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. 2023 Feb;33(2):1143-1151.
doi: 10.1007/s00330-022-09070-1. Epub 2022 Aug 18.

Classification of white matter lesions and characteristics of small vessel disease markers

Kyung-Il Park  1   2 , Keun-Hwa Jung  3   4 , Eung-Joon Lee  1 , Woo-Jin Lee  1   5 , Seol Ah Hwang  1 , Sohyun Kim  1 , David H Salat  6   7
Affiliations

Classification of white matter lesions and characteristics of small vessel disease markers

Kyung-Il Park et al. Eur Radiol. 2023 Feb.

Abstract

Objectives: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Key points: • 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.

Keywords: MRI; Risk factor; Small vessel disease; Type; White matter signal abnormality.

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