Rosette Cardiac MR Fingerprinting for Simultaneous T1, T2, ... , and Fat Fraction Mapping Using a Multi-Echo Deep Image Prior Reconstruction.

Bibliographic Details
Title: Rosette Cardiac MR Fingerprinting for Simultaneous T1, T2, ... , and Fat Fraction Mapping Using a Multi-Echo Deep Image Prior Reconstruction.
Authors: Cummings E; Radiology, University of Michigan, Ann Arbor, Michigan, USA.; Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA., Cruz G; Radiology, University of Michigan, Ann Arbor, Michigan, USA., Richardson J; Radiology, University of Michigan, Ann Arbor, Michigan, USA., Kaplan S; Radiology, University of Michigan, Ann Arbor, Michigan, USA.; Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA., Hamilton J; Radiology, University of Michigan, Ann Arbor, Michigan, USA.; Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA., Seiberlich N; Radiology, University of Michigan, Ann Arbor, Michigan, USA.; Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.
Source: Magnetic resonance in medicine [Magn Reson Med] 2026 Jun; Vol. 95 (6), pp. 3284-3297. Date of Electronic Publication: 2026 Feb 09.
Publication Type: Journal Article
Language: English
Journal Info: Publisher: Wiley Country of Publication: United States NLM ID: 8505245 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1522-2594 (Electronic) Linking ISSN: 07403194 NLM ISO Abbreviation: Magn Reson Med Subsets: MEDLINE
Imprint Name(s): Publication: 1999- : New York, NY : Wiley
Original Publication: San Diego : Academic Press
MeSH Terms: Heart*/diagnostic imaging , Image Processing, Computer-Assisted*/methods , Magnetic Resonance Imaging*/methods , Adipose Tissue*/diagnostic imaging, Myocardium/pathology ; Image Interpretation, Computer-Assisted/methods ; Humans ; Phantoms, Imaging ; Algorithms ; Female ; Adult ; Male ; Deep Learning ; Reproducibility of Results
Abstract: Purpose: Quantitative mapping of cardiac tissue properties is used clinically in diagnosis and monitoring of a wide variety of cardiac pathologies. Cardiac Magnetic Resonance Fingerprinting (cMRF) enables rapid and simultaneous quantification of multiple parameters in the myocardium from a single scan. In this work, a multi-echo cMRF acquisition is combined with a deep image prior framework to reconstruct cardiac T1, T2, INLINEMATH , and fat fraction maps.
Methods: A 2D, single-breathhold, ECG-gated rosette trajectory cMRF sequence was deployed to sensitize the signal to T1, T2, INLINEMATH , and fat off-resonance effects. Data were processed using a deep image prior reconstruction trained with the cMRF encoding model to generate images consistent with the acquired k-space data. These images were used in curve fitting and pattern matching algorithms to generate T1, T2, INLINEMATH and fat fraction maps. The technique was validated using numerical simulations, standard phantoms, and 28 healthy subjects.
Results: In phantoms, good agreement was observed between the proposed technique and gold-standard reference measurements. In healthy subjects, measurements made with the deep image prior (DIP) reconstruction agreed with clinical cardiac measurements and demonstrated smaller voxel-level variance in a healthy population compared to iterative low-rank and direct matching reconstructions.
Conclusion: The multi-echo cMRF acquisition coupled with a DIP reconstruction enables the simultaneous quantification of T1, T2, INLINEMATH , and fat in the heart and demonstrates good agreement with conventional mapping approaches in phantom and in vivo experiments. Additionally, the DIP reconstruction provides accurate measurements with a lower voxel-level variance compared with direct gridding and iterative low-rank reconstruction methods.
(© 2026 The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)
References: Curr Cardiovasc Imaging Rep. 2010 Apr;3(2):83-91. (PMID: 20401158)
Magn Reson Med. 2021 Jan;85(1):103-119. (PMID: 32720408)
Magn Reson Med. 1999 Nov;42(5):952-62. (PMID: 10542355)
Magn Reson Med. 2017 Apr;77(4):1446-1458. (PMID: 27038043)
J Magn Reson Imaging. 2020 Nov;52(5):1340-1351. (PMID: 31837078)
JACC Cardiovasc Imaging. 2018 Dec;11(12):1837-1853. (PMID: 30522686)
Front Cardiovasc Med. 2022 Jun 23;9:928546. (PMID: 35811730)
J Cardiovasc Magn Reson. 2014 Jan 04;16:2. (PMID: 24387626)
Magn Reson Med. 2020 Dec;84(6):3009-3026. (PMID: 32544278)
J Cardiovasc Magn Reson. 2022 Jun 6;24(1):33. (PMID: 35659266)
J Cardiovasc Magn Reson. 2017 Oct 9;19(1):75. (PMID: 28992817)
NMR Biomed. 2019 Feb;32(2):e4041. (PMID: 30561779)
J Cardiovasc Magn Reson. 2013 May 22;15:41. (PMID: 23697969)
Magn Reson Med. 2007 Jul;58(1):200-205. (PMID: 17659626)
IEEE Trans Med Imaging. 1997 Aug;16(4):372-7. (PMID: 9262995)
Magn Reson Med. 2019 Jan;81(1):486-494. (PMID: 30058096)
Nature. 2013 Mar 14;495(7440):187-92. (PMID: 23486058)
Front Cardiovasc Med. 2022 Sep 20;9:977603. (PMID: 36204572)
Magn Reson Med. 2007 Aug;58(2):354-64. (PMID: 17654578)
Magn Reson Med. 2020 Jun;83(6):2107-2123. (PMID: 31736146)
Magn Reson Med. 2010 Jan;63(1):79-90. (PMID: 19859956)
Radiology. 1984 Oct;153(1):189-94. (PMID: 6089263)
Magn Reson Med. 2001 Feb;45(2):341-5. (PMID: 11180442)
Magn Reson Med. 2010 Apr;63(4):849-57. (PMID: 20373385)
J Magn Reson Imaging. 2020 Dec;52(6):1688-1698. (PMID: 32452088)
Magn Reson Med. 2022 Jun;87(6):2757-2774. (PMID: 35081260)
Radiology. 2023 Jan;306(1):150-159. (PMID: 36040337)
J Cardiovasc Magn Reson. 2015 May 10;17:33. (PMID: 25958014)
J Magn Reson Imaging. 2008 Sep;28(3):543-58. (PMID: 18777528)
J Magn Reson Imaging. 2007 Mar;25(3):644-52. (PMID: 17326087)
IEEE Trans Med Imaging. 2017 Jun;36(6):1326-1336. (PMID: 28207389)
IEEE Trans Med Imaging. 2014 Dec;33(12):2311-22. (PMID: 25029380)
Magn Reson Imaging. 2018 Nov;53:40-51. (PMID: 29964183)
Circulation. 2002 Jan 29;105(4):539-42. (PMID: 11815441)
IEEE Trans Med Imaging. 2008 Jun;27(6):866-73. (PMID: 18541493)
Circ Cardiovasc Imaging. 2018 Aug;11(8):e007372. (PMID: 30354491)
J Magn Reson Imaging. 2022 Jul;56(1):45-62. (PMID: 35396897)
Magn Reson Med. 2020 Nov;84(5):2625-2635. (PMID: 32406125)
Grant Information: Siemens Healthineers; R01HL163991 United States NH NIH HHS; R01HL163030 United States NH NIH HHS; R01HL153034 United States NH NIH HHS
Contributed Indexing: Keywords: MR fingerprinting; cardiac MRI; deep learning reconstruction; quantitative MR
Entry Date(s): Date Created: 20260210 Date Completed: 20260707 Latest Revision: 20260813
Update Code: 20260813
PubMed Central ID: PMC13049243
DOI: 10.1002/mrm.70299
PMID: 41664247
Database: MEDLINE
Be the first to leave a comment!
You must be logged in first