Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
361-06-007 ISMRM Abstract

In vivo repeatability of fast whole-brain relaxometry with MR-STAT

Primary: Contrast Mechanisms - Relaxometry
Secondary: Acquisition & Reconstruction - Quantitative Imaging: relaxometry, multi-parametric, MR Fingerprinting, and synthetic MRI
361-06-007 · Quantitative Imaging: Head and Neck II · Monday, 11 May, 5:05 PM–6:00 PM · Digital Posters Row B
Keywords: Relaxometry Quantitative MRI MR-STAT Repeatability
Accepted
Martin B Schilder 1, Elon D Wallert2, Stefano Mandija3, Oscar van der Heide3, Edwin Versteeg3, Cornelis A van den Berg3, Elsmarieke van de Giessen2, Alessandro A Sbrizzi3
1Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, Netherlands
2Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
3Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, UMC Utrecht, Utrecht, Netherlands
Presenting Author: Martin B Schilder

Synopsis

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References

1. Sbrizzi A, van der Heide O, Cloos M, et al. Fast quantitative MRI as a nonlinear tomography problem. Magn Reson Imaging. 2018;46:56-63. doi:10.1016/j.mri.2017.10.015 [doi]
2. Schilder MB, Mandija S, Jacobs SM, et al. Fast whole brain relaxometry with Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) at 3 T: a retrospective cohort study. Magnetic Resonance Materials in Physics, Biology and Medicine. 2025;38(2):333-345. doi:10.1007/s10334-025-01237-3 [doi]
3. van der Heide O, van den Berg CAT, Sbrizzi A. GPU‐accelerated Bloch simulations and MR‐STAT reconstructions using the Julia programming language. Magn Reson Med. 2024;92(2):618-630. doi:10.1002/mrm.30074 [doi]
4. Kleinloog JPD, Mandija S, D’Agata F, et al. Synthetic MRI with Magnetic Resonance Spin TomogrAphy in Time-Domain (MR-STAT): Results from a Prospective Cross-Sectional Clinical Trial. Journal of Magnetic Resonance Imaging. 2023;57(5):1451-1461. doi:https://doi.org/10.1002/jmri.28425 [doi]
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7. Schilder MB, Wallert ED, Mandija S, et al. Detecting dopaminergic degeneration in clinically uncertain parkinsonian syndrome patients using fast MR-STAT relaxometry. In: Proc. Intl. Soc. Mag. Reson. Med. 33 (2025). 2025.
8. Schilder MB, Mandija S, Jacobs SM, et al. Automatic detection and measurement of WM lesions in MS patients using MR-STAT and a self-supervised bivariate Gaussian probabilistic model. In: Proc. Intl. Soc. Mag. Reson. Med. 32 (2024). 2024.
9. Fuderer M, van der Heide O, Liu H, van den Berg CAT, Sbrizzi A. Efficient performance analysis and optimization of transient‐state sequences for multiparametric magnetic resonance imaging. NMR Biomed. 2023;36(3). doi:10.1002/nbm.4864 [doi]
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12. Nunez-Gonzalez L, Kotek G, Gómez PA, et al. Accuracy and repeatability of QRAPMASTER and MRF-vFA. Magn Reson Imaging. 2021;83:196-207. doi:https://doi.org/10.1016/j.mri.2021.09.004 [doi]
13. Buonincontri G, Biagi L, Retico A, et al. Multi-site repeatability and reproducibility of MR fingerprinting of the healthy brain at 1.5 and 3.0 T. Neuroimage. 2019;195:362-372. doi:10.1016/j.neuroimage.2019.03.047 [doi]
14. Liu H, Versteeg E, Fuderer M, et al. Time‐efficient, high‐resolution 3T whole‐brain relaxometry using Cartesian 3D MR Spin TomogrAphy in Time‐Domain (MR‐STAT) with cerebrospinal fluid suppression. Magn Reson Med. 2025;93(5):2008-2019. doi:10.1002/mrm.30384 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/361-06-007