Automated MRI system for clinically significant prostate cancer detection development validation and real-world implementation.

ABSTRACT: Prostate MRI enables detection of clinically significant prostate cancer (csPCa), yet variability in PI-RADS scoring limits reproducibility and throughput. Here, we report the development and validation of an automated MRI-based decision aid (ProAI) that estimates patient-level risk of csPCa from biparametric MRI and supports routine reporting. Training, internal validation, and external testing spanned 7849 examinations across six centres and two public datasets. On pooled external tests, the system achieved a patient-level AUC of 0.93 (95% CI, 0.91-0.95), comparable to PI-RADS while improving inter-case consistency. In a multi-reader, multi-case study involving nine clinicians, assistance increased accuracy from 0.80 to 0.86 and reduced reading time. Prospective implementation in 1978 co

SUBMITTER: Wu H 

PROVIDER: S-EPMC12749140 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature