An evaluation of artificial intelligence assisted prostate biopsy reporting in the Articulate Pro study

Read full text
Authors: Lisa Browning, Richard T. Colling, Jon Oxley, Jacqueline Birks, Nasullah Khalid Alham, Stefano Malacrino, Chuer Zhang, Abhisek Ghosh, Rosalin Cooper, Monica Dolton, M A Horton, Juan A. Retamero
+22 more Andrew Protheroe, Leila Bibi Ahmed, Nahida Banu, Anastasios Chatzitolios, Irini Danial, Samir Al-Hyassat, B. P. Sinha, Pallavi Borkar, Pelvender Gill, Richard J. Bryant, Jonathan Aning, Kieron White, Richard Scheffer, Ewart Stanislaus, James Crofts, David J. Snead, Nasir Rajpoot, Kate Hutton, Davina Hewitt, Clare Dunstan, Rob Procter, Clare Verrill
Cited by: 1
References: 43

Abstract

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.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education AI in cancer detection Prostate Cancer Diagnosis and Treatment

Publication details

Journal / source
npj Digital Medicine
Publisher
Springer Science and Business Media LLC
Volume
9
Issue
1
Publication date
22 May 2026
Language
EN