An evaluation of artificial intelligence assisted prostate biopsy reporting in the Articulate Pro study
Prospective evidence on clinical utility of AI in histopathology is limited. We conducted a prospective study across three National Health Service specialist centres in England to evaluate a commercially available AI system for assistance in prostate biopsy reporting. Of 1613 cases, 1049 were reported with AI-assistance. Endpoints evaluated diagnostic impact, clinical impact and workflow. Staged AI assistance (second-read) prompted case review and changed the initial diagnosis or Grade Group of 21/386(5.4%) patients, 5 of these (1.3%) potentially affecting clinical management. AI-assisted workflows showed significantly reduced mean turnaround time with concurrent-read compared to unassisted-read by 30.1 h (p < 0.0001) at one site with significant reductions in cases requiring immunohistochemistry in all sites (Odds Ratios 0.50,0.43,0.33, p < 0.0001, p = 0.01, p = 0.001). This first prospective, multi-centric evaluation demonstrates AI can enhance diagnostic accuracy, shorten turnaround times and reduce unnecessary testing. Scaled across the NHS, such improvements could improve patient care, deliver faster diagnoses and optimise laboratory efficiency, supporting adoption.
Authors
- Richard Scheffer
- Lisa Browning (ORCID: https://orcid.org/0000-0002-1542-5357)
- Abhisek Ghosh (ORCID: https://orcid.org/0000-0001-6719-6632)
- Richard T. Colling (ORCID: https://orcid.org/0000-0001-6344-9081)
- Clare Dunstan
- I. Danial
- Davina Hewitt
- Anastasios Chatzitolios
- Rob Procter (ORCID: https://orcid.org/0000-0001-8059-5224)
- Nasullah Khalid Alham (ORCID: https://orcid.org/0000-0003-1479-3251)
- Monica Dolton
- Kieron White (ORCID: https://orcid.org/0000-0001-6954-1831)
- M A Horton
- Stefano Malacrino (ORCID: https://orcid.org/0000-0003-1237-8572)
- Ewart Stanislaus
- James Crofts
- B. P. Sinha
- Andrew Protheroe
- Kate Hutton
- Pallavi Borkar
- Pelvender Gill
- Nasir Rajpoot
- Jonathan Aning
- Nahida Banu
- Jacqueline Birks
- Clare Verrill
- Juan A. Retamero
- Samir Al-Hyassat
- Rosalin Cooper
- Jon Oxley
- Chuer Zhang
- Leila Bibi Ahmed
- Richard J. Bryant
- David J. Snead
Institutions
- Turing Institute (GB)
- North Bristol NHS Trust (GB)
- American International Group (United States) (US)
- University Hospital Coventry (GB)
- Nuffield Orthopaedic Centre (GB)
- University Hospitals Coventry and Warwickshire NHS Trust (GB)
- University of Bristol (GB)
- University of Warwick (GB)
- University of Oxford (GB)
- Oxford BioMedica (United Kingdom) (GB)
- Science Oxford (GB)
- Oxford University Hospitals NHS Trust (GB)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2026-05-22
- DOI
- https://doi.org/10.1038/s41746-026-02592-8
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- UK Research and Innovation
- Department of Health and Social Care