磁共振成像2025，Vol.16Issue(10)：35-40,6.DOI:10.12015/issn.1674-8034.2025.10.006
深度神经网络MRI影像组学预测胶质母细胞瘤MGMT启动子甲基化状态
Deep neural network MRI radiomics predicts glioblastoma MGMT promoter methylation status
摘要
Abstract
Objective:To explore the value of a deep neural network model based on multi-sequence MRI in predicting the methylation status of the O6-methylguanine-DNA methyltransferase(MGMT)promoter in patients with glioblastoma.Materials and Methods:T1WI and contrast enhanced T1-weighted imaging(CE-T1WI)data from 262 glioblastoma patients(162 methylation and 100 unmethylation)were retrospectively analyzed.The Mann-Whitney U test,least absolute shrinkage and selection operator(LASSO)regression analysis,combined with the Pearson correlation coefficient method,were used to screen the features.Based on the screened features,a prediction model was constructed by means of the deep neural network algorithm.To evaluate the prediction efficiency of this model,the area under the receiver operating characteristic curve(AUC)was adopted to measure the prediction accuracy and reliability of the model.Results:The T1WI model(AUC=0.752 in the validation set,sensitivity=68.8%,specificity=75.0%),the CE-T1WI model(AUC=0.823 in the validation set,sensitivity=75.0%,specificity=75.0%),and the multi sequence combined model(AUC=0.847 in the validation set,sensitivity=81.3%,specificity=80.0%)based on the deep neural network could be used to predict the MGMT promoter methylation of patients with glioblastoma,and the multi sequence combined model had the highest diagnostic efficacy compared with the single sequence models.Conclusions:The multi sequence MRI radiomics model based on deep neural network can noninvasively predict the MGMT promoter methylation features in glioblastomas.关键词
胶质母细胞瘤/多序列磁共振成像/影像组学/深度神经网络/O6-甲基鸟嘌呤-DNA甲基转移酶Key words
glioblastomas/multi-sequence magnetic resonance images/radiomics/deep neural network/O6-methylguanine-DNA methyltransferase分类
医药卫生引用本文复制引用
吕冲,夏林峰,陈请水,郑广鑫,黄碧云,陈雷..深度神经网络MRI影像组学预测胶质母细胞瘤MGMT启动子甲基化状态[J].磁共振成像,2025,16(10):35-40,6.基金项目
Xiamen Municipal Health and Wellness High Quality Development Science and Technology Program Project for Young Research Subjects(No.2024GZL-QN089). 厦门市卫生健康高质量发展科技计划项目青年科研课题(编号:2024GZL-QN089) （No.2024GZL-QN089）
