Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists
This addresses the issue of inconsistent prostate cancer grading for pathologists, showing incremental improvement through AI synergy.
The study tackled the problem of observer variability in Gleason grading of prostate biopsies by investigating AI assistance, finding that it significantly increased agreement with an expert reference standard from a kappa of 0.799 to 0.872.
While the Gleason score is the most important prognostic marker for prostate cancer patients, it suffers from significant observer variability. Artificial Intelligence (AI) systems, based on deep learning, have proven to achieve pathologist-level performance at Gleason grading. However, the performance of such systems can degrade in the presence of artifacts, foreign tissue, or other anomalies. Pathologists integrating their expertise with feedback from an AI system could result in a synergy that outperforms both the individual pathologist and the system. Despite the hype around AI assistance, existing literature on this topic within the pathology domain is limited. We investigated the value of AI assistance for grading prostate biopsies. A panel of fourteen observers graded 160 biopsies with and without AI assistance. Using AI, the agreement of the panel with an expert reference standard significantly increased (quadratically weighted Cohen's kappa, 0.799 vs 0.872; p=0.018). Our results show the added value of AI systems for Gleason grading, but more importantly, show the benefits of pathologist-AI synergy.