ArticleStroke2018
Texture Analysis of T1-Weighted and Fluid-Attenuated Inversion Recovery Images Detects Abnormalities That Correlate With Cognitive Decline in Small Vessel Disease.
Article in Stroke, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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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
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning applications in vascular neuroimaging for the diagnosis and prognosis of cognitive impairment and dementia: a systematic review and meta-analysis.Alzheimer's research & therapy · 2025Pooled it
- Exploratory SWI-based texture analysis of the substantia nigra on MRI in parkinson's disease.Medicine · 2026Article
- Radiomics models identifying dementia in patients with normal age-related hippocampal atrophy: a study based on machine learning.BMC geriatrics · 2025Article
- Deep adaptive learning predicts and diagnoses CSVD-related cognitive decline using radiomics from TNPJ digital medicine · 2025Article
- Application of Radiomics in Predicting the Prognosis of Medulloblastoma in Children.Children (Basel, Switzerland) · 2025Article
- Comparison of T2W FLAIR Images of Patients with Multiple Sclerosis and Ischemic Gliosis via Histogram Analysis.Journal of clinical practice and research · 2023Article
- The Relevance of Serum Macrophage Migration Inhibitory Factor Level and Executive Function in Patients with White Matter Hyperintensity in Cerebral Small Vessel Disease.Brain sciences · 2023Article
- Texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic stroke.Frontiers in neurology · 2023Article
- Superficial white matter microstructure affects processing speed in cerebral small vessel disease.Human brain mapping · 2022Article
- Delusional Severity Is Associated with Abnormal Texture in FLAIR MRI.Brain sciences · 2022Article
- Of differing methods, disputed estimates and discordant interpretations: the meta-analytical multiverse of brain volume and IQ associations.Royal Society open science · 2022Article
- Research progress on cognitive impairment and the expression of serum inflammatory markers in patients with white matter hyperintensities: a narrative review.Annals of translational medicine · 2022Review
- Fluid-attenuated inversion recovery magnetic resonance imaging textural features as sensitive markers of white matter damage in midlife adults.Brain communications · 2022Article
- Diagnosis of Subcortical Ischemic Vascular Cognitive Impairment With No Dementia Using Radiomics of Cerebral Cortex and Subcortical Nuclei in High-Resolution T1-Weighted MR Imaging.Frontiers in oncology · 2022Article
- Cerebral Small Vessel Disease: Neuroimaging Features, Biochemical Markers, Influencing Factors, Pathological Mechanism and Treatment.Frontiers in neurology · 2022Review
- TJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2021Article
- Contribution of Inflammation and Hypoperfusion to White Matter Hyperintensities-Related Cognitive Impairment.Frontiers in neurology · 2021Article
- Comparing the Performance of Two Radiomic Models to Predict Progression and Progression Speed of White Matter Hyperintensities.Frontiers in neuroinformatics · 2021Article
- FLAIR and ADC Image-Based Radiomics Features as Predictive Biomarkers of Unfavorable Outcome in Patients With Acute Ischemic Stroke.Frontiers in neuroscience · 2021Article
- MRI Radiomic Signature of White Matter Hyperintensities Is Associated With Clinical Phenotypes.Frontiers in neuroscience · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
background and purposeMagnetic resonance imaging may be useful to assess disease severity in cerebral small vessel disease (SVD), identify those individuals who are most likely to progress to dementia, monitor disease progression, and act as surrogate markers to test new therapies. Texture analysis extracts information on the relationship between signal intensities of neighboring voxels. A potential advantage over techniques, such as diffusion tensor imaging, is that it can be used on clinically obtained magnetic resonance sequences. We determined whether texture parameters (TP) were abnormal in SVD, correlated with cognitive impairment, predicted cognitive decline, or conversion to dementia.
methodsIn the prospective SCANS study (St George's Cognition and Neuroimaging in Stroke), we assessed TP in 121 individuals with symptomatic SVD at baseline, 99 of whom attended annual cognitive testing for 5 years. Conversion to dementia was recorded for all subjects during the 5-year period. Texture analysis was performed on fluid-attenuated inversion recovery and T1-weighted images. The TP obtained from the SVD cohort were cross-sectionally compared with 54 age-matched controls scanned on the same magnetic resonance imaging system.
resultsThere were highly significant differences in several TP between SVD cases and controls. Within the SVD population, TP were highly correlated to other magnetic resonance imaging parameters (brain volume, white matter lesion volume, lacune count). TP correlated with executive function and global function at baseline and predicted conversion to dementia, after controlling for age, sex, premorbid intelligence quotient, and magnetic resonance parameters.
conclusionsTP, which can be obtained from routine clinical images, are abnormal in SVD, and the degree of abnormality correlates with executive dysfunction and global cognition at baseline and decline during 5 years. TP may be useful to assess disease severity in clinically collected data. This needs testing in data clinically acquired across multiple sites.
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