Evaluation of EGFR mutation status by radiographic characteristics of MRI in NSCLC patients with brain metastasis

Rong HE; Zhimin ZHANG; Xuan HE; He XIAO; Mingying GENG; Songling LI; Yulong ZHANG; Zhengbo WANG; Ge WANG

doi:10.16016/j.1000-5404.201811007

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Evaluation of EGFR mutation status by radiographic characteristics of MRI in NSCLC patients with brain metastasis

Clinical Medicine | 更新时间：2026-01-09

- Evaluation of EGFR mutation status by radiographic characteristics of MRI in NSCLC patients with brain metastasis
- Journal of Third Military Medical University Vol. 41, Issue 5, Pages: 442-447(2019)
- 作者机构：
  
  400042 重庆，陆军军医大学(第三军医大学)大坪医院肿瘤中心
- 作者简介：
- 基金信息：
  
  the General Program of National Natural Science Foundation of China(81572959);the National Natural Science Foundation for Young Scholars of China(81802292)
- DOI：10.16016/j.1000-5404.201811007
  CLC： R730.23;R730.42;R739.41
- Received：02 November 2018，
  
  Revised：2018-12-20，
  
  Published：15 March 2019
- 稿件说明：
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Rong HE, Zhimin ZHANG, Xuan HE, et al. Evaluation of EGFR mutation status by radiographic characteristics of MRI in NSCLC patients with brain metastasis[J]. Journal of Third Military Medical University, 2019, 41(5): 442-447.
DOI：

Rong HE, Zhimin ZHANG, Xuan HE, et al. Evaluation of EGFR mutation status by radiographic characteristics of MRI in NSCLC patients with brain metastasis[J]. Journal of Third Military Medical University, 2019, 41(5): 442-447. DOI： 10.16016/j.1000-5404.201811007.

摘要

目的

分析EGFR突变与临床非小细胞肺癌(non-small cell lung cancer，NSCLC)脑转移磁共振(magnetic resonance imaging，MRI)影像特征的关系，探讨脑转移MRI特征评价EGFR突变的价值。

方法

收集本院2011年1月至2017年1月116例NSCLC脑转移患者临床资料，应用扩增阻滞突变系统方法检测肺癌EGFR突变；回顾性分析患者MRI特征，脑转移瘤个数、大小、部位、强化方式、最大病灶瘤周水肿大小及瘤周水肿指数与EGFR突变相关性。

结果

116例NSCLC脑转移患者中，EGFR突变型50例(43.1%)；与年龄＞60岁患者相比，年龄＜60岁患者19 Del突变比例较高(25.4%

10.2%

=0.040)，但L858R突变比例较低(16.4%

34.7%

=0.023)。在所测的201个脑转移灶中，野生型组瘤周水肿直径显著高于19缺失突变组(中位值: 2.87

1.54

=0.008)；L858R突变组瘤周水肿直径亦显著高于19缺失突变组(中位值: 3.31

1.54

=0.034)。然而瘤周水肿指数仅在野生型组中显著高于19缺失突变组(中位值: 0.979

0.413

=0.012)。构建年龄、瘤周水肿直径和水肿指数的EGFR 19缺失突变预测模型，ROC曲线分析显示该模型预测效能为0.733(95%

=0.625~0.842)。

结论

NSCLC脑转移临床特征及MRI影像可预测EGFR基因突变，为医学上无法进行EGFR突变检测的患者选用EGFR-TKI靶向治疗提供了理论依据。

Abstract

Objective

To investigate the correlation between brain metastatic MRI features and EGFR mutation status in the patient with non-small cell lung cancer (NSCLC) and explore the value of radiographic characteristics of MRI for evaluation of EGFR mutation.

Methods

Clinical data of 116 patients diagnosed with brain metastases from NSCLC admitted in our hospital during January 2011 and January 2017 were collected. Their EGFR mutation status in pulmonary primary tumors and metastatic tissues was detected by amplification block mutation system (ARMS). The features of MR images were analyzed for the correlation of EGFR mutation status with number

size

location of the metastatic brain tumors

strengthen approaches

size of peritumoral brain edema of the largest lesion and peritumoral brain edema index.

Results

Among the 116 patients with brain metastasis of NSCLC

50 patients had EGFR mutation

at a mutation rate of 43.1%. The patients younger than 60 years had significantly higher ratio of EGFR 19Del mutation (25.4%

10.2%

=0.040) and lower ratio of L858R mutation (16.4%

34.7%

=0.023) when compared with those older than 60 years. Of the 201 brain metastatic lesions measured

the diameter of peripheral edema were significantly larger in the patients with EGFR wild type than those harboring EGFR 19Del mutation (median: 2.87

1.54

=0.008)

and in those with L858R mutation than those with 19Del mutation (median: 3.31

1.54

=0.034). However

the index of peripheral edema in the patients with EGFR wild type was obviously higher than those harboring EGFR 19Del mutation (median: 0.979

0.413

=0.012). The predictive model for EGFR 19 deletion mutation was developed based on age

diameter and index of peripheral edema of metastatic tumor

and the capacity of this model was 0.733 (95%

=0.625~0.842) by ROC analysis.

Conclusion

Clinical features and MRI radiographic characteristics of brain metastatic lesions of NSCLC can be used to predict EGFR mutation status. Our study provides theoretical evidence for selecting subpopulation benefiting from EGFR-TKI from the patients who can't detect the mutation of EGFR medically.

关键词

Keywords

references

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