Brain‐Tumor Interface‐Based MRI Radiomics Models to Determine EGFR Mutation, Response to EGFR‐TKI and T790M Resistance Mutation in Non‐Small Cell Lung Carcinoma Brain Metastasis

医学 T790米 肺癌 突变 肿瘤科 接收机工作特性 内科学 表皮生长因子受体 病理 癌症研究 癌症 吉非替尼 基因 生物 生物化学
作者
Ying Fan,Xinti Wang,Chunna Yang,Huanhuan Chen,Huan Wang,Xiaoyu Wang,Shaoping Hou,Lihua Wang,Yahong Luo,Xianzheng Sha,Huazhe Yang,Tao Yu,Xiran Jiang
出处
期刊:Journal of Magnetic Resonance Imaging [Wiley]
卷期号:58 (6): 1838-1847 被引量:18
标识
DOI:10.1002/jmri.28751
摘要

BACKGROUND: Preoperative assessment of epidermal growth factor receptor (EGFR) status, response to EGFR-tyrosine kinase inhibitors (TKI) and development of T790M mutation in non-small cell lung carcinoma (NSCLC) patients with brain metastases (BM) is important for clinical decision-making, while previous studies were only based on the whole BM. PURPOSE: To investigate values of brain-to-tumor interface (BTI) for determining the EGFR mutation, response to EGFR-TKI and T790M mutation. STUDY TYPE: Retrospective. POPULATION: Two hundred thirty patients from Hospital 1 (primary cohort) and 80 patients from Hospital 2 (external validation cohort) with BM and histological diagnosis of primary NSCLC, and with known EGFR status (biopsy) and T790M mutation status (gene sequencing). FIELD STRENGTH/SEQUENCE: Contrast-enhanced T1-weighted (T1CE) and T2-weighted (T2W) fast spin echo sequences at 3.0T MRI. ASSESSMENT: Treatment response to EGFR-TKI therapy was determined by the Response Evaluation Criteria in Solid Tumors. Radiomics features were extracted from the 4 mm thickness BTI and selected by least shrinkage and selection operator regression. The selected BTI features and volume of peritumoral edema (VPE) were combined to construct models using logistic regression. STATISTICAL TESTS: The performance of each radiomics model was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). RESULTS: A total of 7, 3, and 3 features were strongly associated with the EGFR mutation status, response to EGFR-TKI and T790M mutation status, respectively. The developed models combining BTI features and VPE can improve the performance than those based on BTI features alone, generating AUCs of 0.814, 0.730, and 0.774 for determining the EGFR mutation, response to EGFR-TKI and T790M mutation, respectively, in the external validation cohort. DATA CONCLUSION: BTI features and VPE were associated with the EGFR mutation status, response to EGFR-TKI and T790M mutation status in NSCLC patients with BM. EVIDENCE LEVEL: 3 Technical Efficacy: Stage 2.
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