摘要：

目的 分析颈内动脉颅外段（EICA）和椎动脉颅外段（EVA）迂曲与急性缺血性卒中的相关性，以探讨血管迂曲原因及其诱发脑卒中的作用机制。 方法 采用CTA 测量103 例急性缺血性卒中患者和103 例非缺血性卒中致头晕和头痛患者EICA 和EVA 迂曲指数、偏离度、迂曲度和成角个数，Pearson 相关分析和Spearman 秩相关分析EICA 和EVA 迂曲指数与缺血性卒中危险因素和其他血管形态学指标的相关性，单因素和多因素逐步法Logistic 回归分析筛查EICA 和EVA 迂曲相关危险因素。 结果 脑卒中组患者EICA 和EVA 迂曲指数（P = 0.000，0.000）、偏离度（P = 0.000，0.000）、迂曲度（P =0.002，0.000）和成角个数（P = 0.019，0.000）均高于对照组。根据梗死灶部位，进一步将脑卒中组分为前循环梗死亚组（73 例）和后循环梗死亚组（30 例），两亚组内（梗死侧与非梗死侧EICA，左侧与右侧EVA）和两亚组间血管形态学指标差异均无统计学意义（P > 0.05）；而前循环梗死亚组EICA 迂曲指数（P =0.000）、偏离度（P = 0.000）和迂曲度（P = 0.045），以及后循环梗死亚组EVA 迂曲指数（P = 0.000）、偏离度（P = 0.000）、迂曲度（P = 0.000）和成角个数（P = 0.046）均高于对照组。选择二者迂曲指数较高的一侧，相关分析显示，缺血性卒中患者EICA 迂曲指数与年龄、颈动脉粥样硬化、EICA 和EVA 形态学指标（除外EVA 偏离度）均呈正相关（P < 0.05），而与男性呈负相关（r_s = -0.253，P = 0.010）；EVA 迂曲指数与年龄、高血压、EICA 和EVA 形态学指标均呈正相关（P < 0.05），而与男性呈负相关（r_s = -0.276，P = 0.005）。单因素和多因素逐步法Logistic 回归分析显示，女性（EICA：OR = 1.458，95%CI：1.111 ~ 5.166，P = 0.016；EVA：OR = 9.092，95%CI：1.294 ~ 63.872，P = 0.026）和年龄（EICA：OR = 1.050，95%CI：1.013 ~ 1.088，P = 0.007；EVA：OR = 1.084，95%CI：1.003 ~ 1.138，P = 0.001）是EICA 和EVA 迂曲的独立危险因素。 结论 缺血性卒中患者EICA 和EVA 迂曲无侧别、前后循环分布的差异。缺血性卒中患者EICA 和EVA 形态学指标显著高于非脑卒中患者。女性和高龄是EICA 和EVA 迂曲的独立危险因素。

关键词: 颈内动脉, 椎动脉, 血管畸形, 卒中, 脑缺血, 危险因素, 回归分析

Abstract:

Objective  To analyze the correlation between tortuosity of extracranial internal carotid artery (EICA) and extracranial vertebral artery (EVA) and acute ischemic stroke, so as to discuss the causes of vascular tortuosity and the mechanism on inducing stroke.  Methods  This study included 103 patients with acute ischemic stroke and 103 patients without acute ischemic stroke whose manifestations were headache and dizziness. CTA was used to measure the tortuosity index (TI), deviation degree (DD), tortuosity degree (TD) and angular number (AN) of EICA and EVA. Pearson correlation analysis and Spearman rank correlation analysis were used to analyze the correlations of arterial tortuosity with risk factors for ischemic stroke and vascular morphology. Univariate and stepwise multivariate Logistic regression analysis were used to screen related risk factors for tortuosity of EICA and EVA.  Results  The stroke group had higher TI (P = 0.000, 0.000), DD (P = 0.000, 0.000), TD (P = 0.002, 0.000) and AN (P =0.019, 0.000) of EICA and EVA than those in control group. According to the site of infarction, the stroke group was divided into anterior circulation infarction (ACI) subgroup (N = 73) and posterior circulation infarction (PCI) subgroup (N = 30), and there was no significant difference in above-mentioned vascular morphological indexes between 2 subgroups (P > 0.05, for all); in each subgroup, there was no significant difference between infarct side and non-infarct side of EICA, and between left and right EVA (P > 0.05, for all). Nevertheless, the TI (P = 0.000), DD (P = 0.000) and TD (P = 0.045) of EICA in ACI subgroup were higher than those in control group; TI (P = 0.000), DD (P = 0.000), TD (P = 0.000) and AN (P = 0.046) of EVA in PCI subgroup were higher than those in control group. In stroke group, correlation analysis revealed that TI of EICA was positively correlated with age, cervical artery atherosclerosis (CAS), EICA and EVA morphological indexes (except DD of EVA; P < 0.05, for all), but was negatively correlated with male (r_s = -0.253, P = 0.010); TI of EVA was positively correlated with age, hypertension, morphological indexes of EICA and EVA (P < 0.05, for all), but negatively correlated with male (r_s =-0.276, P = 0.005). Univariate and stepwise multivariate Logistic regression analysis showed that female (EICA: OR = 1.458, 95% CI: 1.111-5.166, P = 0.016; EVA: OR = 9.092，95%CI: 1.294-63.872, P = 0.026) and age (EICA: OR = 1.050, 95%CI: 1.013-1.088，P = 0.007; EVA: OR = 1.084, 95%CI: 1.003-1.138, P = 0.001) were independent risk factors for tortuosity of EICA and EVA.  Conclusions  There are no significant differences between left and right side, anterior and posterior circulation on tortuosity distribution of patients with ischemic stroke. The EICA and EVA morphological indexes of stroke patients was significantly higher than that of non-stroke patients. Female and age are independent risk factors for tortuosity of EICA and EVA.

Key words: Carotid artery, internal, Vertebral artery, Vascular malformations, Stroke, Brain ischemia, Risk factors, Regression analysis