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Abstract #4324

Deep Image Prior Denoising of Cardiac FISP-MRF T1, T2 and M0 Maps at 0.55T

Zhongnan Liu1, Imran Rashid2, Prachi Agarwal3, Nicole Seiberlich3,4, Liyue Shen1, and Jesse Hamilton3,4
1Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, United States, 2Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, United States, 3Department of Radiology, University of Michigan, Ann Arbor, MI, United States, 4Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States

Synopsis

Keywords: Myocardium, Low-Field MRI, MR Fingerprinting; T1 mapping; T2 mapping; Myocardium; Tissue characterization

Motivation: 0.55T scanners offer several potential advantages for quantitative myocardial tissue characterization. However, a challenge at low field is the reduced SNR, which can lead to decreased precision that may compromise the utility of mapping at 0.55T.

Goal(s): To combine cardiac MR Fingerprinting (cMRF) with a Deep Image Prior (DIP) to improve mapping precision at 0.55T.

Approach: cMRF data were acquired in phantoms and 10 healthy subjects at 0.55T, with maps compared using low-rank and DIP reconstruction techniques.

Results: cMRF at 0.55T yielded high-quality maps in all subjects (mean T1 678 +/-24ms, T2 50.4 +/-5.8ms), with DIP yielding improved precision than the low-rank reconstruction.

Impact: This study demonstrates the feasibility of FISP-based cardiac MR Fingerprinting for T1, T2, and M0 mapping at 0.55T using a Deep Image Prior reconstruction to suppress noise at low field, outperforming a low-rank MRF reconstruction method.

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Keywords