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Abstract #5196

A multicenter external validation study of the role of AI algorithm in detecting and localizing clinically significant prostate cancer on mpMRI

Zhaonan Sun1, Xiaoying Wang2, and Kexin Wang3
1Department of Radiology, Peking University First Hospital, Beijing, China, 2Department of Radiology, Peking University First Hospital, Beijing, China, 3School of Basic Medical Sciences, Capital Medical University, Beijing, China

Synopsis

Keywords: Machine Learning/Artificial Intelligence, ProstateA total of 557 mpMRI data were retrospectively collected from three hospitals to build an external validation dataset, with 245 csPCa cases and 312 non-csPCa cases. The csPCa lesions were annotated based on pathology records by two experienced radiologists. AI algorithms were used to automatically detect and localize the suspicious csPCa areas on the T2WI and ADC maps. The metrics of sensitivity, specificity, and accuracy were used to evaluate the diagnostic efficacy of the AI algorithms at the lesion level, the sextant level, and the patient level.

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