Using 18F-FDG PET/CT to Predict PD-L1 Expression in NSCLC via Metabolic Tumor Heterogeneity.

Abstract

Objectives: The purpose of this study is to evaluate the effectiveness of using F-18 FDG PET/CT metabolic heterogeneity to assess the PD-L1 expression in primary tumors.

Methods: Data from 103 NSCLC patients undergoing F-18 FDG PET/CT was collected. PD-L1 expression was verified via biopsy or surgical specimens. The coefficient of variation (COV) assessed metabolic heterogeneity of the primary tumor. ROC curves evaluated the predictive potential of metabolic metrics and defined thresholds. Logistic regression examined predictors of PD-L1 expression.

Results: The study included 103 patients (mean age: 63.65 ± 9.28 years), of whom 60 were male. 64 patients were PD-L1 expression positive, while 39 were negative. COV was significantly higher in the PD-L1 positive group (Z = -2.529, P = 0.011),while no significant differences noted in otherparameters between the groups (P > 0.05 for all). The optimal cutoff value was proposed as 28.9, with sensitivity and specificity of 46.9% (34.3%-59.8%)and 82.1%(66.5%-92.5%), respectively (AUC: 0.649(0.549, 0.741)) whichcan more effectively identify PD-L1 negative patients. Other metabolic parameters are less effective than COV.(AUV < 0.6). In addition, COV-defined metabolic heterogeneity outperformed other metabolic parameters in predicting PD-L1 expression (p = 0.049) and emerged as an independent predictor.

Conclusion: Metabolic heterogeneity, described by the COV of the primary lesion, is a marker for predicting PD-L1 expression in NSCLC patients. Therefore, the COV of the primary tumor may complement conventional imaging in providing immunohistochemical information before biopsy.

Advances in knowledge: COV of the primary tumor can predict PD-L1 expression, potentially complementing conventional imaging for immunohistochemical information prior to biopsy.