Detection of  Clinically Significant Prostate Cancer: Incremental Value of Deep Learning to PI-RADS V2

Deep learning has great potential in medical imaging. 168 patients underwent 3T mpMRI of prostate before mpMR-targeted biopsies plus systematic sampling. Two radiologists from two separate institutions, by using the Prostate Imaging Reporting and Data System (PI-RADS) V2 and a multimodal convolutional neural networks (CNN)-based deep learning, independently assessed prostate MRI examinations. Histopathologic findings were used as the reference standard. In detecting csPCa, both reviewers had significantly higher AUCs using CNN-based deep learning. Reviewer 2 benefited much more from CNN-based deep learning than did reviewer 1. Combined PI-RADS with CNN-based deep learning contribute significant incremental value in the detection of csPCa.