Abstract #3526

Sparsely Sampled Cardiac Diffusion Tensor Imaging Using Phase-Corrected Joint Low-Rank and Sparsity Constraints

Sen Ma^1,2, Christopher T Nguyen^2,3, Anthony G Christodoulou², Sang-Eun Lee^2,4,5,6, Hyuk-Jae Chang^4,5,6, and Debiao Li^1,2

¹Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, ²Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, ³Cardiovascular Research Center, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States, ⁴Severance Cardiovascular Hospital, Seoul, Republic of Korea, ⁵Yonsei-Cedars-Sinai Integrative Cardiovascular Imaging Research Center, Yonsei University, Seoul, Republic of Korea, ⁶College of Medicine, Yonsei University, Seoul, Republic of Korea

We propose to sparsely sample in vivo cardiac diffusion tensor imaging (CDTI) by combining a phase-corrected low-rank model and sparsity constraint. The proposed method was evaluated on 7 hypertrophic cardiomyopathy patients. Helix angle and mean diffusivity maps were compared against employing single constraint, and changes in helix angle transmurality and mean diffusivity were evaluated using Wilcoxon signed rank test to statistically determine the highest achievable acceleration factors preserving CDTI measurements with no significant difference. Our framework shows promise in accelerating acquisition window while preserving myofiber architecture features, and may allow higher spatial resolution or shorter temporal footprint in the future.

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