流体衰减反转恢复
医学
四分位间距
置信区间
接收机工作特性
逻辑回归
溶栓
冲程(发动机)
核医学
队列
放射科
曲线下面积
试验预测值
磁共振成像
内科学
机械工程
工程类
心肌梗塞
作者
Anke Wouters,Bastian Cheng,Søren Christensen,Patrick Dupont,David Robben,Bo Norrving,Rico Laage,Vincent Thijs,Gregory W. Albers,Götz Thomalla,Robin Lemmens
出处
期刊:Neurology
[Ovid Technologies (Wolters Kluwer)]
日期:2018-05-01
卷期号:90 (18)
被引量:9
标识
DOI:10.1212/wnl.0000000000005413
摘要
To develop an automated model based on diffusion-weighted imaging (DWI) to detect patients within 4.5 hours after stroke onset and compare this method to the visual DWI-FLAIR (fluid-attenuated inversion recovery) mismatch.We performed a subanalysis of the "DWI-FLAIR mismatch for the identification of patients with acute ischemic stroke within 4.5 hours of symptom onset" (PRE-FLAIR) and the "AX200 for ischemic stroke" (AXIS 2) trials. We developed a prediction model with data from the PRE-FLAIR study by backward logistic regression with the 4.5-hour time window as dependent variable and the following explanatory variables: age and median relative DWI (rDWI) signal intensity, interquartile range (IQR) rDWI signal intensity, and volume of the core. We obtained the accuracy of the model to predict the 4.5-hour time window and validated our findings in an independent cohort from the AXIS 2 trial. We compared the receiver operating characteristic curve to the visual DWI-FLAIR mismatch.In the derivation cohort of 118 patients, we retained the IQR rDWI as explanatory variable. A threshold of 0.39 was most optimal in selecting patients within 4.5 hours after stroke onset resulting in a sensitivity of 76% and specificity of 63%. The accuracy was validated in an independent cohort of 200 patients. The predictive value of the area under the curve of 0.72 (95% confidence interval 0.64-0.80) was similar to the visual DWI-FLAIR mismatch (area under the curve = 0.65; 95% confidence interval 0.58-0.72; p for difference = 0.18).An automated analysis of DWI performs at least as good as the visual DWI-FLAIR mismatch in selecting patients within the 4.5-hour time window.
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