^(18)F-FDG PET-CT显像在预测不可切除肺腺癌EGFR突变的价值

Value of ^(18)F-FDG PET-CT imaging in predicting epidermal growth factor receptor mutations in unresectable lung adeocarcinoma

目的探讨氟脱氧葡萄糖F18正电子发射计算机断层显像(^(18)F-FDG PET-CT)在不可切除肺腺癌表皮生长因子受体(EGFR)突变中的预测价值。方法收集2012年4月至2016年5月151例ⅢB期或Ⅳ期的肺腺癌患者的临床资料,所有患者治疗前均行^(18)F-FDG PET-CT检查及EGFR突变检测。采用受试者工作特征(ROC)曲线计算最大标准摄取值(SUV_(max))的截断值,Logistics回归分析影响EGFR突变的预测因素。结果 ROC曲线分析显示,SUV_(max)预测EGFR突变的截断值为10.28。151例不可切除肺腺癌患者中,68例(45.0%)为EGFR突变型。单因素分析结果显示,性别、吸烟、癌胚抗原、SUV_(max)与EGFR突变有关(P<0.05),而CT征象包括空洞、空气支气管征、密度、分叶、胸膜凹陷与EGFR突变无关(P>0.05)。Logistic多因素分析显示,吸烟和SUV_(max)是预测EGFR突变的独立因素(P<0.05)。结论 SUV_(max)是^(18)F-FDG PET-CT预测不可切除肺腺癌EGFR突变的独立因素,在预测EGFR突变中具有一定的参考价值。

Objective To investigate the value of fluorodeoxyglucose F18 positron emission tomography-computed tomography （ ISF-FDG PET-CT） in predicting the presence of epidermal growth factor receptor （EGFR） mutations in unresectable lung adeocareinoma. Methods From April 2012 to May 2016, 151 patients with stage ⅢB or Ⅳ lung adeoearcinoma who underwent JSF-FDG PET- CT and EGFR mutation analysis were enrolled in this study. Receiver-operating characteristic （ROC） curve was used to test the cut-off of maximum standard uptake value（ SUVmax ）. Logistic regression model was employed to analyze the independent predictive factors for EGFR mutatuin. Results ROC curve showed that the cut-off of SUVm^X was 10. 28. Among 151 lung adeocarcinoma patients, 68 （45.0%） were identified with EGFR mutation. Univariate analysis showed that gender, smoking status, CEA and SUVm^xWere all asso- ciated with EGFR mutation （ P〈0. 05 ）. And no significant differences were found regarding partical CT characteristics of lesions including cavitation, air bronchogram, attenuation, lobulation and pleural-indentation （ P〉0. 05）. Logistic multivariate analysis showed that smoking status and SUVmax were the independent factors for predicting EGFR mutation （P〈0. 05 ）. Conclusion SUVmax of ^18F-FDG PET/CT is an independent factor for predicting EGFR mutation in patients with unresectable lung adeocarcinoma, and it has certainly reference value for predicting EGFR mutation.