Improved prostate cancer prognostication and treatment selection using artificial intelligence and genomic profiling

Histopathological evaluation of prostate biopsies is critical to the clinical management of men suspected of having prostate cancer.

Despite this importance, the histopathological diagnosis of prostate cancer is associated with a number of challenges: The large number of prostate biopsies being performed worldwide together with the shortage of well-trained uro-pathologists and the high inter- pathologist variability leads to suboptimal prostate cancer diagnostics and prognostication, with risks for under- and overtreatment.My research group has over the last years developed an artificial intelligence (AI) system to assist the pathologists in the evaluation of prostate biopsies, with the overarching aim of solving these problems.

In a recent article in the Lancet Oncology, we demonstrate that the system performs on par with internationally leading uro-pathologist for grading prostate needle biopsies.In this research proposal, we aim to:Perform retrospective international multisite validation of the AI system to assess the AI’s performance across different labs, technical platforms (scanners), and disease subtypesDevelop methods to go beyond today’s grading to improve prognosticationLink the AI system with genomic profiling of tumor tissue to improve treatment selectionPerform prospective validation of the AI system in a randomized diagnostic histopathology trial