Abstract #0140

Accelerated Cardiac Diffusion Tensor Imaging Using a Joint Low-Rank and Sparsity Constraint

Sen Ma^1,2, Christopher Nguyen¹, Anthony Christodoulou^1,3, Daniel Luthringer⁴, Jon Kobashigawa³, and Debiao Li^1,2

¹Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, ²Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, ³Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, ⁴Department of Pathology, Cedars-Sinai Medical Center, Los Angeles, CA, United States

We present an image reconstruction technique to accelerate cardiac diffusion tensor imaging by jointly applying a low-rank and spatial sparsity constraint. We evaluated four acquisition schemes at different undersampling levels on 9 ex vivo diseased human heart, evaluating the reconstruction quality based on the resulting helix angle (HA) maps and helix angle transmurality (HAT) values. A Wilcoxon signed rank test was performed to statistically evaluate changes in HAT to determine the highest achievable acceleration factor for each acquisition scheme. Our framework shows promise in greatly reducing scan time while preserving the fiber architecture features of heart failure.

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