666-02-007 ISMRM Abstract

Reducing Undersampling Artifacts in MRF – Iterative Reconstruction and Optimized Acquisition

Primary: Acquisition & Reconstruction - Quantitative Imaging: relaxometry, multi-parametric, MR Fingerprinting, and synthetic MRI

Secondary: Acquisition & Reconstruction - Artifacts and Correction Strategies

666-02-007 · Multiparametric Quantitative MR Methods · Thursday, 14 May, 9:25 AM–10:20 AM · Digital Posters Row G

Keywords: MR Fingerprinting Quantitative Imaging Iterative reconstruction MRI sequence optimization

Accepted

Jona R Sippel ¹, Tim Höpfner^1,2, Maximilian Gram^3,4, Herbert Köstler¹

¹Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany

²Institute of Mathematics, University of Würzburg, Würzburg, Germany

³Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany

⁴Experimental Physics 5, University of Würzburg, Würzburg, Germany

Presenting Author: Jona R Sippel

Synopsis

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References

1. Ma D, Gulani V, Seiberlich N, Liu K, Sunshine JL, Duerk JL, Griswold MA. Magnetic resonance fingerprinting. Nature. 2013 Mar 14;495(7440):187-92. doi: 10.1038/nature11971. PMID: 23486058; PMCID: PMC3602925. [doi] [pmid]

2. B. Zhao, J. P. Haldar, K. Setsompop and L. L. Wald, "Optimal experiment design for magnetic resonance fingerprinting," 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 2016, pp. 453-456, doi: 10.1109/EMBC.2016.7590737. [doi]

3. Stolk, C. C., & Sbrizzi, A. (2019). Understanding the Combined Effect of k-Space Undersampling and Transient States Excitation in MR Fingerprinting Reconstructions. IEEE Transactions on Medical Imaging, 38(10), 2445-2455. https://doi.org/10.1109/TMI.2019.2900585 [doi]

4. Heesterbeek DGJ, Koolstra K, van Osch MJP, van Gijzen MB, Vos FM, Nagtegaal MA. Mitigating undersampling errors in MR fingerprinting by sequence optimization. Magn Reson Med. 2023; 89: 2076-2087. doi:10.1002/mrm.29554 [doi]

5. Tran-Gia, J., Stäb, D., Wech, T., Hahn, D. and Köstler, H. (2013), Model-based Acceleration of Parameter mapping (MAP) for saturation prepared radially acquired data. Magn. Reson. Med., 70: 1524-1534. https://doi.org/10.1002/mrm.24600 [doi]

6. Bibiano, J., Kleineisel, J., Schad, O., Weng, A. M., Köstler, H., & Slawig, A. (2024). No-wait inversion—a novel model for T1 mapping from inversion recovery measurements without the waiting times. Frontiers in Physics, 11(1299522). doi:10.3389/fphy.2023.1299522 [doi]

7. BART Toolbox for Computational Magnetic Resonance Imaging, DOI: 10.5281/zenodo.592960 [doi]

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http://echo.ismrm.org/p/ISMRM2026/666-02-007