Association of Data-Driven White Matter Hyperintensity Spatial Signatures With Distinct Cerebral Small Vessel Disease Etiologies
Document Type
Article
Abstract
BACKGROUND AND OBJECTIVES: Topographical distribution of white matter hyperintensities (WMH) are hypothesized to vary by cerebrovascular risk factors. We used an unbiased pattern discovery approach to identify distinct WMH spatial patterns and investigate their association with different WMH etiologies. METHODS: We performed a cross-sectional study on participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) to identify spatially distinct WMH distribution patterns using voxel-based spectral clustering analysis of aligned WMH probability maps. We included all participants from the ADNI Grand Opportunity/ADNI 2 study with available baseline 2D-FLAIR MRI scans, without history of stroke or presence of infarction on imaging. We evaluated the associations of these WMH spatial patterns with vascular risk factors, amyloid-β PET, and imaging biomarkers of cerebral amyloid angiopathy (CAA), characterizing different forms of cerebral small vessel disease (CSVD) using multivariable regression. We also used linear regression models to investigate whether WMH spatial distribution influenced cognitive impairment. RESULTS: We analyzed MRI scans of 1,046 ADNI participants with mixed vascular and amyloid-related risk factors (mean age 72.9, 47.7% female, 31.4% hypertensive, 48.3% with abnormal amyloid PET). We observed unbiased partitioning of WMH into 5 unique spatial patterns: deep frontal, periventricular, juxtacortical, parietal, and posterior. Juxtacortical WMH were independently associated with probable CAA, deep frontal WMH were associated with risk factors for arteriolosclerosis (hypertension and diabetes), and parietal WMH were associated with brain amyloid accumulation, consistent with an Alzheimer disease (AD) phenotype. Juxtacortical, deep frontal, and parietal WMH spatial patterns were associated with cognitive impairment. Periventricular and posterior WMH spatial patterns were unrelated to any disease phenotype or cognitive decline. DISCUSSION: Data-driven WMH spatial patterns reflect discrete underlying etiologies including arteriolosclerosis, CAA, AD, and normal aging. Global measures of WMH volume may miss important spatial distinctions. WMH spatial signatures may serve as etiology-specific imaging markers, helping to resolve WMH heterogeneity, identify the dominant underlying pathologic process, and improve prediction of clinical-relevant trajectories that influence cognitive decline.
Medical Subject Headings
Humans; Female; Male; Alzheimer Disease (pathology); White Matter (pathology); Cross-Sectional Studies; Arteriolosclerosis (complications); Cerebral Amyloid Angiopathy (complications, diagnostic imaging, pathology); Magnetic Resonance Imaging; Cognitive Dysfunction (pathology); Cerebral Small Vessel Diseases (complications, diagnostic imaging, pathology)
Publication Date
12-5-2022
Publication Title
Neurology
E-ISSN
1526-632X
Volume
99
Issue
23
First Page
e2535
Last Page
e2547
PubMed ID
36123127
Digital Object Identifier (DOI)
10.1212/WNL.0000000000201186
Recommended Citation
Phuah, Chia-Ling; Chen, Yasheng; Strain, Jeremy F.; Yechoor, Nirupama; Laurido-Soto, Osvaldo J.; Ances, Beau M.; and Lee, Jin-Moo, "Association of Data-Driven White Matter Hyperintensity Spatial Signatures With Distinct Cerebral Small Vessel Disease Etiologies" (2022). Neurology. 1713.
https://scholar.barrowneuro.org/neurology/1713