<p>Diagnostic and Predictive Values of <sup>18</sup>F-FDG PET/CT Metabolic Parameters in <em>EGFR</em>-Mutated Advanced Lung Adenocarcinoma</p>
Il Ki Hong, Jeongmi Lee, In Kyoung Hwang, Seung Sook Paik, Chanwoo Kim, Seung Hyeun Lee
Abstract
Purpose: The clinical implications of the metabolic parameters of 18 F-fluorodeoxyglucose positron emission tomography-computed tomography ( 18 F-FDG PET/CT) in epidermal growth factor receptor ( EGFR) -mutated lung cancer are not fully understood. The aim of this study was to evaluate the diagnostic and prognostic utility of the parameters in EGFR -mutated lung cancer patients. Patients and Methods: We retrospectively enrolled 134 patients with advanced lung adenocarcinoma (72 EGFR -negative and 62 EGFR- positive). We evaluated the correlation between EGFR mutational status and the maximum standardized uptake value (SUVmax), as well as the associations between treatment outcomes in EGFR -mutated patients and various metabolic parameters of primary tumors. For the best predictive parameters, we calculated the metabolic tumor volume (MTV) and total lesion glycolysis (TLG) using two SUV cutoffs: 1.5 (MTV 1.5 , TLG 1.5 ) and 2.5 (MTV 2.5 , TLG 2.5 ). Results: Mean SUVmax was lower for EGFR -mutated tumors compared with EGFR wild-type (6.11 vs 10.41, p < 0.001) tumors. Low SUVmax was significantly associated with positive EGFR mutation (odds ratio = 1.74). Multivariate analysis for survival demonstrated that high MTV 1.5 , TLG 1.5 , MTV 2.5 , and TLG 2.5 were independently associated with shorter progression-free survival (PFS) and overall survival (OS), and the highest hazard ratios were found in TLG 1.5 (3.26 for PFS and 4.62 for OS). Conclusion: SUVmax may be predictive for EGFR mutational status, and MTV and TLG of primary tumors may be promising prognostic parameters; 18 F-FDG PET/CT has potential utility for the risk stratification of EGFR -mutated patients treated with targeted therapy. Keywords: lung cancer, 18 F-fluorodeoxyglucose positron emission tomography-computed tomography, epidermal growth factor receptor mutation, survival, metabolic parameters