Abstract #3681

Added value of deep learning-accelerated T2-weighted imaging of the bladder on 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

Synopsis

This study evaluated deep learning accelerated T2w imaging (T2_DL) 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 (T2_S) sequence in twenty-five patients. Two radiologists evaluated the images independently. TA of T2_DL was reduced by nearly 50% compared to T2_S. Overall image quality and sharpness of lesions were superior in T2_DL, while artifacts, diagnostic confidence and T2 score were similar between T2_S and T2_DL. T2_DL has the potential to replace T2_S in bladder MR.

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