Abstract #3445

Synergistic Combination of Golden-angle Radial Sampling and Dual-Subspace Modeling for Rapid and Robust High Spatiotemporal Resolution MRA

Zhifeng Chen^1,2 and Lirong Yan^1,2

¹USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, ²Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States

Synopsis

This study proposes a rapid and robust ASL-based time-resolved MRA technique with high spatiotemporal resolution termed Dual-Subspace MRA (DS-MRA), which employs subspace modeling from both temporal and control/label dimensions as sparsity constraints to improve the robustness of image reconstruction with under-sampled golden-angle radial dynamic MRA. The performance of DS-MRA was compared with conventional iGRASP and 5-dimensional GRASP. Our preliminary data suggests that DS-MRA outperforms conventional GRASP reconstructions with less residual streaking artifacts and noise, especially at higher acceleration rates.

This abstract and the presentation materials are available to members only; a login is required.

Join Here