Fast water/fat T2 and PDFF mapping via multiple overlapping‑echo acquisition and deep learning reconstruction

Motivation: Skeletal muscle inflammation/necrosis and fat infiltration are strong indicators of disease activity and progression in many neuromuscular disorders. They can be assessed by muscle T2 relaxometry and water-fat separation techniques, respectively. Goal(s): Develop a method for simultaneous water-fat separation and T2 quantification. Approach: The chemical-shift encoding multiple overlapping-echo detachment (CSE-MOLED) sequence was designed for MRI data acquisition, and synthetic data and deep learning were used for image reconstruction. Results: The experiments showed that accurate T2 maps of water and fat and proton density fat fraction maps (PDFF) can be fast and simultaneously acquired by CSE-MOLED. Impact: A new MRI method is proposed for fast and simultaneous T2 and PDFF mapping, which may help improve the clinical diagnosis of neuromuscular diseases.