Development and Validation of a Deep Learning Algorithm for Improving Gleason Scoring of Prostate Cancer

Understand

For prostate cancer patients, the Gleason score is one of the most important prognostic factors, potentially determining treatment independent of the stage.

• However, Gleason scoring is based on subjective microscopic examination of tumor morphology and suffers from poor reproducibility.
• Here we present a deep learning system (DLS) for Gleason scoring whole-slide images of prostatectomies.
• Our system was developed using 112 million pathologist-annotated image patches from 1,226 slides, and evaluated on an independent validation dataset of 331 slides, where the reference standard was established by genitourinary specialist pathologists.