Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
351-02-013 / 351-02-013 ISMRM Abstract

Multi-Vendor Multi-Site Prospective Evaluation of SuperMAP Deep-Learning Reconstruction for Accelerated T1ρ and T2 Mappings

Primary: Acquisition & Reconstruction - Quantitative Imaging: spine, MSK, others
Secondary: Musculoskeletal - Osteoarthritis
351-02-013 · MSK: Everything, Everywhere, and All at Once · Monday, 11 May, 1:50 PM–3:26 PM · Power Pitch Theatre 1
351-02-013 · MSK: Everything, Everywhere, and All at Once · Monday, 11 May, 1:50 PM–3:26 PM · Power Pitch Theatre 1
Keywords: Deep learning reconstruction Knee cartilage Multi-vendor Quantitative T1rho and T2 Mappings SuperMAP
Accepted
Xinyan Jian 1,2,3, Zhiyuan Zhang1,2,3, Jeehun Kim1,2, Ruiying Liu4, Koushani Chakrabarty5, Richard Lartey1,2, Carl Winalski1,2,6, Mingrui Yang1,2, Qi Peng7, Michael A Samaan8, Peter A Hardy9, Jing Liu10, Thomas M Link10, Lei (Leslie) Ying5,11, Xiaojuan Li1,2,6
1Program of Advanced Musculoskeletal Imaging (PAMI), Cleveland Clinic, Cleveland, United States of America
2Department of Biomedical Engineering, Cleveland Clinic Research, Cleveland Clinic, Cleveland, United States of America
3Department of Biomedical Engineering, Case Western Reserve University, Cleveland, United States of America
4Department of Biomedical Informatics, Emory University, Atlanta, United States of America
5Department of Biomedical Engineering, University at Buffalo, Buffalo, United States of America
6Department of Diagnostic Radiology, Diagnostics Institute, Cleveland Clinic, Cleveland, United States of America
7Department of Radiology, Albert Einstein College of Medicine, Bronx, United States of America
8Department of Kinesiology & Health Promotion, University of Kentucky, Lexington, United States of America
9Department of Radiology, University of Kentucky, Lexington, United States of America
10Department of Radiology and Biomedical Imaging, University Of California, San Francisco (UCSF), United States of America
11Department of Electrical Engineering, University at Buffalo, Buffalo, United States of America
Presenting Author: Xinyan Jian

Synopsis

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References

1. Martel-Pelletier J, Barr AJ, Cicuttini FM, et al. Osteoarthritis. Nat Rev Dis Primers. 2016;2:16072. Published 2016 Oct 13. doi:10.1038/nrdp.2016.72 [doi]
2. Bannuru RR, Schmid CH, Kent DM, Vaysbrot EE, Wong JB, McAlindon TE. Comparative effectiveness of pharmacologic interventions for knee osteoarthritis: a systematic review and network meta-analysis. Ann Intern Med. 2015;162(1):46-54. doi:10.7326/M14-1231 [doi]
3. Li X, Ma CB, Link TM, Castillo DD, Blumenkrantz G, Lozano J, Carballido-Gamio J, Ries M, Majumdar S. In vivo T1ρ and T2 mapping of articular cartilage in osteoarthritis of the knee using 3 T MRI. Osteoarthritis Cartilage. 2007;15(7):789-797. doi:10.1016/j.joca.2007.01.011 [doi]
4. Kim, J et al. Retrospective and prospective accelerated T1ρ/T2 mapping with Compressed Sensing: high resolution T1ρ mapping and simultaneous T1ρ/T2 mapping. ISMRM 2023
5. Li H, Yang M, Kim JH, Zhang C, Liu R, Huang P, Liang D, Zhang X, Li X, Ying L. SuperMAP: Deep Ultrafast MR Relaxometry with Joint Spatiotemporal Undersampling. Magn Reson Med. 2022;89(1):64–76. doi:10.1002/mrm.29411 [doi]
6. Li X, Han ET, Busse RF, Majumdar S. In vivo T(1ρ) mapping in cartilage using 3D magnetization-prepared angle-modulated partitioned k-space spoiled gradient echo snapshots (3D MAPSS). Magnetic resonance in medicine. 2008;59(2):298-307. Epub 2008/01/30. doi: 10.1002/mrm.21414. PubMed PMID: 18228578; PubMed Central PMCID: PMCPMC2724872. [doi] [pmid]
7. Kim J, Mamoto K, Lartey R, et al. Multi-vendor multi-site T1ρ and T2 quantification of knee cartilage. Osteoarthritis Cartilage. 2020;28(12):1539-1550. doi:10.1016/j.joca.2020.07.005 [doi]
8. Zibetti MVW, Sharafi A, Otazo R, Regatte RR. Accelerating 3D- T1ρ mapping of cartilage using compressed sensing with different sparse and low rank models. Magnetic resonance in medicine. 2018;80(4):1475-91. Epub 2018/02/27. doi: 10.1002/mrm.27138. [doi]
9. Gaj S, Yang M, Nakamura K, Li X. Automated cartilage and meniscus segmentation of knee MRI with conditional generative adversarial networks. Magn Reson Med. 2020;84(1):437-449.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/351-02-013