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Abstract #3681

Added value of deep learning-accelerated T2-weighted imaging of the bladder onĀ image quality and lesion evaluation

Gumuyang Zhang1, Li Chen1, Hailong Zhou1, Yunna Wang1, Jinxia Zhu1, Marcel Dominik Nickel2, Elisabeth Weiland3, Hao Sun1, and Zhengyu Jin1
1Peking Union Medical College Hospital, Beijing, China, 2Siemens Healthineers Ltd., Beijing, China, 3MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany


This study evaluated deep learning accelerated T2w imaging (T2DL) of the bladder in terms of acquisition time (TA), overall image quality, presence of artifacts, diagnostic confidence, sharpness of lesions, and VI-RADS T2 score compared to a standard T2w (T2S) sequence in twenty-five patients. Two radiologists evaluated the images independently. TA of T2DL was reduced by nearly 50% compared to T2S. Overall image quality and sharpness of lesions were superior in T2DL, while artifacts, diagnostic confidence and T2 score were similar between T2S and T2DL. T2DL has the potential to replace T2S in bladder MR.

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