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Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer
Published on: July 21, 2018
Correlation between F-18 FDG PET/CT-derived metabolic parameters and PD-L1 expression in non-small cell lung cancer
S Kesim1, F Ozulker1, G Gul Gecmen2
1Department of Nuclear Medicine, University of Health Sciences, Kartal Dr. Lutfi Kirdar City Hospital, Istanbul, Turkey.
Objectives:
Programmed death-ligand 1 (PD-L1) expression serves as a critical biomarker for selecting patients eligible for treatment with immune checkpoint inhibitors. Herein, we investigated the association between PD-L1 expression and various FDG PET/CT-derived metabolic parameters in patients with non-small cell lung cancer (NSCLC).
Materials And Methods:
This retrospective study included 81 NSCLC patients who underwent pre-treatment F-18 FDG PET/CT imaging and histopathological evaluation of PD-L1 expression. PD-L1 tumour proportion score (TPS) was determined using the SP263 immunohistochemical assay. PD-L1 positivity was defined as TPS ≥ 1%. Quantitative PET/CT parameters-SUVmax, SUVmean, SULpeak, SULmax, metabolic tumor volume (MTV), total lesion glycolysis (TLG), and heterogeneity indices (coefficient of variation [COV] and SUV-based heterogeneity index [HI])-were analyzed in relation to PD-L1 TPS.
Results:
PD-L1 positivity was identified in 30 patients (37%). Although SUVmax, SUVmean, SULpeak, and SULmax values tended to be higher in PD-L1-positive patients, these differences were not statistically significant. Conversely, MTV and TLG were higher in the PD-L1-negative group. Among all parameters, HI was significantly elevated in the PD-L1-positive group (P = .031), and remained significant across PD-L1 expression strata (P = .037). In metastatic patients, HI and COV showed significant positive correlation with PD-L1 expression (r = 0.34 and 0.33, respectively). ROC analysis identified a HI cut-off of 1.59 to predict PD-L1 positivity with 90% sensitivity and 50% specificity (AUC = 0.674).
Conclusions:
Tumor heterogeneity indices, particularly HI and COV derived from FDG PET/CT, demonstrated stronger predictive value for PD-L1 expression than conventional metabolic parameters. These findings suggest that metabolic heterogeneity may serve as a useful noninvasive imaging biomarker for guiding immunotherapy in NSCLC.
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