Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
451-03-007 / 451-03-007 ISMRM Abstract

A universal plug-and-play framework for rapid reconstruction of contrast-enhanced 5D free-running cardiac MRI

Accepted
Kevin B Borsos 1, Augustin C Ogier2, Christopher W Roy2, Xavier Sieber2, Milan Prša3, Matthias Stuber2,4, Ruud B van Heeswijk2, Roger Hullin5, Orlando Simonetti6, Tobias Rutz5, Thomas Küstner7, Jérôme Yerly2,4
1Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
2Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
3Women-Mother-Child Department, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
4Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
5Cardiovascular Department, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
6Department of Radiology, The Ohio State University, Columbus, United States of America
7Medical Image and Data Analysis (MIDAS.lab), Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Tuebingen, Germany
Presenting Author: Kevin B Borsos

Synopsis

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References

1. Di Sopra, et al. "An automated approach to fully self‐gated free‐running cardiac and respiratory motion‐resolved 5D whole‐heart MRI." Magnetic resonance in medicine 82.6 (2019): 2118-2132. https://doi.org/10.1002/mrm.27898 [doi]
2. Holtackers, and Stuber. "Free-running cardiac and respiratory motion-resolved imaging: a paradigm shift for managing motion in cardiac MRI?." Diagnostics 14.17 (2024): 1946. https://doi.org/10.3390/diagnostics14171946 [doi]
3. Feng, et al. "5D whole‐heart sparse MRI." Magnetic resonance in medicine 79.2 (2018): 826-838. https://doi.org/10.1002/mrm.26745 [doi]
4. Heckel, et al. "Deep learning for accelerated and robust MRI reconstruction." Magnetic Resonance Materials in Physics, Biology and Medicine 37.3 (2024): 335-368. https://doi.org/10.1007/s10334-024-01173-8 [doi]
5. Ahmad, et al. "Plug-and-play methods for magnetic resonance imaging: Using denoisers for image recovery." IEEE signal processing magazine 37.1 (2020): 105-116. https://doi.org/10.1109/MSP.2019.2949470 [doi]
6. Roy et al. "Free-running 5D whole-heart MRI using a Gadolinium enhanced Fast-Interrupted Steady-State sequence to evaluate congenital heart disease." In: Proceedings of ISMRM & SMRT Conference & Exhibition (2024) 0285. https://doi.org/10.58530/2024/0285 [doi]
7. Sieber, et al. "Ferumoxytol-enhanced free-running 5D whole-heart CMR at 0.55 T." Journal of Cardiovascular Magnetic Resonance 27 (2025). https://doi.org/10.1016/j.jocmr.2024.101341 [doi]
8. Meyer, et al. "The HeartMagic prospective observational study protocol–characterizing subtypes of heart failure with preserved ejection fraction." medRxiv (2025): 2025-04. https://doi.org/10.1101/2025.04.10.25325567 [doi]
9. Roy, et al. "Free-running cardiac and respiratory motion-resolved 5D whole-heart coronary cardiovascular magnetic resonance angiography in pediatric cardiac patients using ferumoxytol." Journal of Cardiovascular Magnetic Resonance 24.1 (2022): 39. https://doi.org/10.1186/s12968-022-00871-3 [doi]
10. Borsos, et al. "Efficient deep-learning-based reconstruction of Ferumoxytol-enhanced whole-heart 5D cardiac MRI." In: Proceedings of ISMRM & SMRT Conference & Exhibition (2025) 1187. https://doi.org/10.58530/2025/1187 [doi]
11. Kamilov et al. "A plug-and-play priors approach for solving nonlinear imaging inverse problems." IEEE Signal Processing Letters 24.12 (2017): 1872-1876. https://doi.org/10.1109/LSP.2017.2763583 [doi]
12. Comby, et al., "MRI-NUFFT: Doing non-Cartesian MRI has never been easier". Journal of Open Source Software, 10(108), 7743 (2025) https://doi.org/10.21105/joss.07743 [doi]

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