Yin Xuyang, Han Yan, Cao Xin, Zeng Yanwei, Tang Yuping, Ding Ding, Zhang Jun
Department of Radiology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China.
National Center for Neurological Disorders, Shanghai, China.
Quant Imaging Med Surg. 2023 Jan 1;13(1):27-36. doi: 10.21037/qims-22-264. Epub 2022 Oct 26.
This study aimed to explore the association between deep medullary veins (DMVs) and the neuroimaging burden of cerebral small vessel disease (CSVD).
In this cross-sectional study based on a retrospective analysis, a total of 248 patients (183 males and 65 females; mean age ± standard deviation, 69.5±14.8 years) diagnosed with CSVD with complete imaging and clinical data were enrolled. Neuroimaging markers of CSVD, including white matter hyperintensities, lacunes, prominent perivascular spaces (PVSs), and cerebral microbleeds (CMBs), were identified, and the total burden of CSVD was scored. Both DMV number and DMV score were used for assessment using susceptibility-weighted imaging (SWI).
With the exception of perivascular spaces, more severe neuroimaging markers were observed in patients with a higher DMV score. After adjustments were made for age and body mass index (BMI), a higher DMV score (β=1.39; P<0.001) and smaller DMV number (β=-2.55; P=0.001) were associated with an increased CSVD burden. The degree of CMBs was independently correlated with both DMV score (β=1.60; P<0.001) and DMV number (β=-2.27; P=0.009). The association between lacunes and DMV score was also significant (β=0.97; P=0.026).
Both DMV score and DMV number are potential imaging indicators of CSVD.
本研究旨在探讨深部髓静脉（DMV）与脑小血管病（CSVD）神经影像学负担之间的关联。
在这项基于回顾性分析的横断面研究中，共纳入了248例诊断为CSVD且具有完整影像学和临床资料的患者（183例男性和65例女性；平均年龄±标准差，69.5±14.8岁）。确定了CSVD的神经影像学标志物，包括白质高信号、腔隙、明显的血管周围间隙（PVS）和脑微出血（CMB），并对CSVD的总负担进行评分。使用磁敏感加权成像（SWI）评估DMV数量和DMV评分。
除血管周围间隙外，DMV评分较高的患者观察到更严重的神经影像学标志物。在对年龄和体重指数（BMI）进行调整后，较高的DMV评分（β=1.39；P<0.001）和较少的DMV数量（β=-2.55；P=0.001）与CSVD负担增加相关。CMB的程度与DMV评分（β=1.60；P<0.001）和DMV数量（β=-2.27；P=0.009）均独立相关。腔隙与DMV评分之间的关联也很显著（β=0.97；P=0.026）。
DMV评分和DMV数量均是CSVD的潜在影像学指标。
