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中华肺部疾病杂志(电子版) ›› 2023, Vol. 16 ›› Issue (01) : 51 -54. doi: 10.3877/cma.j.issn.1674-6902.2023.01.011

临床研究

非小细胞肺癌EGFR突变状态与CT特征的相关性
汪涛1, 朱浩雨1, 卜青松1, 胡磊1, 王文娟1, 方阮1, 刘啸峰1,()   
  1. 1. 247000 池州,池州市人民医院医学影像科
  • 收稿日期:2022-07-12 出版日期:2023-02-25
  • 通信作者: 刘啸峰

Correlation between EGFR mutation status and CT features in non­small cell lung cancer

Tao Wang1, Haoyu Zhu1, Qingsong Bu1   

  • Received:2022-07-12 Published:2023-02-25
引用本文:

汪涛, 朱浩雨, 卜青松, 胡磊, 王文娟, 方阮, 刘啸峰. 非小细胞肺癌EGFR突变状态与CT特征的相关性[J/OL]. 中华肺部疾病杂志(电子版), 2023, 16(01): 51-54.

Tao Wang, Haoyu Zhu, Qingsong Bu. Correlation between EGFR mutation status and CT features in non­small cell lung cancer[J/OL]. Chinese Journal of Lung Diseases(Electronic Edition), 2023, 16(01): 51-54.

目的

分析计算机断层扫描(CT)纹理特征与非小细胞肺癌(non-small cell lung cancer, NSCLC)表皮生长因素受体(EGFR)突变状态的相关性。

方法

选择2018年1月至2022年1月我院收治的73例NSCLC患者为对象,根据EGFR突变状态分为突变组40例和未突变组33例。筛选NSCLC EGFR突变状态非0系数的CT纹理特征,构建Lasso-Logistics回归模型,绘制受试者工作特征曲线(ROC)分析诊断效能。

结果

共筛选出能量、熵、均匀度、对比度4个非0系数的CT纹理特征及气管空气征、胸膜凹陷征2个CT形态特征。ROC曲线分析显示Lasso-Logistics回归模型诊断NSCLCEGFR突变状态的AUC为0.879(95%CI 0.872~0.926),敏感度90.00%,特异度82.50%。

结论

CT纹理特征气管空气征、胸膜凹陷征、能量、熵、均匀度、对比度是NSCLC患者EGFR突变状态的诊断因素,建立的诊断模型能为临床识别NSCLC EGFR突变的高危患者提供参考。

表1 两组临床资料比较[n(%)]
表2 两组患者CT特征比较(±s)
图1 CT图像特征集合。注:十倍交叉验证法调节参数λ将模型中二项式偏差降到最小后筛选
图2 特征系数收敛图
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