临床肿瘤学杂志

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18F-FDG PET-CT显像在预测不可切除肺腺癌EGFR突变的价值

汤泊1,丁重阳2,李天女1   

  1. 1 223600 江苏宿迁 沭阳县中医院影像科2 210029 南京医科大学第一附属医院核医学科
  • 收稿日期:2017-02-16 修回日期:2017-04-17 出版日期:2017-06-30 发布日期:2017-06-30
  • 通讯作者: 丁重阳

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

TANG Bo,DING Chongyang,LI Tiannv.   

  1. Department of Image,Shuyang Hospital of Traditional Chinese Medicine, Shuyang 223600, China
  • Received:2017-02-16 Revised:2017-04-17 Online:2017-06-30 Published:2017-06-30
  • Contact: DING Chongyang

摘要: 目的 探讨氟脱氧葡萄糖F18正电子发射计算机断层显像(18F-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18F-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(SUVmax)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,SUVmax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、SUVmax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SUVmax是预测EGFR突变的独立因素(P<0.05)。结论 SUVmax是18F-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。

Abstract: Objective To investigate the value of fluorodeoxyglucose F18 positron emission tomography-computed tomography (18F-FDG PET-CT) in predicting the presence of epidermal growth factor receptor (EGFR) mutations in unresectable lung adeocarcinoma. Methods From April 2012 to May 2016, 151 patients with stage ⅢB or Ⅳ lung adeocarcinoma who underwent 18F-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 SUVmax 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 SUVmaxwere all associated 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.

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