Department of Geriatrics, Xiangya Hospital, Central South University; National Clinical Research Centre for Geriatric Disorders, Changsha, Hunan, China (F.Y.).
Department of Neurology, Donders Center for Medical Neurosciences, Radboud University Medical Center, Nijmegen, the Netherlands (F.Y., M.C., M.A.J., A.M.T., F.-E.d.L.).
Stroke. 2022 Dec;53(12):3688-3695. doi: 10.1161/STROKEAHA.122.039903. Epub 2022 Oct 3.
The underlying mechanisms of incident lacunes regarding their spatial distribution remain largely unknown. We investigated the spatial distribution pattern and MRI predictors of incident lacunes in relation to white matter hyperintensity (WMH) over 14 years follow-up in sporadic small vessel disease.
Five hundred three participants from the ongoing prospective single-center Radboud University Nijmegen Diffusion Tensor and Magnetic resonance Cohort (RUN DMC) were recruited with baseline assessment in 2006 and follow ups in 2011, 2015, and 2020. Three hundred eighty-two participants who underwent at least 2 available brain MRI scans were included. Incident lacunes were systematically identified, and the spatial relationship between incident lacunes located in subcortical white matter and WMH were determined using a visual rating scale. Adjusted multiple logistic regression and linear mixed-effect regression models were used to assess the association between baseline small vessel disease markers, WMH progression, and incident lacunes. Participants with atrial fibrillation were excluded in multivariable analysis.
Eighty incident lacunes were identified in 43 patients (mean age 66.5±8.2 years, 37.2% women) during a mean follow-up time of 11.2±3.3 years (incidence rate 10.0/1000 person-year). Sixty percent of incident lacunes were in the white matter, of which 48.9% showed no contact with preexisting WMH. Baseline WMH volume (odds ratio=2.5 [95% CI, 1.6-4.2]) predicted incident lacunes after adjustment for age, sex, and vascular risk factors. WMH progression was associated with incident lacunes independent of age, sex, baseline WMH volume, and vascular risk factors (odds ratio, 3.2 [95% CI, 1.5-6.9]). Baseline WMH volume and progression rate were higher in participants with incident lacunes in contact with preexisting WMH. No difference in vascular risk factors was observed regarding location or relation with preexisting WMH.
The 2 different distribution patterns of lacunes regarding their relation to WMH may suggest distinct underlying mechanisms, one of which may be more closely linked to a similar pathophysiology as that of WMH. The longitudinal relation between WMH and lacunes further supports plausible shared mechanisms between the 2 key markers.
关于腔隙性梗死的发病机制及其空间分布仍知之甚少。我们通过 14 年的随访,研究了散发小血管病患者的腔隙性梗死的空间分布模式和 MRI 预测因子,与脑白质高信号(WMH)相关。
我们招募了来自持续进行的前瞻性单中心 Radboud 大学奈梅亨弥散张量和磁共振队列(RUN DMC)的 503 名参与者,在 2006 年进行基线评估,在 2011 年、2015 年和 2020 年进行随访。纳入了至少进行 2 次可获得的脑部 MRI 扫描的 382 名参与者。系统地识别了腔隙性梗死,并使用视觉评分量表确定了位于皮质下白质中的腔隙性梗死与 WMH 之间的空间关系。使用多变量逻辑回归和线性混合效应回归模型来评估基线小血管疾病标志物、WMH 进展与腔隙性梗死之间的关联。在多变量分析中排除了房颤患者。
在平均 11.2±3.3 年的随访中,43 名患者(平均年龄 66.5±8.2 岁,37.2%为女性)中发现了 80 个腔隙性梗死(发生率为 10.0/1000 人年)。60%的腔隙性梗死位于白质,其中 48.9%与既往 WMH 无接触。在调整年龄、性别和血管危险因素后,基线 WMH 体积(比值比=2.5[95%可信区间,1.6-4.2])预测腔隙性梗死。WMH 进展与腔隙性梗死相关,独立于年龄、性别、基线 WMH 体积和血管危险因素(比值比,3.2[95%可信区间,1.5-6.9])。与既往 WMH 接触的腔隙性梗死患者的基线 WMH 体积和进展率更高。在与既往 WMH 的位置或关系方面,血管危险因素没有差异。
腔隙性梗死与 WMH 的 2 种不同分布模式可能提示不同的发病机制,其中一种可能与 WMH 的类似病理生理学更为密切相关。WMH 和腔隙性梗死之间的纵向关系进一步支持了这两个关键标志物之间可能存在共同的机制。