Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
408-04-006 ISMRM Abstract

Cardiac MRF Optimization at 3T Using Rosette Trajectories and MT Modeling in OpenMRF

Primary: Acquisition & Reconstruction - Quantitative Imaging: relaxometry, multi-parametric, MR Fingerprinting, and synthetic MRI
Secondary: Cardiovascular - Myocardium
408-04-006 · Quantitative Imaging: MR Fingerprinting · Tuesday, 12 May, 4:00 PM–5:50 PM · Meeting Room 1.60
Keywords: MR Fingerprinting Magnetization transfer Open-Source MRI sequence optimization
Accepted
Sydney Kaplan1,2, Evan Cummings1,2, Tom Griesler1,2, Maximilian Gram3,4, Nicole Seiberlich 1,2
1Department of Radiology, University of Michigan, Ann Arbor, United States of America
2Department of Biomedical Engineering, University of Michigan, Ann Arbor, United States of America
3Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany
4Experimental Physics 5, University of Würzburg, Würzburg, Germany
Presenting Author: Nicole Seiberlich

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. Hilbert T, Xia D, Block KT, et al. Magnetization transfer in magnetic resonance fingerprinting. Magnetic Resonance in Medicine. 2020;84(1):128-141. doi:10.1002/mrm.28096 [doi]
2. Kaplan S, Hamilton J, Malik S, Murthy V, Seiberlich N. Impact of magnetization transfer effects on T1 and T2 measurements using cardiac magnetic resonance fingerprinting. Journal of Cardiovascular Magnetic Resonance. 2025;27:101546. doi:10.1016/j.jocmr.2024.101546 [doi]
3. von Knobelsdorff-Brenkenhoff F, Prothmann M, Dieringer MA, et al. Myocardial T1 and T2 mapping at 3 T: reference values, influencing factors and implications. Journal of Cardiovascular Magnetic Resonance. 2013;15(1):53. doi:10.1186/1532-429X-15-53 [doi]
4. Liu Y, Hamilton J, Rajagopalan S, Seiberlich N. Cardiac Magnetic Resonance Fingerprinting: Technical Overview and Initial Results. JACC: Cardiovascular Imaging. 2018;11(12):1837-1853. doi:10.1016/j.jcmg.2018.08.028 [doi]
5. Cruz G, Jaubert O, Botnar RM, Prieto C. Cardiac Magnetic Resonance Fingerprinting: Technical Developments and Initial Clinical Validation. Curr Cardiol Rep. 2019;21(9):91. doi:10.1007/s11886-019-1181-1 [doi]
6. Hamilton JI, Jiang Y, Chen Y, et al. MR fingerprinting for rapid quantification of myocardial T1, T2, and proton spin density - Hamilton - 2017 - Magnetic Resonance in Medicine - Wiley Online Library. https://onlinelibrary.wiley.com/doi/10.1002/mrm.26216. Accessed August 28, 2023.
7. Griesler T, Hamilton J, Kaplan S, Cummings E, Seiberlich N, Cruz G. Preparation Scheme Optimization for Abdominal MRF. In: Singapore; :3548. doi:10.58530/2024/3548 [doi]
8. Hamilton JI. A Self-Supervised Deep Learning Reconstruction for Shortening the Breathhold and Acquisition Window in Cardiac Magnetic Resonance Fingerprinting. Front Cardiovasc Med. 2022;9. doi:10.3389/fcvm.2022.928546 [doi]
9. Cummings E, Cruz GLD, Hamilton J, Seiberlich N. Single-breathhold cardiac T1, T2, T2*, and fat fraction mapping at 0.55T using dual rosette trajectory MRF and a deep image prior reconstruction. In: Honolulu, Hawaii, USA; :4603. doi:10.58530/2025/4603 [doi]
10. Bush AM, Sandino CM, Ramachandran S, et al. Rosette Trajectories Enable Ungated, Motion-Robust, Simultaneous Cardiac and Liver T2* Iron Assessment. Journal of Magnetic Resonance Imaging. 2020;52(6):1688-1698. doi:10.1002/jmri.27196 [doi]
11. Hernando D, Kellman P, Haldar JP, Liang ZP. Robust water/fat separation in the presence of large field inhomogeneities using a graph cut algorithm. Magnetic Resonance in Medicine. 2010;63(1):79-90. doi:10.1002/mrm.22177 [doi]
12. Ma D, Gulani V, Seiberlich N, et al. Magnetic resonance fingerprinting. Nature. 2013;495(7440):187-192. doi:10.1038/nature11971 [doi]
13. Shaihan J. Malik, Shaihan J. Malik, Rui Pedro A. G. Teixeira, Rui Pedro A. G. Teixeira, Joseph V. Hajnal, Joseph V. Hajnal. Extended phase graph formalism for systems with magnetization transfer and exchange. Magnetic Resonance in Medicine. 2018. doi:10.1002/mrm.27040 [doi]
14. López K, Neji R, Bustin A, et al. Quantitative magnetization transfer imaging for non-contrast enhanced detection of myocardial fibrosis. Magnetic Resonance in Medicine. 2021;85(4):2069-2083. doi:10.1002/mrm.28577 [doi]
15. Segars WP, Sturgeon G, Mendonca S, Grimes J, Tsui BMW. 4D XCAT phantom for multimodality imaging research. Med Phys. 2010;37(9):4902-4915. doi:10.1118/1.3480985 [doi]
16. Stupic KF, Ainslie M, Boss MA, et al. A standard system phantom for magnetic resonance imaging. Magnetic Resonance in Medicine. 2021;86(3):1194-1211. doi:10.1002/mrm.28779 [doi]
17. Messroghli DR, Radjenovic A, Kozerke S, Higgins DM, Sivananthan MU, Ridgway JP. Modified Look-Locker inversion recovery (MOLLI) for high-resolution T1 mapping of the heart. Magnetic Resonance in Medicine. 2004;52(1):141-146. doi:10.1002/mrm.20110 [doi]
18. Giri S, Chung YC, Merchant A, et al. T2 quantification for improved detection of myocardial edema. J Cardiovasc Magn Reson. 2009;11(1):56. doi:10.1186/1532-429X-11-56 [doi]
19. Hamilton JI, Jiang Y, Ma D, et al. Investigating and reducing the effects of confounding factors for robust T1 and T2 mapping with cardiac MR fingerprinting. Magnetic Resonance Imaging. 2018;53:40-51. doi:10.1016/j.mri.2018.06.018 [doi]
20. Cerqueira MD, Weissman NJ, Dilsizian V, et al. Standardized Myocardial Segmentation and Nomenclature for Tomographic Imaging of the Heart. Circulation. 2002;105(4):539-542. doi:10.1161/hc0402.102975 [doi]
21. Teixeira T, Hafyane T, Stikov N, Akdeniz C, Greiser A, Friedrich MG. Comparison of different cardiovascular magnetic resonance sequences for native myocardial T1 mapping at 3T. J Cardiovasc Magn Reson. 2016;18:65. doi:10.1186/s12968-016-0286-6 [doi]
22. Weingärtner S, Meßner NM, Budjan J, et al. Myocardial T1-mapping at 3T using saturation-recovery: reference values, precision and comparison with MOLLI. Journal of Cardiovascular Magnetic Resonance. 2016;18(1):84. doi:10.1186/s12968-016-0302-x [doi]
23. Heidenreich JF, Weng AM, Donhauser J, et al. T1- and ECV-mapping in clinical routine at 3 T: differences between MOLLI, ShMOLLI and SASHA. BMC Medical Imaging. 2019;19(1):59. doi:10.1186/s12880-019-0362-0 [doi]
24. Granitz M, Motloch LJ, Granitz C, et al. Comparison of native myocardial T1 and T2 mapping at 1.5T and 3T in healthy volunteers. Wien Klin Wochenschr. 2019;131(7):143-155. doi:10.1007/s00508-018-1411-3 [doi]
25. van Heeswijk RB, Feliciano H, Bongard C, et al. Free-Breathing 3 T Magnetic Resonance T2-Mapping of the Heart. JACC: Cardiovascular Imaging. 2012;5(12):1231-1239. doi:10.1016/j.jcmg.2012.06.010 [doi]
26. Layton KJ, Kroboth S, Jia F, et al. Pulseq: A rapid and hardware-independent pulse sequence prototyping framework. Magnetic Resonance in Medicine. 2017;77(4):1544-1552. doi:10.1002/mrm.26235 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/408-04-006