Wintermark Max, Arora Sandeep, Tong Elizabeth, Vittinghoff Eric, Lau Benison C, Chien Jeffrey D, Dillon William P, Saloner David
Department of Radiology, Neuroradiology Section, University of California, San Francisco, San Francisco, CA 94143-0628, USA.
Ann Neurol. 2008 Aug;64(2):149-57. doi: 10.1002/ana.21424.
To identify a set of computed tomographic (CT) features of carotid atherosclerotic plaques that is significantly associated with ischemic stroke.
In a cross-sectional study, we retrospectively identified 136 consecutive patients admitted to our emergency department with suspected stroke who underwent a CT-angiogram of the carotid arteries. CT-angiographic studies of the carotid arteries were processed automatically using automated computer classifier algorithm that quantitatively assesses a battery of carotid CT features. Acute stroke patients were categorized into "acute carotid stroke patients" and "nonacute carotid stroke patients" independent of carotid wall CT features, using the Causative Classification System for Ischemic Stroke, which includes the neuroradiologist's review of the imaging studies of the brain parenchyma and of the degree of carotid stenosis, and charted test results (such as electrocardiogram). Univariate followed by multivariate analyses were used to build models to differentiate between these patient groups and to differentiate between the infarct and unaffected sides in the "acute carotid stroke patients."
Forty "acute carotid stroke" patients and 50 "nonacute carotid stroke" patients were identified. Multivariate modeling identified a small number of the carotid wall CT features that were significantly associated with acute carotid stroke, including wall volume, fibrous cap thickness, number and location of lipid clusters, and number of calcium clusters.
Patients with acute carotid stroke demonstrate significant differences in the appearance of their carotid wall ipsilateral to the side of their infarct, when compared with either nonacute carotid stroke patients or the carotid wall contralateral with the infarct side.
确定一组与缺血性卒中显著相关的颈动脉粥样硬化斑块的计算机断层扫描（CT）特征。
在一项横断面研究中，我们回顾性纳入了136例因疑似卒中入住急诊科且接受了颈动脉CT血管造影的连续患者。使用自动计算机分类算法对颈动脉的CT血管造影研究进行自动处理，该算法可定量评估一系列颈动脉CT特征。采用缺血性卒中病因分类系统，独立于颈动脉壁CT特征，将急性卒中患者分为“急性颈动脉卒中患者”和“非急性颈动脉卒中患者”，该系统包括神经放射科医生对脑实质成像研究、颈动脉狭窄程度以及图表化检查结果（如心电图）的评估。采用单因素分析和多因素分析构建模型，以区分这些患者组，并区分“急性颈动脉卒中患者”梗死侧和未受影响侧。
共识别出40例“急性颈动脉卒中”患者和50例“非急性颈动脉卒中”患者。多因素建模确定了少数与急性颈动脉卒中显著相关的颈动脉壁CT特征，包括壁体积、纤维帽厚度、脂质簇的数量和位置以及钙簇的数量。
与非急性颈动脉卒中患者或梗死侧对侧的颈动脉壁相比，急性颈动脉卒中患者梗死侧同侧的颈动脉壁外观存在显著差异。
