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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


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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