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Abstract #2396

Radiomics based on multiparametric magnetic resonance imaging to predict extraprostatic extension of prostate cancer

Lili Xu1, Gumuyang Zhang1, Lun Zhao2, Li Mao2, Xiuli Li2, Weigang Yan3, Yu Xiao4, Jing Lei1, Zhengyu Jin1, and Hao Sun1
1Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China, 2Deepwise AI Lab, Beijing, China, 3Department of Urology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China, 4Department of Pathology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China

The preoperative prediction of EPE has a profound impact on treatment decision making, however, it still remains challenging presently. In this study, we compared the radiomics signatures extracted from different MR sequences to diagnose EPE. The radiomics signature based on DWI showed better performance for EPE prediction among mpMRI sequences. The radiomics model based on DWI, T2WI and DCE images was demonstrated feasible for the prediction of EPE. But the added value of clinical variables to the radiomics model was not prominent.

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