Artificial Intelligence–Enabled Imaging for Predicting Preoperative Extraprostatic Extension in Prostate Cancer: Systematic Review and Meta-Analysis
mpMRI-based AI demonstrated improved diagnostic performance for preoperative prediction of EPE in prostate cancer compared to conventional radiological assessment, achieving higher AUC. However, PSMA PET-based AI models currently offer no significant advantage over either mpMRI-based AI or radiologists. Limitations include the retrospective design and high heterogeneity, which may introduce bias and affect generalizability. Larger, more diverse cohorts are essential for confirming these findings and optimizing the integration of AI in clinical practice.
Authors
- Yiting Qi (ORCID: https://orcid.org/0009-0002-6835-8183)
- Haowen Chen (ORCID: https://orcid.org/0009-0004-2553-4559)
- Xi Wang (ORCID: https://orcid.org/0009-0005-7247-4891)
- Jia Li (ORCID: https://orcid.org/0000-0001-7430-8583)
- Xin Zhang (ORCID: https://orcid.org/0009-0005-5128-9734)
Institutions
- Zunyi Medical University (CN)
- Zhuhai People's Hospital (CN)
- Kiang Wu Nursing College of Macau (CN)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-12-09
- DOI
- https://doi.org/10.2196/80981
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00