Figure 2.

Effects of region-specific analysis and tumour-to-tissue ratio on classifier performance

(A) Example tissue section, whole tumour annotation, and luminal surface annotation (ie, a virtual biopsy). (B) Microsatellite instability and EBV prediction scores for whole-slide images, tumour only, and virtual biopsy samples in the TUM, KCCH, and AUGSB cohorts. Prediction performance of the model for microsatellite instability (C) and EBV status (D) according to tumour-to-tissue ratio. Patients were stratified by the ratio between tumour-contianing area and total tissue area as follows: low was a tumour-to-tissue ratio of 0–0·33, medium was a ratio of 0·34–0·66, and high was a ratio of 0·66–1. AUROC=area under the receiver operating curve. AUGSB=samples from University Hospital Augsberg, Germany. BERN=samples from University of Bern, Switzerland. CLASSIC=samples from the CLASSIC trial in South Korea. EBV=Epstein-Barr virus. ITALIAN=samples from University of Siena, Italy. KCCH=samples from Kanagawa Cancer Center Hospital, Japan. LEEDS=samples from Leeds Teaching Hospitals NHS Trust, UK. MAGIC=samples from the MAGIC trial in the UK. TCGA=samples from The Cancer Genome Atlas. TUM=samples from Technical University Munich, Germany.