Deep-learning computer-aided detection and classification of prostate lesions on biparametric MRI: comparison with expert readers

Clinical validation of deep learning computer-aided detection (DL-CAD) models for the detection and classification of prostate lesions on MRI is urgently needed. A pre-trained DL-CAD algorithm showed fair-to-excellent per-patient performance for detection of prostate lesions on biparametric MRI, with moderate performance for PI-RADS ≥ 3 lesion classification. Identification of false negatives and false positives of prostate cancer detection DL-CAD algorithms is important for future improvement and clinical deployment. A DL-CAD-based prostate cancer detection algorithm with high NPV may reduce interpretation time.