Correlation between EGFR mutation status and F18‐fluorodeoxyglucose positron emission tomography‐computed tomography image features in lung adenocarcinoma. Issue 4 (18th February 2019)

• Record Type: Journal Article
• Authors: Zhu, Lei; Yin, Guotao; Chen, Wei; Li, Xiaofeng; Yu, Xiaozhou; Zhu, Xiang; Jiang, Wei; Jia, Chaoyang; Chen, Peihe; Zhang, Yufan; Lu, Di; Yu, Lijuan; Li, Xubin; Xu, Wengui
• Is Part Of: Thoracic cancer. Volume 10:Issue 4(2019)
• Page Start: 659
• Page End: 664
• Publication Date: 2019-02-18
• Subjects: 18F‐FDG -- EGFR mutation -- lung cancer -- PET/CT; Chest -- Cancer -- Periodicals; Chest -- Cancer -- Treatment -- Periodicals; Chest -- Surgery -- Periodicals; 616.99494005
• DOI: 10.1111/1759-7714.12981
• Languages: English
• ISSNs: 1759-7706

Abstract

Abstract : Background: The purpose of this study was to investigate an association between EGFR mutation status and 18 F‐fluorodeoxyglucose positron emission tomography‐computed tomography ( 18 F‐FDG PET‐CT) image features in lung adenocarcinoma. Methods: Retrospective analysis of the data of 139 patients with lung adenocarcinoma confirmed by surgical pathology who underwent preoperative 18 F‐FDG PET‐CT was conducted. Correlations between EGFR mutation status, clinical characteristics, and PET‐CT parameters, including the maximum standardized uptake value (SUVmax), the mean of the SUV (SUVmean), the peak of the SUV (SUVpeak) of the primary tumor, and the ratio of SUVmax between the primary tumor and the mediastinal blood pool (SUVratio), were statistically analyzed. Multivariate logistic regression analysis was performed to identify predictors of EGFR mutation. Receiver operating characteristic curves of statistical quantitative parameters were compared. Results: EGFR mutations were detected in 74 (53.2%) of the 139 lung adenocarcinomas and were more frequent in non‐smoking patients. Univariate analysis showed that the SUVmax, SUVmean, SUVpeak, and SUVratio were lower in EGFR ‐mutated than in wild‐type tumors. The receiver operating characteristic curves showed no significant differences between their diagnostic efficiencies. Multivariate logistic regression analysis showed that being a never smoker was an independent predictor of EGFR mutation. Conclusion: Quantitative parameters based on 18 F‐FDG PET‐CT have modest power to predict the presence of EGFR mutation in lung adenocarcinoma; however, when compared to smoking history, they are not good or significant predictive factors.