Computer-aided image analysis for PD-L1 assessment in canine urothelial carcinoma

The programmed cell death-1/programmed cell death ligand-1 (PD-1/PD-L1) pathway contributes to tumor immune evasion and represents an emerging topic in canine oncology. In canine urothelial carcinoma (UC), PD-L1 immunohistochemical evaluation may be challenging because of staining heterogeneity, and only membranous labeling is considered specific. This study assessed the feasibility of a computer-aided image analysis workflow incorporating supervised classification tools for PD-L1 scoring on whole-slide images of canine UC. Immunohistochemistry was performed using a validated anti-PD-L1 antibody. Digital slides were analyzed with QuPath software using object- and pixel-based classifiers to identify PD-L1-positive tumor and immune cells and to calculate the combined positive score (CPS). Ten of 48 tumors (21%) showed PD-L1 expression. CPS values obtained by computer-aided analysis correlated with manual counts. Interobserver agreement for manual CPS assessment among multiple pathologists was good (intraclass correlation coefficient = 0.795). These results indicate that computer-aided whole-slide analysis is a feasible supportive approach for PD-L1 scoring in canine UC under pathologist supervision.