Department of Neurology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Department of Neurology, Seoul National University Healthcare System Gangnam Center, Seoul, South Korea.
Eur Radiol. 2023 Feb;33(2):1143-1151. doi: 10.1007/s00330-022-09070-1. Epub 2022 Aug 18.
Radiological markers for cerebral small vessel disease (SVD) may have different biological underpinnings in their development. We attempted to categorize SVD burden by integrating white matter signal abnormalities (WMSA) features and secondary presence of lacunes, microbleeds, and enlarged perivascular spaces.
Data were acquired from 610 older adults (aged > 40 years) who underwent brain magnetic resonance imaging exam as part of a health checkup. The WMSA were classified individually by the number and size of non-contiguous lesions, distribution, and contrast. Age-detrended lacunes, microbleeds, and enlarged perivascular space were quantified to further categorize individuals. Clinical and laboratory values were compared across the individual classes.
Class I was characterized by multiple, small, deep WMSA but a low burden of lacunes and microbleeds; class II had large periventricular WMSA and a high burden of lacunes and microbleeds; and class III had limited juxtaventricular WMSA and lacked lacunes and microbleeds. Class II was associated with older age, diabetes, and a relatively higher neutrophil-to-lymphocyte ratio. Smoking and higher uric acid levels were associated with an increased risk of class I.
The heterogeneity of SVD was categorized into three classes with distinct clinical correlates. This categorization will improve our understanding of SVD pathophysiology, risk stratification, and outcome prediction.
• Classification of white matter signal abnormality (WMSA) features was associated with different characteristic of lacunes, microbleeds, and enlarged perivascular space and clinical variability. • Class I was characterized by multiple, small, deep WMSA but a low burden of lacunes and microbleeds. Class II had large periventricular WMSA and a high burden of lacunes and microbleeds. Class III had limited juxtaventricular WMSA and lacked lacunes and microbleeds. • Class II was associated with older age, diabetes, and higher neutrophil-to-lymphocyte ratio. Smoking and higher uric acid levels were associated with an increased risk of class I.
脑小血管病（SVD）的放射学标志物在其发展过程中可能具有不同的生物学基础。我们试图通过整合脑白质信号异常（WMSA）特征以及腔隙、微出血和扩大的血管周围间隙的继发存在来对 SVD 负担进行分类。
数据来自 610 名年龄在 40 岁以上的老年人，他们在健康检查中接受了脑部磁共振成像检查。WMSA 单独按照非连续病变的数量和大小、分布和对比进行分类。量化年龄趋势的腔隙、微出血和扩大的血管周围间隙以进一步对个体进行分类。比较个体分类的临床和实验室值。
I 类特征为多发性、小而深的 WMSA，但腔隙和微出血负担较低；II 类具有大的脑室周围 WMSA 和高腔隙和微出血负担；III 类具有有限的脑室旁 WMSA，且缺乏腔隙和微出血。II 类与年龄较大、糖尿病和相对较高的中性粒细胞与淋巴细胞比值有关。吸烟和尿酸水平升高与 I 类的风险增加有关。
SVD 的异质性被分为三个具有不同临床相关性的类别。这种分类将提高我们对 SVD 病理生理学、风险分层和结果预测的理解。
WMSA 特征的分类与腔隙、微出血和扩大的血管周围间隙的不同特征以及临床变异性相关。
I 类的特征是多发性、小而深的 WMSA，但腔隙和微出血负担较低。II 类具有大的脑室周围 WMSA 和高腔隙和微出血负担。III 类具有有限的脑室旁 WMSA，且缺乏腔隙和微出血。
II 类与年龄较大、糖尿病和较高的中性粒细胞与淋巴细胞比值有关。吸烟和尿酸水平升高与 I 类的风险增加有关。
