中国医科大学学报2025，Vol.54Issue(5)：455-460,6.DOI:10.12007/j.issn.0258-4646.2025.05.013
基于多参数MRI影像组学和深度学习的急性脑梗死患者缺血半暗带预测研究
Prediction of ischemic penumbra in patients with acute cerebral infarction based on multiparameter MRI radiomics and deep learning
摘要
Abstract
Objective To explore the clinical feasibility of predicting ischemic penumbra(IP)in patients with acute cerebral infarction based on multiparameter magnetic resonance imaging(MRI)radiomics and deep learning.Methods A total of 105 patients with acute cerebral infarction treated at our hospital between January 2020 and January 2024 were divided into non-IP(n=36)and IP(n=69)groups according to the results of MRI diffusion-weighted imaging(DWI).The clinical data of the two groups were collected,and multipa-rameter MRI radiomics features were screened.Clinical,radiomics,and deep learning models were constructed,and their distinguishing powers were evaluated.A fused model was constructed,and the receiver operating characteristic(ROC),calibration,and clinical decision curves were used to evaluate the predictive efficacy of the four models.Results Increases in the admission National Institutes of Health Stroke Scale(NIHSS)score,anisotropy score(FA),apparent diffusion coefficient(ADC),average diffusion coefficient(DCavg),and N-acetyl aspartate(NAA)were protective factors for IP.An increase in the lactic acid(Lac)level was a risk factor for IP(P<0.05).Of the six considered deep learning models,the support vector machine model performed the best,with an accuracy of 0.952(100/105),sensi-tivity of 0.957(66/69),and specificity of 0.944(34/36).These three models can distinguish the patients with IP.The four models exhibited high differentiation,accuracy,and effectiveness;the prediction efficiency of the fused model was the highest.Conclusion The fused model based on clinical features,multiparameter MRI radiomics,and deep learning accurately predicts IP in patients with acute cerebral infarction and can be used to provide personalized prediction results.关键词
急性脑梗死/缺血半暗带/多参数磁共振成像影像组学/深度学习/融合模型Key words
acute cerebral infarction/ischemic penumbra/multiparameter magnetic resonance imaging radiomics/deep learning/fusion model分类
医药卫生引用本文复制引用
陈媛慧,雷雨萌,史文文..基于多参数MRI影像组学和深度学习的急性脑梗死患者缺血半暗带预测研究[J].中国医科大学学报,2025,54(5):455-460,6.基金项目
江西省卫生健康委科技计划(202120075) （202120075）
