Abstract
Background: Identifying programmed death-ligand-1 (PD-L1) expression is crucial for optimizing treatment strategies involving immune checkpoint inhibitors. However, the role of intratumoral metabolic heterogeneity specifically derived from (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) images in predicting PD-L1 expression in patients with newly diagnosed non-small cell lung cancer (NSCLC) remains unexplored. Here, we investigated the association between FDG PET texture features and PD-L1 expression by retrospectively analyzing the data of patients newly diagnosed with NSCLC who underwent FDG PET/CT scans and PD-L1 immunohistochemical staining before treatment. Methods: Patients were categorized based on their tumor proportion scores (TPSs) into negative-, low-, and high-PD-L1 expression groups. We computed the maximum standardized uptake value and 31 texture features for the primary tumor from PET images and compared differences in parameters among the groups. Results: Of the 83 patients, 12, 45, and 26 were assigned to the negative-, low-, and high-PD-L1 expression groups, respectively. Six specific texture features (low gray-level run emphasis, short-run low gray-level emphasis, long-run high gray-level emphasis, low gray-level zone emphasis, high gray-level zone emphasis, and short-zone low gray-level emphasis) helped distinguish among all possible combinations. Conclusions: Our findings revealed that FDG PET texture features are potential imaging biomarkers for predicting PD-L1 expression in patients newly diagnosed with NSCLC.