Abstract #4220

An Automatic Abdomen MR-Quantification based on a Simultaneous Multi-Parameter Mapping within 3 Breath-holds and deep-learning Segmentation

Min-xiong Zhou¹, Zheng Qu², Yun Liu³, Haodong Zhong³, Yang Song⁴, Guang Yang³, Jianqi Li³, and Xu Yan⁴

¹Shanghai University of Medicine & Health Sciences, Shanghai, China, ²West China School of Medicine/West China Hospital, Sichuan University, Chengdu, China, ³Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China, ⁴MR Scientific Marketing, Siemens Healthineers, Shanghai, China

Synopsis

For automatic abdomen quantification, a rapid and simultaneous multi-parameter mapping method was evaluated, which could acquire quantitative R1, R2* and PDFF indices within 3-4 breath-holds. By adopting automatic organ segmentation, it could directly generate MR quantitative information for liver, kidney and spleen, which could be potentially used for liver pathology evaluation. The result showed that the multi-parameter sequence could generate high-quality R1, R2* and PDFF maps, with well B1 field correction and fat signal separation.

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