TY - JOUR
T1 - Classification of white matter lesions and characteristics of small vessel disease markers
AU - Park, Kyung Il
AU - Jung, Keun Hwa
AU - Lee, Eung Joon
AU - Lee, Woo Jin
AU - Hwang, Seol Ah
AU - Kim, Sohyun
AU - Salat, David H.
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive licence to European Society of Radiology.
PY - 2023/2
Y1 - 2023/2
N2 - 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.
AB - 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.
KW - MRI
KW - Risk factor
KW - Small vessel disease
KW - Type
KW - White matter signal abnormality
UR - http://www.scopus.com/inward/record.url?scp=85136304762&partnerID=8YFLogxK
U2 - 10.1007/s00330-022-09070-1
DO - 10.1007/s00330-022-09070-1
M3 - Article
C2 - 35980432
AN - SCOPUS:85136304762
SN - 0938-7994
VL - 33
SP - 1143
EP - 1151
JO - European Radiology
JF - European Radiology
IS - 2
ER -