Heterogeneity of cerebral small vessel disease based on imaging markers in a community-based population

The heterogeneity of cerebral small vessel disease (CSVD) within community populations remains underexplored. In this study, we aimed to establish an imaging biomarker-based research paradigm to investigate CSVD heterogeneity and assess differences in progression risk among population subgroups.

This study is a population-based prospective cohort that included participants aged 50-75 years from the Polyvascular Evaluation for Cognitive Impairment and Vascular Events study. Participants underwent two follow-up evaluations, with continuous monitoring for incident vascular events and mortality. Imaging markers, including white matter hyperintensities (WMH), lacunes, enlarged perivascular spaces (EPVS) and cerebral microbleeds (CMB) were rated on cranial MRI. Automated pipelines quantified WMH volume, and cognitive function was assessed using the Montreal Cognitive Assessment. K-means clustering identified subgroups with distinct CSVD imaging features. Mixed linear regression models predicted imaging progression and cognitive decline. Internal and external validation were performed using cross-validation and outcome-based Cox proportional hazards models, respectively.

Among 2332 participants, four distinct CSVD subgroups were identified. Subgroup 1 exhibited a globally high imaging burden, the greatest vascular risk factor load, and was classified as a high-risk, rapidly progressing arteriolosclerosis subtype. Subgroup 2 demonstrated a high lacune/CMB burden, moderate EPVS severity, low WMH load, few risk factors and elevated high high-density lipoprotein cholesterol levels, representing a protected, slowly progressing subtype. Subgroup 3 showed low lacune/CMB counts, moderate WMH and EPVS burden, multiple risk factors and prevalent renal impairment, forming a high-risk, rapidly progressing renal impairment subtype. Subgroup 4 presented moderate WMH burden, high lacune/CMB counts, low EPVS severity, the lowest risk profile and was identified as a global low-risk, slowly progressing subtype.

Cluster analysis effectively delineated heterogeneous CSVD subgroups in a community population, each exhibiting distinct progression risks. Imaging-based heterogeneity profiling may support population risk stratification and guide targeted intervention strategies.