Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
363-06-012 ISMRM Abstract

4D bSSFP MRI and 4D flow MRI to assess changes in aortic motion and hemodynamics after root replacement surgery in Marfan

Primary: Cardiovascular - Flow
Secondary: Cardiovascular - Vascular and Vessel Wall
363-06-012 · Hemodynamics and Flow · Monday, 11 May, 5:05 PM–6:00 PM · Digital Posters Row D
Keywords: 4D flow MRI 4D CINE Aorta Marfan
Accepted
Daan Bosshardt1, Renske Merton1, Eric Schrauben1, Aart J Nederveen1, Moniek G Cox2, Danielle Robbers-Vissers1, Maarten Groenink1, Pim van Ooij 1
1Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
2University Medical Center Groningen, Groningen, Netherlands
Presenting Author: Pim van Ooij

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References

1. 1. Silverman, D.I., et al., Life expectancy in the Marfan syndrome. The American Journal of Cardiology, 1995. 75(2): p. 157–160. PMID: 7810492; DOI: 10.1016/s0002-9149(00)80066-1 [doi] [pmid]
2. 2. Narula, N., et al., Risk of Type B Dissection in Marfan Syndrome: The Cornell Aortic Aneurysm Registry. J Am Coll Cardiol, 2023. PMID: 37930285; DOI: 10.1016/j.jacc.2023.08.055 [doi] [pmid]
3. 3. Thomas, R., et al., Elective root replacement increases the risk of type B dissection in patients with Marfan syndrome. The Journal of thoracic and cardiovascular surgery, 2024. PMID: 39326730; DOI: 10.1016/j.jtcvs.2024.09.027 [doi] [pmid]
4. 4. Merton, R., et al., Reproducibility of 3D thoracic aortic displacement from 3D cine balanced SSFP at 3 T without contrast enhancement. Magn Reson Med, 2024. 91(2): p. 466–480. PMID: 37831612; DOI: 10.1002/mrm.29856 [doi] [pmid]
5. 5. Merton, R., et al., Assessing aortic motion with automated 3D cine balanced steady state free precession cardiovascular magnetic resonance segmentation. J Cardiovasc Magn Reson, 2024. 26(2): p. 101089. PMID: 39218220; DOI: 10.1016/j.jocmr.2024.101089 [doi] [pmid]
6. 6. Gottwald, L.M., et al., Pseudo-spiral sampling and compressed sensing reconstruction provides flexibility of temporal resolution in accelerated aortic 4D flow MRI: A comparison with k-t principal component analysis. NMR in biomedicine, 2020. 33(4): p. e4255–e4255. PMID: 31957927; DOI: 10.1002/nbm.4255 [doi] [pmid]
7. 7. Fischer, C., et al., Fully automated background phase correction using M-estimate SAmple consensus (MSAC)-Application to 2D and 4D flow. Magnetic resonance in medicine, 2022. PMID: 35916368; DOI: 10.1002/mrm.29363 [doi] [pmid]
8. 8. Isensee, F., et al., nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature methods, 2021. 18(2): p. 203–211. PMID: 33288961; DOI: 10.1038/s41592-020-01008-z [doi] [pmid]
9. 9. Potters, W.V., et al., Volumetric arterial wall shear stress calculation based on cine phase contrast MRI. Journal of magnetic resonance imaging : JMRI, 2015. 41(2): p. 505–16. PMID: 24436246; DOI: 10.1002/jmri.24560 [doi] [pmid]
10. 10. Schrauben, E.M., et al. A Pulse Wave Velocity Calculation Tool for 4D flow MRI - Data Requirements and Application in Marfan Patients. in ISMRM. 2021.

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http://echo.ismrm.org/p/ISMRM2026/363-06-012