Clinical College, Xuzhou Medical University, Xuzhou, China.
Department of Neurology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
Brain Behav. 2023 Apr;13(4):e2932. doi: 10.1002/brb3.2932. Epub 2023 Mar 14.
The contribution of large vessel stenosis to the development of white matter hyperintensities (WMHs) has not been fully elucidated. This study aims to explore the correlation between ipsilateral white matter hyperintensities (WMHs) and the severity of large vessel stenosis in the anterior circulation and cerebral perfusion level, as well as analyze the factors influencing WMHs.
A cross-sectional study of 150 patients with unilateral anterior circulation large vessel stenosis of ≥50% was conducted. The severity of ipsilateral WMHs was assessed by Fazekas scale on T2-weighted image and/or fluid-attenuated inversion recovery MR imaging, vascular stenosis severity was evaluated on computed tomography angiography images, and the level of cerebral perfusion was rated according to a staging system for abnormal cerebral perfusion based on CTP results. The relationships between the stenosis severity, cerebral perfusion level and ipsilateral WMHs severity were analyzed. A multivariate logistic regression analysis was performed to determine the factors independently influencing WMHs.
Among 150 patients (mean age, 63.12 ± 10.55 years), there was a statistically significant positive correlation between cerebral perfusion level and the severity of DWMHs and PWMHs (Gamma = 0.561, p < .001; Gamma = 0.600, p < .001), and a positive correlation between cerebral perfusion level and the severity of vascular stenosis (Gamma = 0.495, p < .001).While, there was no statistically significant correlation between the severity of vascular stenosis and the severity of DWMHs and PWMHs (Gamma = 0.188, p = .08; Gamma = 0.196, p = .06). The multivariate logistic regression analysis results demonstrated that age (OR = 1.047, 95% CI 1.003-1.093; p = .035), stroke/TIA history (OR = 2.880, 95% CI 1.154-7.190; p = .023) and stage II of cerebral perfusion (OR = 2.880, 95% CI 1.154-7.190; p = .023) were independent influencing factors on ipsilateral DWMHs. Age (OR = 1.051, 95% CI 1.009-1.094; p = .018), and stage II of cerebral perfusion (OR = 12.871, 95% CI 3.576-46.322; p < .001) were factors independently influencing ipsilateral PWMHs.
White matter hyperintensities may be attributed to cerebral hypoperfusion secondary to vascular stenosis but not directly to the severity of stenosis in the large vessels of anterior circulation. Moreover, longitudinal studies with sequential imaging exams may further reveal the impact of cerebral perfusion secondary to vascular stenosis on the development and progression of WMHs.
大动脉狭窄对白质高信号(WMHs)发展的影响尚未完全阐明。本研究旨在探讨同侧白质高信号(WMHs)与前循环大血管狭窄严重程度和脑灌注水平的相关性,并分析影响 WMHs 的因素。
对 150 例单侧前循环大血管狭窄≥50%的患者进行横断面研究。采用 T2 加权图像和/或液体衰减反转恢复磁共振成像(FLAIR)的 Fazekas 量表评估同侧 WMHs 的严重程度,采用计算机断层血管造影(CTA)图像评估血管狭窄的严重程度,根据 CTP 结果的异常脑灌注分期系统评估脑灌注水平。分析狭窄严重程度、脑灌注水平与同侧 WMHs 严重程度之间的关系。采用多变量逻辑回归分析确定影响 WMHs 的独立因素。
在 150 例患者(平均年龄 63.12±10.55 岁)中,脑灌注水平与 DWMHs 和 PWMHs 的严重程度呈显著正相关(Gamma=0.561,p<0.001;Gamma=0.600,p<0.001),脑灌注水平与血管狭窄严重程度呈正相关(Gamma=0.495,p<0.001)。而血管狭窄严重程度与 DWMHs 和 PWMHs 的严重程度无统计学显著相关性(Gamma=0.188,p=0.08;Gamma=0.196,p=0.06)。多变量逻辑回归分析结果表明,年龄(OR=1.047,95%CI 1.003-1.093;p=0.035)、卒中/TIA 病史(OR=2.880,95%CI 1.154-7.190;p=0.023)和脑灌注分期 II 期(OR=2.880,95%CI 1.154-7.190;p=0.023)是同侧 DWMHs 的独立影响因素。年龄(OR=1.051,95%CI 1.009-1.094;p=0.018)和脑灌注分期 II 期(OR=12.871,95%CI 3.576-46.322;p<0.001)是同侧 PWMHs 的独立影响因素。
WMHs 可能是由于血管狭窄导致的脑灌注不足引起的,而不是直接由前循环大血管的狭窄严重程度引起的。此外,通过连续影像学检查的纵向研究可能进一步揭示血管狭窄导致的脑灌注对 WMHs 发展和进展的影响。