Influence of Artificial Intelligence Assistance on Gleason Grading and Prostate Cancer Detection by Uropathologists...

Current practices in prostate cancer diagnosis rely heavily on Gleason grading by uropathologists. While AI tools have shown promise in controlled settings, their real-world impact remains unclear. Prior research has established that Gleason grading influences treatment decisions, but variability exists between pathologists. No prior work had resolved how AI assistance affects diagnostic outcomes in daily clinical settings. This gap motivated the need to evaluate AI's influence on grading accuracy and confidence. The study aimed to address uncertainties about AI's role in urological pathology. By focusing on real-world application, the research sought to bridge the gap between theoretical AI benefits and practical implementation. The study also aimed to quantify how often AI alters diagnostic decisions. Understanding these effects is crucial for integrating AI into clinical workflows.

The study aimed to assess how AI assistance influences Gleason grading and prostate cancer detection in routine urological pathology. The specific problem addressed was the lack of evidence on AI's real-world impact in this field. The motivation was to determine whether AI tools can improve diagnostic accuracy and confidence in daily practice. The research focused on evaluating changes in Gleason grading and tumor detection rates. The study also aimed to measure shifts in diagnostic confidence among uropathologists. By comparing AI-assisted and unassisted evaluations, the study sought to quantify AI's influence. The goal was to provide evidence for the practical utility of AI in this clinical context. The findings could inform future guidelines on integrating AI into diagnostic workflows.

The study used a prospective multicenter design involving two Dutch hospitals. A total of 130 consecutive prostate biopsy cases were analyzed. Each case was reviewed in three steps: first by a pathologist without AI, then by AI (Paige Prostate Suite), and finally by the pathologist with AI assistance. The assessments focused on Gleason grading and tumor detection. The International Society of Urological Pathology grade groups (GG) were also evaluated. Agreement between AI-assisted and unassisted evaluations was measured. Diagnostic confidence levels were recorded at each step. The study tracked changes in grading and detection outcomes across all three evaluation stages.

Tumor was detected in 64.3% of biopsy entries, covering all GG categories. In 16.5% of cases, AI-assisted grading differed from unassisted grading. Of these discrepancies, 80.0% involved a one-point GG change, and 20.0% involved a two-point change. Notably, 36.7% of discrepancies were between GG1 and GG2. Tumor detection agreement was 98.6%, with differences limited to GG1 tumors. Uropathologists' confidence increased from confident to high confidence with AI assistance. The most significant changes occurred in low-grade tumors, which typically do not require treatment. These findings suggest AI may improve diagnostic accuracy in certain cases.

The study found that AI assistance influenced Gleason grading in 16.5% of entries. Changes in grading were primarily one or two points, with clinically relevant shifts between GG1 and GG2 in 36.7% of cases. Differences in tumor detection were limited to low-grade (GG1) tumors, which usually do not require active treatment. AI support increased uropathologists' diagnostic confidence. The authors propose that AI assistance may be a valuable tool in improving patient management for prostate cancer. These findings suggest AI could enhance diagnostic accuracy in real-world settings. The study highlights the potential of AI to support pathologists in daily practice. The authors suggest that AI could help reduce variability in Gleason grading assessments.