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SUBTYPES AND UNIQUE CLINICAL MARKERS OF CEREBRAL SMALL VESSEL DISEASE
Background and Aims
Radiological markers for cerebral small vessel disease (SVD) may have different biological underpinnings in their pathophysiology. However, there is no effective tool to individually categorize SVD. The relationships between white matter signal abnormalities (WMSA) features, lacunes, cerebral microbleeds (CMB) and enlarged perivascular space (EPVS) were quantified to categorize the phenotypes of SVD.
Data were acquired from healthy individuals who underwent comprehensive brain examinations for a health check-up program at a tertiary center. Among 647 individuals, 611 aged > 40 years were included after excluding 36 with minimal WMSA volume. The WMSA, lacunes, CMB and EPVS were quantified automatically or manually. The WMSA were classified by the number and size of non-contiguous lesions, distribution, and contrast. An algorithm with WMSA class and its interaction with other SVD markers was constructed to categorize individuals into distinct ‘types’ of SVD. Clinical and laboratory variability were determined across the individual SVD types.
Type A was characterized by multiple, small, deep WMSA but a low burden of lacunes and deep CMB; Type B had large periventricular WMSA and a high burden of lacunes and deep CMB; and Type C had restricted juxtaventricular WMSA and lacked lacunes and deep CMB. Type B was associated with an older age and a higher prevalence of hypertension and diabetes. Smoking and high uric acid levels were associated with an increased risk of type A.
The heterogeneity of SVD was categorized into three types with distinct clinical correlates. This new categorization will improve our understanding of SVD pathophysiology, risk stratification and outcome prediction.