5D reconstruction exploiting spatial-motion-echo sparsity for accelerated free-breathing liver R2*/QSM

Motivation: Conventional compressed sensing-based 4D respiratory motion-resolved image reconstruction techniques are limited in their ability to utilize correlations between echoes for free-breathing 3D multi-echo liver MRI, which is inherently a 5D imaging problem. Goal(s): Develop a 5D reconstruction algorithm to jointly exploit correlations between echoes and motion states. Approach: 5D reconstruction with sparsity constraints along the motion and echo dimensions was developed to reconstruct retrospectively undersampled k-space data and compared with the 4D reconstruction on one volunteer and one patient. Results: Compared to the 4D reconstruction, the proposed reconstruction showed comparable image quality to the reference (undersampling factor=1) and more reliable liver R2*/QSM values. Impact: Using the proposed 5D image reconstruction, the scan time of free-breathing 3D multi-echo liver MRI for R2*/QSM can be reduced while preserving image quality and providing reliable R2*/QSM values.