Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
467-01-005 ISMRM Abstract

High resolution 3D MR fingerprinting for the characterization of respiratory muscles in free breathing conditions

Primary: Musculoskeletal - Muscle
Secondary: Acquisition & Reconstruction - Quantitative Imaging: relaxometry, multi-parametric, MR Fingerprinting, and synthetic MRI
467-01-005 · Quantitative Imaging Beyond the CNS · Tuesday, 12 May, 8:20 AM–9:15 AM · Digital Posters Row H
Keywords: MR Fingerprinting Motion Correction Respiratory Muscles Skeletal Muscle Synthetic MRI
Accepted
Constantin Slioussarenko 1, Thomas Le Tat2, Pierre-Yves Baudin1, Marc Lapert3, Benjamin Marty1
1NMR Laboratory, Institute of Myology, Neuromuscular Investigation Center, Paris, France
2Medical Imaging Department, Ambroise Paré University Hospital, Boulogne-Billancourt, France
3Siemens Healthcare SAS, Courbevoie, France
Presenting Author: Constantin Slioussarenko

Synopsis

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References

1. Marty B, Reyngoudt H, Boisserie JM, et al. Water-fat separation in MR fingerprinting for quantitative monitoring of the skeletal muscle in neuromuscular disorders. Radiology. 2021;300(3):652-660. doi:10.1148/radiol.2021204028 [doi]
2. Marty B, Carlier PG. MR fingerprinting for water T1 and fat fraction quantification in fat infiltrated skeletal muscles. Magn Reson Med. 2020;83(2):621-634. doi:10.1002/mrm.27960 [doi]
3. Finnegan R, Rohwer A, Scoto M, et al. Mortality of symptomatic children with spinal muscular atrophy in the era of disease-modifying therapies. Neuromuscular Disorders. 2025;49:105313. doi:10.1016/j.nmd.2025.105313 [doi]
4. Cruz G, Qi H, Jaubert O, et al. Generalized low‐rank nonrigid motion‐corrected reconstruction for MR fingerprinting. Magnetic Resonance in Med. 2022;87(2):746-763. doi:10.1002/mrm.29027 [doi]
5. Slioussarenko C, Lapert M, Baudin PY, Marty B. Upper-body free-breathing Magnetic Resonance Fingerprinting applied to the quantification of water T1 and fat fraction. Medical Image Analysis. 2025;105:103699. doi:10.1016/j.media.2025.103699 [doi]
6. Slioussarenko C, Baudin P, Marty B. A steady‐state MR fingerprinting sequence optimization framework applied to the fast 3D quantification of fat fraction and water T1 in the thigh muscles. Magnetic Resonance in Med. March 2025:mrm.30490. doi:10.1002/mrm.30490 [doi]
7. Feng L. Golden-Angle Radial MRI: Basics, Advances, and Applications. J Magn Reson Imaging. 2022;56(1):45-62. doi:10.1002/jmri.28187 [doi]
8. Balakrishnan G, Zhao A, Sabuncu MR, Guttag J, Dalca AV. VoxelMorph: A Learning Framework for Deformable Medical Image Registration. IEEE Trans Med Imaging. 2019;38(8):1788-1800. doi:10.1109/TMI.2019.2897538 [doi]
9. Slioussarenko C, Baudin P, Reyngoudt H, Marty B. Bi‐component dictionary matching for MR fingerprinting for efficient quantification of fat fraction and water T1 in skeletal muscle. Magnetic Resonance in Med. March 2024:mrm.29901. doi:10.1002/mrm.29901 [doi]
10. Lopez Kolkovsky AL, Matot B, Baudin PY, et al. Multiparametric aging study across adulthood in the leg through quantitative MR imaging, 1H spectroscopy, and 31P spectroscopy at 3T. Journal of Magnetic Resonance Imaging. April 2024. doi:10.1002/jmri.29368 [doi]
11. Pennati F, Arrigoni F, LoMauro A, et al. Diaphragm Involvement in Duchenne Muscular Dystrophy (DMD): An MRI Study. Magnetic Resonance Imaging. 2020;51(2):461-471. doi:10.1002/jmri.26864 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/467-01-005