463-01-001 ISMRM Abstract

Motion-Corrected Deep-Learning Reconstruction Framework for 3D Whole Heart Joint T1/T2 mapping at 0.55T

Primary: Acquisition & Reconstruction - Image Reconstruction: AI

Secondary: Acquisition & Reconstruction - Quantitative Imaging: relaxometry, multi-parametric, MR Fingerprinting, and synthetic MRI

463-01-001 · Data-Driven Reconstruction: From Networks to Clinical Practice · Tuesday, 12 May, 8:20 AM–9:15 AM · Digital Posters Row D

Keywords: AI/ML Image Reconstruction Motion Correction T1 T2 Mapping Cardiac Model based reconstruction

Accepted

Matias I Paredes ^1,2, Dongyue Si³, Andrew Phair⁴, Rene M Botnar^1,2,3,5, Claudia Prieto^1,2,3

¹Millennium Institute for Intelligent Healthcare Engineering - iHEALTH, Santiago, Chile

²School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, Chile

³School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom

⁴Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia

⁵Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, Chile

Presenting Author: Matias I Paredes

Synopsis

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References

1. Milotta G, Bustin A, Jaubert O, Neji R, Prieto C, Botnar RM. 3D whole-heart isotropic-resolution motion-compensated joint T1 /T2 mapping and water/fat imaging. Magn Reson Med. 2020;84(6):3009-3026. doi:10.1002/mrm.28330 [doi]

2. Si, D., Crabb, M. G., Kunze, K. P., Littlewood, S. J., Prieto, C., & Botnar, R. M. (2024). Free-breathing 3D whole-heart joint T1/T2 mapping and water/fat imaging at 0.55 T. Magnetic resonance in medicine, 92(4), 1511–1524. https://doi.org/10.1002/mrm.30139 [doi]

3. Bustin A, Rashid I, Cruz G, et al. 3D whole-heart isotropic sub-millimeter resolution coronary magnetic resonance angiography with non-rigid motion-compensated PROST. J Cardiovasc Magn Reson. 2020;22(1):24. Published 2020 Apr 16. doi:10.1186/s12968-020-00611-5 [doi]

4. Phair A, Fotaki A, Felsner L, et al. A motion-corrected deep-learning reconstruction framework for accelerating whole-heart magnetic resonance imaging in patients with congenital heart disease. J Cardiovasc Magn Reson. 2024;26(1):101039. doi:10.1016/j.jocmr.2024.101039 [doi]

5. Nordio G, Schneider T, Cruz G, et al. Whole-heart T1 mapping using a 2D fat image navigator for respiratory motion compensation. Magn Reson Med. 2020;83(1):178-187. doi:10.1002/mrm.27919 [doi]

6. Prieto C, Doneva M, Usman M, et al. Highly efficient respiratory motion compensated free-breathing coronary MRA using golden-step Cartesian acquisition. J Magn Reson Imaging. 2015;41(3):738-746. doi:10.1002/jmri.24602 [doi]

7. Berglund J, Ahlström H, Johansson L, Kullberg J. Two-point dixon method with flexible echo times. Magn Reson Med. 2011;65(4):994-1004. doi:10.1002/mrm.22679 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/463-01-001