||CADESS is a decision support system under development for the prognostication of prostate cancer from tissue samples. CADESS bases its algorithms on consensus-graded tissue data.
During 2015 thirteen internationally prominent uropathologists remotely graded 650 small images from whole mount sections according to Gleason. We observed similar intra- and interobserver grading variations as seen in other studies. But unlike studies based on entire biopsies or whole mounts, each image in our study contained only one dominant morphological pattern, allowing identification of patterns that cause large discrepancies. In September this year the pathologists met in Uppsala to establish a consensus for these patterns.
We describe the consensus-grading process, with particular focus on morphological patterns that caused in the greatest grading discrepancy and how these discrepancies were resolved.