motion and B0 estimation: applications to EPTI and multi-echo GRE, in Proceedings of the 33rd Annual Meeting of ISMRM, Hawaii, USA. p. 0034.
8. Gretsch, F., Marques, J. P., & Gallichan, D. (2018). Investigating the accuracy of FatNav-derived estimates of temporal B0 changes and their application to retrospective correction of high-resolution 3D GRE of the human brain at 7T. Magnetic resonance in medicine, 80(2), 585–597. https://doi.org/10.1002/mrm.27063 [doi]
9. Andersson, J. L. R., Graham, M. S., Drobnjak, I., Zhang, H., & Campbell, J. (2018). Susceptibility-induced distortion that varies due to motion: Correction in diffusion MR without acquiring additional data. NeuroImage, 171, 277–295. https://doi.org/10.1016/j.neuroimage.2017.12.040 [doi]
10. Brackenier, Y., Cordero-Grande, L., Tomi-Tricot, R., Wilkinson, T., Bridgen, P., Price, A., Malik, S. J., De Vita, E., & Hajnal, J. V. (2022). Data-driven motion-corrected brain MRI incorporating pose-dependent B0 fields. Magnetic resonance in medicine, 88(2), 817–831. https://doi.org/10.1002/mrm.29255 [doi]
11. Motyka, S., Weiser, P., Bachrata, B., Hingerl, L., Strasser, B., Hangel, G., Niess, E., Niess, F., Zaitsev, M., Robinson, S. D., Langs, G., Trattnig, S., & Bogner, W. (2024). Predicting dynamic, motion-related changes in B0 field in the brain at a 7T MRI using a subject-specific fine-trained U-net. Magnetic resonance in medicine, 91(5), 2044–2056. https://doi.org/10.1002/mrm.29980 [doi]
12. Uecker, M., Lai, P., Murphy, M. J., Virtue, P., Elad, M., Pauly, J. M., Vasanawala, S. S., & Lustig, M. (2014). ESPIRiT--an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magnetic resonance in medicine, 71(3), 990–1001. https://doi.org/10.1002/mrm.24751 [doi]
13. Fessler, J.A., & Sutton, B.P. (2003) Nonuniform fast fourier transforms using min-max interpolation. IEEE Trans. Signal Process, 51(2): p. 560-574. doi: 10.1109/TSP.2002.807005 [doi]

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http://echo.ismrm.org/p/ISMRM2026/560-01-001