Automated PD-L1 Scoring Using Artificial Intelligence in Head and Neck Squamous Cell Carcinoma.

ABSTRACT: Immune checkpoint inhibitors (ICI) represent a new therapeutic approach in recurrent and metastatic head and neck squamous cell carcinoma (HNSCC). The patient selection for the PD-1/PD-L1 inhibitor therapy is based on the degree of PD-L1 expression in immunohistochemistry reflected by manually determined PD-L1 scores. However, manual scoring shows variability between different investigators and is influenced by cognitive and visual traps and could therefore negatively influence treatment decisions. Automated PD-L1 scoring could facilitate reliable and reproducible results. Our novel approach uses three neural networks sequentially applied for fully automated PD-L1 scoring of all three established PD-L1 scores: tumor proportion score (TPS), combined positive score (CPS) and tumor-infiltrati

SUBMITTER: Puladi B 

PROVIDER: S-EPMC8431396 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature