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Abstract #4115

Classification of Cancer at Prostate MRI: Artificial Intelligence versus Clinical Assessment and Human-Machine Synergy

guiqin LIU1, Guangyu Wu1, yongming Dai2, Ke Xue2, and Shu Liao3
1Radiology, Renji Hospital´╝îShanghai Jiaotong University School of Medicine, Shanghai, China, 2United Imaing Healthcare, Shanghai, China, 3Shanghai United Imaging Intelligence Co. Ltd, Shanghai, China

The interpretation of mpMRI is limited by expertise required and interobserver variability. Here we present an AI model, with ordinary accuracy level for diagnosing prostate cancer, the remarkable of false negative and sensitivity could help to reduce missed-diagnosis of PCa especially csPCa. To assess its performance in clinical setting, we curated internal and external validation, and performance of radiologists, AI model, human-machine synergy were compared, although AI performed suboptimal, the human-led synergy method performed equivalent to clinical assessment with improved consistency, which can serve as a comparison standard to more complex deep learning and synergy approaches in the future.

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