Classification differentiates clinical and neuroanatomic features of cerebral small vessel disease. Issue 2 (20th May 2021)

• Record Type: Journal Article
• Authors: Chou, Kun-Hsien; Lee, Pei-Lin; Peng, Li-Ning; Lee, Wei-Ju; Wang, Pei-Ning; Chen, Liang-Kung; Lin, Ching-Po; Chung, Chih-Ping
• Is Part Of: Brain communications. Volume 3:Issue 2(2021)
• Publication Date: 2021-05-20
• Subjects: cerebral small vessel disease -- stratification -- grey-matter volume -- white-matter microstructure integrity; 616
• DOI: 10.1093/braincomms/fcab107
• Languages: English
• ISSNs: 2632-1297

Abstract

Abstract: Age-related cerebral small vessel disease involves heterogeneous pathogenesis, such as arteriosclerosis/lipohyalinosis and cerebral amyloid angiopathy. MRI can visualize the brain lesions attributable to small vessel disease pathologies, including white-matter hyperintensities, lacune and cerebral microbleeds. However, these MRI markers usually coexist in small vessel disease of different aetiologies. Currently, there is no available classification integrating these neuroimaging markers for differentiating clinical and neuroanatomic features of small vessel disease yet. In this study, we tested whether our proposed stratification scheme could characterize specific clinical, neuroanatomic and potentially pathogenesis/aetiologies in classified small vessel disease subtypes. Cross-sectional analyses from a community-based non-demented non-stroke cohort consisting of ≥50 years old individuals were conducted. All participants were scanned 3T brain MRI for small vessel disease detection and neuroanatomic measurements and underwent physical and cognitive assessments. Study population were classified into robust and four small vessel disease groups based on imaging markers indicating (i) bleeding or non-bleeding; (ii) specific location of cerebral microbleeds; and (iii) the severity and combination of white-matter hyperintensities and lacune. We used whole-brain voxel-based morphometry analyses and tract-based spatial statistics to evaluate the regional grey-matter volume and white-matter microstructure integrity for comparisons among groups. Among the 735 participants with eligible brain MRI images, quality screening qualified 670 for grey-matter volume analyses and 617 for white-matter microstructural analyses. Common and distinct patterns of the clinical and neuroimaging manifestations were found in the stratified four small vessel disease subgroups. Hierarchical clustering analysis revealed that small vessel disease type 4 had features distinct from the small vessel disease types 1, 2 and 3. Abnormal white-matter microstructures and cognitive function but preserved physical function and grey-matter volume were found in small vessel disease type 4. Among small vessel disease types 1, 2 and 3, there were similar characteristics but different severity; the clinical features showed both physical frail and cognitive impairment and the neuroanatomic features revealed frontal–subcortical white-matter microstructures and remote, diffuse cortical abnormalities. This novel stratification scheme highlights the distinct clinical and neuroanatomic features of small vessel disease and the possible underlying pathogenesis. It could have potential application in research and clinical settings. Abstract : Chou et al. propose a novel classification for cerebral small vessel disease and report the common and distinct patterns of the clinical and neuroimaging manifestations in the stratified four subgroups. It could be used in clinical and research settings to differentiate arteriosclerosis and cerebral amyloid angiopathy and also their severity. Graphical Abstract: