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Abstract #4351

Deep learning-accelerated T2-weighted imaging of the female pelvis: reduced acquisition times and improved image quality

Jing Ren1, Yonglan He1, Chong Liu1, Shifei Liu 1, Jinxia Zhu2, Marcel Dominik Nickel3, Zhengyu Jin1, and Huadan Xue1
1Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China, 2MR collaboration, Siemens Healthineers Ltd., Beijing, China, 3MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany


Novel deep learning (DL) reconstruction methods may accelerate female pelvis MRI protocols keeping high image quality. The value of a novel DL reconstruction of T2-weighted (T2DLR) turbo spin-echo (TSE) sequences for female pelvis MRI in three orthogonal planes was evaluated. We evaluated examination times, image quality, and lesion conspicuity of benign uterine disease. The T2DLR quantitative parameters remained similar or were significantly improved compared with that of standard T2 TSE (T2S), allowing for a 62.7% reduction in acquisition times. Applying this novel T2DLR sequence achieved better image quality and shorter acquisition time than T2S.

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