殷鹏展,张超,徐楚楚,洪薇,方兴根,叶明全,周运锋.基于一站式全脑CT灌注动态列线图预测动脉瘤性蛛网膜下腔出血后迟发性脑缺血[J].中国医学影像技术,2024,40(4):514~519
基于一站式全脑CT灌注动态列线图预测动脉瘤性蛛网膜下腔出血后迟发性脑缺血
Dynamic nomogram based on one-stop whole brain CT perfusion for predicting delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage
投稿时间:2023-10-09  修订日期:2023-11-30
DOI:10.13929/j.issn.1003-3289.2024.04.008
中文关键词:  蛛网膜下腔出血  动脉瘤  脑缺血  体层摄影术,X线计算机  列线图
英文关键词:subarachnoid hemorrhage  aneurysm  brain ischemia  tomography, X-ray computed  nomogram
基金项目:2022年度安徽省重点研究与开发计划项目(2022a05020011)、2022年度皖南医学院校中青年科研基金(WK2022F33)、2023年度安徽省高校自然科学研究项目(2023AH040251)。
作者单位E-mail
殷鹏展 皖南医学院第一附属医院放射科, 安徽 芜湖 241001  
张超 皖南医学院第一附属医院放射科, 安徽 芜湖 241001  
徐楚楚 皖南医学院第一附属医院放射科, 安徽 芜湖 241001  
洪薇 皖南医学院第一附属医院放射科, 安徽 芜湖 241001  
方兴根 皖南医学院第一附属医院神经外科, 安徽 芜湖 241001  
叶明全 皖南医学院医学信息学院, 安徽 芜湖 241002  
周运锋 皖南医学院第一附属医院放射科, 安徽 芜湖 241001 zhouyunfeng808@163.com 
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中文摘要:
      目的 观察基于一站式全脑CT灌注(CTP)动态列线图预测动脉瘤性蛛网膜下腔出血(aSAH)后迟发性脑缺血(DCI)的价值。方法 前瞻性对233例aSAH患者行一站式全脑CTP检查。按7[DK(]∶[DK)]3比例随机将其分为训练集(n=164)和验证集(n=69)并于集内根据是否发生DCI划分亚组;采用单因素分析、线性诊断和多因素logistic回归分析筛选预测aSAH后DCI的独立因素,建立传统列线图,生成基于网络的动态列线图;绘制受试者工作特征(ROC)曲线,评估动态列线图预测aSAH后DCI的效能。结果 高血压×平均流入时间(mTTS)、世界神经外科医师联盟(WFNS)分级、改良Fisher分级(mFS)及平均流量提取乘积(mFEP)均为aSAH后DCI的独立预测因素。基于此构建的动态列线图预测训练集aSAH后DCI的敏感度、特异度及曲线下面积(AUC)分别为70.00%、89.50%及0.890,在验证集分别为76.20%、83.33%及0.870。结论 基于一站式全脑CTP动态列线图可有效预测aSAH后DCI。
英文摘要:
      Objective To explore the value of dynamic nomogram based on one-stop whole brain CT perfusion (CTP) for predicting delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH). Methods Totally 233 aSAH patients were prospectively enrolled, and one-stop whole brain CTP examinations were performed. The patients were randomly divided into training set (n=164) or validation set (n=69) at a ratio of 7 ∶ 3, and further assigned into subgroups according to whether DCI occurred or not after aSAH. Univariate analysis, linear diagnosis and multivariate logistic regression were used to screen the independent factors for predicting DCI after aSAH, and a traditional nomogram was established, then a dynamic nomogram was constructed based on network. Receiver operating characteristic (ROC) curve was drawn to evaluate the efficacy of the dynamic nomogram for predicting DCI after aSAH. Results Hypertension×mean time to start (mTTS), World Federation of Neurosurgical Societies (WFNS) grade, modified Fisher scale (mFS), and mean flow extraction product (mFEP) were all independent predictors of DCI after aSAH. The sensitivity, specificity and area under the curve (AUC) of the dynamic nomogram for predicting DCI after aSAH was 70.00%, 89.50% and 0.890 in training set, 76.20%, 83.33% and 0.870 in validation set, respectively. Conclusion Dynamic nomogram based on one-stop whole brain CTP could be used to effectively predict DCI after aSAH.
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