Validation of diagnostic artificial intelligence models for prostate pathology in a Middle Eastern cohort
Artificial intelligence (AI) for pathology is accelerating cancer diagnostics. For global adoption, studies in currently under-represented populations - where the potential gains from AI may also be greatest - are needed. We present the first external validation study in a Middle Eastern setting, focusing on diagnosis and Gleason grading of prostate cancer. We digitised 339 prostate glass slides from Kurdistan, Iraq, representing a consecutive series of 185 patients from 2013 to 2024. Each slide was scanned on three digital pathology scanners, generating 1,017 whole-slide images. Task-specific and foundation AI models demonstrated AI-pathologist grading concordance similar to pathologist-pathologist concordance (Cohen's quadratically weighted kappa 0.801 vs. 0.799). Cross-scanner concordance was high (kappa > 0.90) for all AI models across three scanners. The demonstrated robust performance on a low-cost compact scanner could enable validation studies in non-digitalised settings and cost-effective AI adoption in laboratories with limited sample volumes. The publicly shared dataset supports further research to facilitate broader adoption of AI pathology.
Authors
- Abdulbasit K. Faeq Al-Talabani
- Nita Mulliqi (ORCID: https://orcid.org/0009-0002-7448-4960)
- Abdulbasit K. Al‐Talabani (ORCID: https://orcid.org/0000-0001-6328-204X)
- Han N. Mohammed Fadhl (ORCID: https://orcid.org/0000-0001-7035-1920)
- Kimmo Kartasalo (ORCID: https://orcid.org/0000-0002-9470-4783)
- Kelvin Szolnoky (ORCID: https://orcid.org/0000-0002-0554-1872)
- Anders Blilie (ORCID: https://orcid.org/0009-0002-9546-5443)
- Julia Anna Mielcarz
- Peshawa J. Muhammad Ali (ORCID: https://orcid.org/0000-0002-0471-5172)
- Saman S. Abdulla (ORCID: https://orcid.org/0000-0002-9091-0184)
- Xiaoyi Ji (ORCID: https://orcid.org/0009-0005-8431-7906)
- Navin Vincent (ORCID: https://orcid.org/0000-0003-2894-6319)
Institutions
- University of Turku (FI)
- Hawler Medical University (IQ)
- Stavanger University Hospital (NO)
- Science for Life Laboratory (SE)
- Karolinska Institutet (SE)
- University of Kurdistan Hewler (IQ)
- Koya University (IQ)
- University of Sulaimani (IQ)
- University of Stavanger (NO)
Publication Details
- Journal
- Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin
- Published
- 2026-10-10
- DOI
- https://doi.org/10.1007/s00428-026-04742-5
- Citations
- 1
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 3.67
Funders
- Cancerfonden
- Karolinska Institutet
- Knut och Alice Wallenbergs Stiftelse
- Vetenskapsrådet
- Instrumentariumin Tiedesäätiö
- Science for Life Laboratory
- National Supercomputer Centre, Linköpings Universitet