Evaluation Of The Use Of Combined Artificial Intelligence And Pathologist Assessment To Review And Grade Prostate Biopsies (Vol 3, E2023267, 2020)

This diagnostic study evaluates whether the use of an artificial intelligence-based assistive tool is associated with improvements in the grading of prostate core needle biopsies among general pathologists compared with the majority opinion of subspecialists.Question Is the use of an artificial intelligence-based assistive tool associated with improvements in the grading of prostate needle biopsies by pathologists? Findings In this diagnostic study involving 20 pathologists who reviewed 240 prostate biopsies, the use of an artificial intelligence-based assistive tool was associated with significant increases in grading agreement between pathologists and subspecialists, from 70% to 75% across all biopsies and from 72% to 79% for Gleason grade group 1 biopsies. Meaning The study's findings indicated that the use of an artificial intelligence tool may help pathologists grade prostate biopsies more consistently with the opinions of subspecialists.Importance Expert-level artificial intelligence (AI) algorithms for prostate biopsy grading have recently been developed. However, the potential impact of integrating such algorithms into pathologist workflows remains largely unexplored. Objective To evaluate an expert-level AI-based assistive tool when used by pathologists for the grading of prostate biopsies. Design, Setting, and Participants This diagnostic study used a fully crossed multiple-reader, multiple-case design to evaluate an AI-based assistive tool for prostate biopsy grading. Retrospective grading of prostate core needle biopsies from 2 independent medical laboratories in the US was performed between October 2019 and January 2020. A total of 20 general pathologists reviewed 240 prostate core needle biopsies from 240 patients. Each pathologist was randomized to 1 of 2 study cohorts. The 2 cohorts reviewed every case in the opposite modality (with AI assistance vs without AI assistance) to each other, with the modality switching after every 10 cases. After a minimum 4-week washout period for each batch, the pathologists reviewed the cases for a second time using the opposite modality. The pathologist-provided grade group for each biopsy was compared with the majority opinion of urologic pathology subspecialists. Exposure An AI-based assistive tool for Gleason grading of prostate biopsies. Main Outcomes and Measures Agreement between pathologists and subspecialists with and without the use of an AI-based assistive tool for the grading of all prostate biopsies and Gleason grade group 1 biopsies. Results Biopsies from 240 patients (median age, 67 years; range, 39-91 years) with a median prostate-specific antigen level of 6.5 ng/mL (range, 0.6-97.0 ng/mL) were included in the analyses. Artificial intelligence-assisted review by pathologists was associated with a 5.6% increase (95% CI, 3.2%-7.9%; P < .001) in agreement with subspecialists (from 69.7% for unassisted reviews to 75.3% for assisted reviews) across all biopsies and a 6.2% increase (95% CI, 2.7%-9.8%; P = .001) in agreement with subspecialists (from 72.3% for unassisted reviews to 78.5% for assisted reviews) for grade group 1 biopsies. A secondary analysis indicated that AI assistance was also associated with improvements in tumor detection, mean review time, mean self-reported confidence, and interpathologist agreement. Conclusions and Relevance In this study, the use of an AI-based assistive tool for the review of prostate biopsies was associated with improvements in the quality, efficiency, and consistency of cancer detection and grading.