2025 年第 10 期 第 20 卷

分水岭脑梗死患者头颈部动脉粥样硬化斑块的计算机断层扫描血管成像特征及其与动态动脉硬化指数的相关性

Computed tomography angiography  characteristics of atherosclerotic plaques in head and neck of patients with cerebral watershed infarction and its correlation with ambulatory arterial stifness index

作者：于远1王坤2杨淑贞2

英文作者：Yu Yuan1 Wang Kun2 Yang Shuzhen2

单位：1首都医科大学附属北京天坛医院放射科，北京100070；2北京航天总医院影像中心，北京100070

英文单位：1Department of Radiology Beijing Tiantan Hospital Capital Medical University Beijing 100070 China; 2Imaging Center Beijing Aerospace General Hospital Beijing 100070 China

关键词：分水岭脑梗死；计算机断层扫描血管成像；动态动脉硬化指数

英文关键词：Cerebralwatershedinfarction;Computedtomographyangiography;Ambulatoryarterialstifnessindex

• 摘要：

• 目的 探究分水岭脑梗死（CWI）患者头颈部动脉粥样硬化斑块的计算机断层扫描血管成像（CTA）特征及其与动态动脉硬化指数（AASI）的相关性。方法 回顾性分析2021年3月至2024年3月于北京航天总医院就诊的100例CWI患者的临床资料，根据磁共振弥散加权成像检查结果，分为急性CWI（ACWI）组（46例）和非ACWI组（54例）。采用多因素Logistic回归方法分析危险因素以及不同分层参数间的关联效应。采用多元线性回归（MLR）模型分析相关性。采用受试者工作特征（ROC）曲线评估预测效能。结果 多因素分析显示，颈内动脉狭窄程度、大脑中动脉（MCA）狭窄程度、病变血管支数、平均动脉压（MAP）、空腹血糖、低密度脂蛋白胆固醇（LDL-C）、AASI、颈动脉斑块（CP）负荷、CP体积、CP脂质核心体积均为ACWI发生的独立影响因素（均P<0.05）。MLR分析显示，AASI与颈内动脉狭窄程度、MCA狭窄程度、病变血管支数、CP负荷、CP体积、CP脂质核心体积、空腹血糖、LDL-C均呈正相关（均P<0.05）。AASI与CP负荷、体积、脂质核心体积存在强关联性（均P趋势<0.05）。ROC曲线分析显示，颈内动脉和MCA狭窄程度+病变血管支数+CP负荷+CP体积+CP脂质核心体积+AASI联合预测ACWI的曲线下面积最大（0.924），预测价值最高。结论 颈内动脉和MCA狭窄程度、病变血管支数、AASI、CP负荷、CP体积、CP脂质核心体积、空腹血糖、LDL-C均为ACWI发生的独立影响因素。临床上可通过头颈部CTA诊断结果和相关参数与AASI联合对ACWI患者进行早期诊断。

• Objective To explore the computed tomography angiography (CTA) characteristics of atherosclerotic plaques in the head and neck of patients with cerebral watershed infarction (CWI) and its correlation with ambulatory arterial stifness index (AASI). Methods The clinical data of 100 patients with CWI who were admitted to Beijing Aerospace General Hospital from March 2021 to March 2024 were retrospectively analyzed, and they were divided into acute CWI (ACWI) group (46 cases) and non-ACWI group (54 cases) according to the results of magnetic resonance diffusion-weighted imaging. Multiple Logistic regression method was used to analyze the association effects between risk factors and different stratification parameters. Multivariable linear regression (MLR) model was used to analyze the correlation. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance. Results Multivariate analysis showed that the degree of internal carotid artery (ICA) stenosis, middle cerebral artery (MCA) stenosis, number of diseased vessels, mean arterial pressure (MAP), fasting blood glucose (FBG), low-density lipoprotein cholesterol (LDL-C), AASI, carotid plaque (CP) burden, CP volume, and CP lipid core volume were all independent influencing factors for the occurrence of ACWI (all P<0.05). MLR analysis showed that AASI was positively correlated with the degree of internal carotid artery stenosis, MCA stenosis, number of diseased vessel branches, CP load, CP volume, CP lipid core volume, fasting blood glucose, and LDL-C (all P<0.05). There was a strong correlation between AASI and CP burden, volume, and lipid core volume (all Ptrend<0.05). ROC curve analysis showed that the combination of ICA and MCA stenosis degree+number of diseased blood vessels+CP burden+CP volume+CP lipid core volume+ASI had the highest area under the curve (0.924) and predictive value for predicting ACWI. Conclusions ICA and MCA stenosis degree, number of diseased vessel branches, AASI, CP burden, volume, lipid core volume, FBG, and LDL-C are all independent influencing factors for the occurrence of ACWI. In clinical practice, early diagnosis of ACWI patients can be achieved by combining head and neck CTA diagnostic results and related parameters with AASI.