Clinical advantages in providing artificial intelligence-assisted prostate cancer diagnosis: A pilot study
Prostate cancer is a prevalent male malignancy, with increasing incidence rates placing significant diagnostic burdens on pathology services worldwide. Artificial intelligence (AI) is emerging as a promising aid in enhancing diagnostic efficiency and accuracy. This study evaluates the clinical benefits of AI-assisted prostate biopsy (PB) diagnosis, with Paige Prostate tool, compared to non-AI-assisted PB diagnosis, focusing on its predictive accuracy for features in radical prostatectomy (RP) specimens. A retrospective analysis included 55 patients divided into two cohorts: one with non-AI-assisted PB diagnosis (n = 25) and another with AI-assisted PB diagnosis (n = 30). Pathological assessments recorded tumor size, Gleason score, Grade Group, and perineural invasion. The correlation between PB and RP results was analyzed, with statistical significance set at p < 0.05. AI-assisted PB diagnosis showed faster reporting times by 24 hours, enhancing workflow efficiency. AI assistance improved the correlation of tumor size between PB and RP, showing a substantial agreement (R=0.646, p < 0.001) compared to non-AI (R=0.479, p = 0.015). Gleason Score concordance increased by 13 % in the AI-assisted group, achieving 73.3 % versus 60 % in the non-AI-assisted group. This small pilot study suggests that AI-assisted PB diagnosis appears to enhance efficiency and accuracy in the diagnosis of prostate cancer, a finding to be confirmed with further studies.
Authors
- Antonia Syrnioti (ORCID: https://orcid.org/0000-0002-9232-6715)
- Iván Rienda (ORCID: https://orcid.org/0000-0002-3254-7372)
- Catarina Eloy (ORCID: https://orcid.org/0000-0001-7642-1280)
- António Polónia (ORCID: https://orcid.org/0000-0001-8312-1681)
- A.V. Asaturova (ORCID: https://orcid.org/0000-0001-8739-5209)
- João Correia Pinto (ORCID: https://orcid.org/0000-0003-1993-1705)
- R. Prisco
Institutions
- Fernando Pessoa University (PT)
- Universidade do Porto (PT)
- Aristotle University of Thessaloniki (GR)
- CUF Porto Hospital (PT)
- National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I.Kulakov of the Ministry of Healthcare of the Russian Federation (RU)
Publication Details
- Journal
- Pathology - Research and Practice
- Published
- 2025-05-09
- DOI
- https://doi.org/10.1016/j.prp.2025.156007
- Citations
- 2
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 4.96