ArticleStroke2021
Heterogeneity of Cerebral White Matter Lesions and Clinical Correlates in Older Adults.
Article in Stroke, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 22 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 31 citations in OpenAlex.
- Age-inappropriate white matter injury reveals hidden cerebral small vessel disease burden and mortality risk.Cerebral circulation - cognition and behavior · 2026Article
- The relationship between white matter hyperintensity and gait in patients with cerebral small vessel disease.Frontiers in neurology · 2026Article
- Heterogeneity of white matter hyperintensities in Alzheimer's disease captured by multimodal neuroimaging.Scientific reports · 2025Article
- Tremor, sensory-motor polyneuropathy and cerebral gliosis in klinefelter's syndrome.Acta neurologica Belgica · 2025Article
- Domain-specific longitudinal associations between brain volume, white matter lesions, and cognitive function changes.Heliyon · 2025Article
- Pathophysiological link between carotid atherosclerosis and cerebral white matter lesions.Scientific reports · 2025Article
- Impaired kidney function, cerebral small vessel disease and cognitive disorders: the Framingham Heart Study.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024Article
- The Different Associations of White Matter Hyperintensities With Severity of Dementia and Cognitive Impairment According to the Distance From the Lateral Ventricular Surface in Patients With Alzheimer's Disease.Psychiatry investigation · 2024Article
- Leukoaraiosis: Epidemiology, Imaging, Risk Factors, and Management of Age-Related Cerebral White Matter Hyperintensities.Journal of stroke · 2024Review
- Specialized gray matter segmentation via a generative adversarial network: application on brain white matter hyperintensities classification.Frontiers in neuroscience · 2024Article
- Associations between cerebral blood flow and progression of white matter hyperintensities.Frontiers in neuroimaging · 2024Article
- Blood-Brain Barrier Breakdown is a Sensitive Biomarker of Cognitive and Language Impairment in Patients with White Matter Hyperintensities.Neurology and therapy · 2023Article
- Mechanical loading of the ventricular wall as a spatial indicator for periventricular white matter degeneration.Journal of the mechanical behavior of biomedical materials · 2023Article
- Characteristics and Clinical Implication of White Matter Lesions in Patients With Adult Moyamoya Disease.Neurology · 2023Article
- Biomarkers of aging.Science China. Life sciences · 2023Review
- Heterogeneity of White Matter Hyperintensity and Cognitive Impairment in Patients with Acute Lacunar Stroke.Brain sciences · 2022Article
- Cortical Short-Range Fiber Connectivity and Its Association With Deep Brain White Matter Hyperintensities in Older Diabetic People With Low Serum Vitamin BFrontiers in aging neuroscience · 2022Article
- Fluid-attenuated inversion recovery magnetic resonance imaging textural features as sensitive markers of white matter damage in midlife adults.Brain communications · 2022Article
- Segmentation of white matter lesions in multicentre FLAIR MRI.Neuroimage. Reports · 2021Article
- Heterogeneity of White Matter Hyperintensities in Cognitively Impaired Patients With Cerebral Small Vessel Disease.Frontiers in immunology · 2021Article
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
7 authors at 5 institutions in 3 countries.
Funding
Abstract
background and purposeCerebral white matter signal abnormalities (WMSAs) are a significant radiological marker associated with brain and vascular aging. However, understanding their clinical impact is limited because of their pathobiological heterogeneity. We determined whether use of robust reliable automated procedures can distinguish WMSA classes with different clinical consequences.
methodsData from generally healthy participants aged >50 years with moderate or greater WMSA were selected from the Human Connectome Project-Aging (n=130). WMSAs were segmented on T1 imaging. Features extracted from WMSA included total and regional volume, number of discontinuous clusters, size of noncontiguous lesion, contrast of lesion intensity relative to surrounding normal appearing tissue using a fully automated procedure. Hierarchical clustering was used to classify individuals into distinct classes of WMSA. Radiological and clinical variability was evaluated across the individual WMSA classes.
resultsClass I was characterized by multiple, small, lower-contrast lesions predominantly in the deep WM; class II by large, confluent lesions in the periventricular WM; and class III by higher-contrast lesions restricted to the juxtaventricular WM. Class II was associated with lower myelin content than the other 2 classes. Class II was more prevalent in older subjects and was associated with a higher prevalence of hypertension and lower physical activity levels. Poor sleep quality was associated with a greater risk of class I.
conclusionsWe classified heterogeneous subsets of cerebral white matter lesions into distinct classes that have different clinical risk factors. This new method for identifying classes of WMSA will be important in understanding the underlying pathophysiology and in determining the impact on clinical outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.