Histopathology-based Artificial Intelligence Algorithms for the Prediction of Prostate Cancer Metastasis After Radical Prostatectomy
EUROPEAN UROLOGY, cilt.89, sa.2, ss.140-148, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 89 Sayı: 2
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.eururo.2025.08.018
- Dergi Adı: EUROPEAN UROLOGY
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, EMBASE, Gender Studies Database, MEDLINE, Academic Search Ultimate (EBSCO)
- Sayfa Sayıları: ss.140-148
- Gazi Üniversitesi Adresli: Evet
Özet
Background and objective: Multimodal artificial intelligence (AI) algorithms have been validated to predict prostate cancer (PCa) metastasis using combined histopathology and clinical-pathologic parameters in clinical trial cohorts. Here, we used purely histopathology-based AI algorithms to predict the probability of lethal PCa in surgically treated population-or hospital-based cohorts, comparing with genomic classifiers and standard clinical risk tools. Methods: This study included representative whole slide images (WSIs) of radical prostatectomy (RP) and needle biopsy samples, or tissue microarrays (TMAs) constructed from RP specimens across five surgically treated PCa cohorts. A concatenated feature-based classification system using histopathologic data from each image generated an AI risk score for metastasis. Key findings and limitations: In Cox models for time to metastasis, an AI risk score from prostatectomy WSIs showed similar performance (C-index: 0.81-0.85) to the Decipher or Prolaris genomic classifiers (C-index: 0.72-0.80) in testing cohorts. A modified TMA AI score analyzing 1 mm2 of prostatectomy tumor tissue from a nationwide study of 1351 patients had a C-index of 0.71 (95% confidence interval [CI]: 0.67-0.75). Ina needle biopsy cohort followed for metastasis after prostatectomy, the TMA AI score had a Cindex of 0.74 (95% CI: 0.70-0.79), and models combined with the Cancer of the