Motivation: Abdominal T2-weighted imaging, T2water mapping, and PDFF quantification are important biomarkers for subjects with fatty liver disease. Abdominal acquisitions are inefficient due to respiratory motion. Goal(s): To develop a respiratory triggered approach to obtain full abdominal fat-suppressed T2-weighted images, T2water, and PDFF simultaneously in a clinically feasible scan-time. Approach: Combining RADGRASE with respiratory triggering and deep learning reconstruction to obtain anatomical images, T2water maps, and PDFF maps from highly accelerated free-breathing acquisitions in human subjects. Results: RADGRASE provided high quality anatomical images and accurate T2water and PDFF measurements compared to reference values. Acceleration via deep learning maintained image quality and parameter map accuracy. Impact: Abdominal T2-weighted imaging, T2water, and PDFF quantification are important biomarkers for subjects with fatty liver disease. RADGRASE with respiratory triggering provided accurate measurements of these biomarkers through the whole abdomen in an accelerated (~ 3 min) free-breathing acquisition.
Toner et al. (Tue,) studied this question.