Artificial Intelligence in equivocal prostatic needle biopsies: benign mimics and cancer detection

Equivocal prostatic needle biopsies are diagnostically challenging because minute atypical glandular foci may represent early acinar adenocarcinoma or benign mimics. This review critically examines the role of artificial intelligence (AI) in small-focus cancer detection, recognition of benign mimics, and immunohistochemistry (IHC) triage.

A structured narrative search of PubMed/MEDLINE, Scopus, Web of Science Core Collection, and Google Scholar was conducted from database inception through 15 May 2026. English-language, peer-reviewed diagnostic and validation studies, consensus recommendations, and focused reviews addressing prostate needle-biopsy interpretation, benign mimics, IHC, digital pathology, and clinically relevant AI methods were included.

AI applied to digitized H&E slides can support cancer detection, grading, workflow prioritization, and quality assurance. In equivocal biopsies, its most credible near-term roles are localization of minute suspicious foci and safety-prioritized identification of cases in which IHC might be avoided or requested earlier. However, partial atrophy, adenosis, basal cell hyperplasia, seminal vesicle or ejaculatory duct epithelium, inflammation, treatment effects, and tissue or scanning artefacts may cause clinically important errors. Current evidence is mainly retrospective, and equivocal cases are often defined by previous IHC-ordering practice rather than uniform morphological criteria.

AI may improve the consistency and efficiency of equivocal prostate-biopsy assessment, but it should remain an assistive triage tool. Clinical use requires mimic-enriched external validation, conservative thresholds, interpretable localization, and pathologist-led correlation with morphology and IHC.