Researchradiomicsmp mriprostate cancerpsma pet
mpMRI-Based AI Improves Preoperative EPE Prediction Accuracy
7.0
A 2025 meta-analysis of 21 studies up to September 2025 found mpMRI-based AI achieved pooled sensitivity 0.77, specificity 0.71, and AUC 0.81 internally, and AUC 0.80 externally for preoperative extraprostatic extension (EPE) prediction in prostate cancer. Radiologists had pooled AUC 0.77, while PSMA PET–based AI showed lower or comparable performance; authors note retrospective designs and heterogeneity, urging larger prospective cohorts.
Key Points
- 1mpMRI-based AI achieved pooled AUC 0.81 internally and 0.80 externally across 21 studies
- 2Demonstrates higher AUC than radiologists (0.81 vs 0.77), indicating improved diagnostic discrimination
- 3Recommends larger, prospective, diverse cohorts and standardization before clinical integration of AI tools
Scoring Rationale
Comprehensive meta-analysis with peer-reviewed data but limited by retrospective studies and high heterogeneity affecting generalizability.
Sources
Public references used for this report.
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