Digital image analysis in pathologist-selected regions of interest predicts survival more accurately than whole-slide analysis: a direct comparison study in 153 gastric carcinomas

Automatic quantification of biomarkers such as tumor-infiltrating lymphocytes and PD-L1 is one of the most studied topics in digital pathology image analysis (DIA). However, direct comparison between the DIA of a whole-slide image (WSI) and that of regions of interest (ROIs) chosen by pathologists has not been performed. In this study, we aimed to compare the prognostic value of tumor microenvironment markers CD8 and PD-L1, measured by DIA of WSIs and ROIs. We selected 153 primary gastric cancer tissues and stained them with CD8 and PD-L1. All IHC slides were scanned at x200 magnification and ratios of CD8 and PD-L1 were measured in WSIs and ROIs from the invasive front, within the tumor, and the mucosa. Patients with high CD8 and PD-L1 ratios showed more favorable outcomes compared to those with low ratios. Pathologist-aided DIA predicted the survival of patients more accurately than WSI analysis (CD8,p= 0.025 versusp= 0.068; PD-L1,p= 0.008 versusp= 0.2). Although a high density of CD8+ T cells at the invasive front correlated best with patient survival, CD8 ratio in the mucosa could also predict patient outcome. In conclusion, CD8 and PD-L1 ratios measured by pathologist-aided DIA predicted survival more accurately than WSI analyses and ROIs at the invasive front correlated best with patient outcome.

Automated summary

This study found that the ratios of CD8 and PD-L1 measured by pathologist-aided digital pathology image analysis can more accurately predict patient survival, with regions of interest at the invasive front showing the strongest correlation with patient outcome.