370-02-015 ISMRM Abstract

Assessing vascular aging using aortic 2D flow MRI in a healthy Swiss cohort

Primary: Cardiovascular - Flow

Secondary: Cardiovascular - Vascular and Vessel Wall

370-02-015 · Vascular and Vessel Wall Imaging · Monday, 11 May, 8:20 AM–9:15 AM · Traditional Posters | Exhibition Hall

Keywords: Analysis/Processing Aging Velocity & Flow Cardiac MRI Aorta

Accepted

Gloria Wolkerstorfer ¹, Stefano Buoso¹, Tobias Kudelka¹, Pia Leuders¹, Max Fuetterer¹, Robert M Manka^1,2,3, Sebastian Kozerke¹

¹Institute for Biomedical Engineering, University Zurich and ETH Zurich, Zurich, Switzerland

²Department of Cardiology, University Heart Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland

³Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland

Presenting Author: Gloria Wolkerstorfer

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References

1. Shah M, de A. Inácio MH, Lu C, et al. Environmental and genetic predictors of human cardiovascular ageing. Nat Commun. 2023;14:4941. doi:10.1038/s41467-023-40566-6 [doi]

2. Ohyama Y, Ambale-Venkatesh B, Noda C, et al. Aortic arch pulse wave velocity assessed by magnetic resonance imaging as a predictor of incident cardiovascular events: The MESA (Multi-Ethnic Study of Atherosclerosis). Hypertension. 2017;70(3):524-530. doi:10.1161/HYPERTENSIONAHA.116.08749 [doi]

3. Redheuil A, Yu WC, Wu CO, et al. Reduced ascending aortic strain and distensibility: earliest manifestations of vascular aging in humans. Hypertension. 2010;55(2):319-326. doi:10.1161/HYPERTENSIONAHA.109.141275 [doi]

4. Jiang Y, Yao T, Paliwal N, et al. Fully automated measurement of aortic pulse wave velocity from routine cardiac MRI studies. Magn Reson Imaging. 2025;122:110442. doi:10.1016/j.mri.2025.110442 [doi]

5. Ramaekers MJFG, Te Kiefte BJC, Adriaans BP, et al. Comprehensive sex-specific and age-dependent analysis of four-dimensional flow cardiovascular magnetic resonance assessed aortic blood flow-related parameters in normal subjects using single-vendor magnetic resonance systems and single-vendor software. J Cardiovasc Magn Reson. 2024;26(2):101083. doi:10.1016/j.jocmr.2024.101083 [doi]

6. Rodgers JL, Jones J, Bolleddu SI, et al. Cardiovascular risks associated with gender and aging. J Cardiovasc Dev Dis. 2019;6(2):19. doi:10.3390/jcdd6020019 [doi]

7. Isensee F, Jaeger PF, Kohl S, et al. nnU-Net: A self-configuring method for deep learning-based biomedical image segmentation. Nat Methods. 2020;17(2):203-211. doi:10.1038/s41592-020-01008-z [doi]

8. Wolkerstorfer G, Buoso S, Kozerke S. Joint magnitude and phase neural network segmentation for cine 2D flow MRI. In: Proceedings of the 33rd Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM); 2025 May 10-15; Honolulu, Hawaii. ISMRM; 2025. Abstract No. 3505.

9. Wentland AL, Wieben O, François CJ, et al. Aortic pulse wave velocity measurements with undersampled 4D flow-sensitive MRI: comparison with 2D and algorithm determination. J Magn Reson Imaging. 2013;37(4):853-859. doi:10.1002/jmri.23877 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/370-02-015