Comparison of data-driven approaches for gradient delay corrections in PDFF mapping using a radial stack-of-stars acquisition

Motivation: Data-driven eddy current compensation would allow corrections to be performed retroactively on scanned data without the need for calibration scans or direct measurements during the scan. Goal(s): This work aims to evaluate data-based eddy current correction techniques for self-gated free-breathing radial SOS sequences in the liver. Approach: PDFF liver maps were obtained using free-breathing radial SoS scans from four volunteers and the eddy current corrected results were compared to a clinically established breath-hold cartesian sequence. Results: Data-driven eddy current corrections improve PDFF map homogeneity for radial SoS sequences with the RING method outperforming the spoke alignment. Impact: Prior studies analyzed various data-driven eddy current corrections in radial imaging, but never quantitatively assessed in vivo PDFF maps. This work is the first to apply multiple data-driven correction techniques in vivo, comparing them to clinically established breath-hold cartesian sequences.