May 28, 2021—Nearly 50,000 cases of prostate cancer are diagnosed each year in the UK. During the diagnostic process, men with suspected prostate cancer undergo a biopsy, which is analyzed by pathology services. There are over 60,000 prostate biopsies performed in the UK annually, and with increasing demand and a shortage of pathologists, tools that help streamline this workflow could save time and speed diagnoses.
To confidently diagnose prostate cancer, pathologists need to identify several tissue architecture and cellular cues. All biopsies are stained with Hematoxylin & Eosin (H&E), which allows the pathologist to study the size and shape (morphology) of the cells and tissue. However, in 25-50% of cases, H&E staining alone does not provide sufficient evidence for a diagnosis, requiring immunohistochemistry (IHC) to further study cellular features.
One bottleneck in the current pathology workflow is the requirement for a pathologist to review the H&E-stained biopsies to determine which require IHC. To address this need, a team led by Ludwig Oxford’s Jens Rittscher and his University of Oxford colleagues Richard Colling, Clare Verrill and Andrea Chatrian used prostate biopsies annotated by pathologists at Oxford University Hospitals to train an artificial intelligence (AI) tool to detect tissue regions with ambiguous morphology and decide which cases needed IHC.
They report in Modern Pathology that the tool agreed with the pathologist’s review in 81% of cases on average. By enabling automated request of IHC based on the AI tool results, the pathologist would only need to review the case once all necessary staining had been carried out. This workflow improvement is estimated to save on average 11 minutes of pathologist time for each case, which scales up to 165 pathologist hours for 1000 prostate biopsies needing IHC.
The tool will now be developed and validated further using pathology data from different locations to account for variation in IHC requests between pathologist teams and centers.