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Journal of magnetic resonance imaging : JMRI · 2023

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.

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Fan Ying, Wang Xinti, Yang Chunna, Chen Huanhuan, Wang Huan, Wang Xiaoyu, Hou Shaoping, Wang Lihua, Luo Yahong, Sha Xianzheng, Yang Huazhe, Yu Tao, Jiang Xiran

Аннотация

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.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты