MRI radiomics for predicting intracranial progression in non-small-cell lung cancer patients with brain metastases treated with epidermal growth factor receptor tyrosine kinase inhibitors

被引:2
作者
Qu, J. [1 ,2 ,3 ,4 ]
Zhang, T. [5 ]
Zhang, X. [6 ]
Zhang, W. [1 ,2 ,3 ,4 ]
Li, Y. [1 ,2 ,3 ,4 ]
Gong, Q. [1 ,2 ,3 ,4 ]
Yao, L. [1 ,2 ,3 ,4 ]
Lui, S. [1 ,2 ,3 ,4 ]
机构
[1] Sichuan Univ, Dept Radiol, West China Hosp, 37 Guoxue Alley, Chengdu 610041, Peoples R China
[2] Sichuan Univ, Funct & Mol Imaging Key Lab Sichuan Prov, West China Hosp, Chengdu, Peoples R China
[3] Sichuan Univ, Huaxi MR Res Ctr HMRRC, West China Hosp, Chengdu, Peoples R China
[4] Chinese Acad Med Sci, Res Unit Psychoradiol, Chengdu, Peoples R China
[5] Univ Elect Sci & Technol China, Dept Comp Sci & Engn, Chengdu, Peoples R China
[6] GE Healthcare, Pharmaceut Diagnost Team, Life Sci, Beijing, Peoples R China
关键词
SURVIVAL; TUMORS; RESISTANCE; MUTATIONS;
D O I
10.1016/j.crad.2024.01.005
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
AIM: To identify clinical and magnetic resonance imaging (MRI) radiomics predictors specialised for intracranial progression (IP) after first -line epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) treatment in non -small -cell lung cancer (NSCLC) patients with brain metastases (BMs). MATERIALS AND METHODS: Seventy EGFR-mutated NSCLC patients with a total of 212 BMs who received first -line EGFR-TKI therapy were enrolled. Radiomics features were extracted from the BM regions on the pretreatment contrast -enhanced T1 -weighted images, and the radiomics score (rad-score) of each BM was established based on the selected features. Furthermore, the mean rad-score derived from the average rad-score of all included BMs in each patient was calculated. Univariate and multivariate logistic regression analyses were performed to identify potential predictors of IP. Prediction models based on different predictors and their combinations were constructed, and nomogram based on the optimal prediction model was evaluated. RESULTS: Thirty-three (47.1 %) patients developed IP, and the remaining 37 (52.9 %) patients were IP-free. EGFR-19del mutation (OR 0.19, 95 % CI 0.05-0.69), third -generation TKI treatment (OR 0.33, 95 % CI 0.16-0.67) and mean rad-score (OR 5.71, 95 % CI 1.65-19.68) were found to be independent predictive factors. Models based on these three predictors alone and in combination (combined model) achieved AUCs of 0.64, 0.64, 0.74, and 0.86 and 0.64, 0.64, 0.75, and 0.84 in the training and validation sets, respectively, and the combined model demonstrated optimal performance for predicting IP. CONCLUSIONS: The model integrating EGFR-19del mutation, third -generation TKI treatment and mean rad-score had good predictive value for IP after EGFR-TKI treatment in NSCLC patients with BM. (c) 2024 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:e582 / e591
页数:10
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