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Abstract #0270

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

Qing Lin1, Weikun Chen1, Taishan Kang2, Xinran Chen1, Liangjie Lin3, Zhong Chen1, Shuhui Cai1, and Congbo Cai1
1Xiamen University, Xiamen, China, 2Magnetic Resonance Center, Zhongshan Hospital Afflicated to Xiamen University, Xiamen, China, 3Clinical & Technical Support, Philips Healthcare, Beijing, China

Synopsis

Keywords: Quantitative Imaging, Fat, T2 mapping

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.

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Keywords