ArticleNeuroImage. Clinical2022
Determining the OPTIMAL DTI analysis method for application in cerebral small vessel disease.
Article in NeuroImage. Clinical, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 27 citations in OpenAlex.
- Regional diffusion imaging measures to disentangle SVD-related hypertensive arteriopathy versus cerebral amyloid angiopathy.Molecular neurodegeneration · 2026Article
- Evaluating regional and global diffusion measures as biomarkers for vascular contributions to cognitive impairment and dementia.Cerebral circulation - cognition and behavior · 2026Article
- Remote cortical degeneration related to structural connectivity following recent small subcortical infarcts.NeuroImage. Clinical · 2026Article
- Cognitive reserve mitigates cognitive impairment in cerebral small vessel disease by protecting white matter fibers: an automated fiber quantification study.Brain imaging and behavior · 2025Article
- Blood pressure and the brain: the conundrum of hypertension and dementia.Cardiovascular research · 2025Review
- Emerging biomarkers and frontier therapies: unveiling the role of endothelial dysfunction in cerebral small vessel disease.Frontiers in neurology · 2025Review
- Biological validation of peak-width of skeletonized mean diffusivity as a VCID biomarker: The MarkVCID Consortium.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Two-Stage Recruitment Design to Reduce Magnetic Resonance Imaging Screening Cost for a Theoretical Clinical Trial of White Matter Hyperintensity Progression.Journal of the American Heart Association · 2024Article
- Loss of white matter integrity mediates the association between cortical cerebral microinfarcts and cognitive dysfunction: A longitudinal study.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2024Article
- Locus coeruleus microstructural integrity is associated with vigilance vulnerability to sleep deprivation.Human brain mapping · 2024Article
- Association ofNeurology · 2024Article
- Vascular risk, gait, behavioral, and plasma indicators of VCID.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Diffusion tensor imaging in cerebral small vessel disease applications: opportunities and challenges.Frontiers in neuroscience · 2024Review
- Blood pressure-related white matter microstructural disintegrity and associated cognitive function impairment in asymptomatic adults.Stroke and vascular neurology · 2023Article
- The association of diffusion tensor MRI measures of normal appearing white matter and cognition.Cerebral circulation - cognition and behavior · 2023Article
- Cerebral small vessel disease: Recent advances and future directions.International journal of stroke : official journal of the International Stroke Society · 2023Review
- Predicting incident dementia in cerebral small vessel disease: comparison of machine learning and traditional statistical models.Cerebral circulation - cognition and behavior · 2023Article
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Authors and funding
16 authors at 10 institutions in 6 countries.
Funding
Abstract
backgroundDTI is sensitive to white matter (WM) microstructural damage and has been suggested as a surrogate marker for phase 2 clinical trials in cerebral small vessel disease (SVD). The study's objective is to establish the best way to analyse the diffusion-weighted imaging data in SVD for this purpose. The ideal method would be sensitive to change and predict dementia conversion, but also straightforward to implement and ideally automated. As part of the OPTIMAL collaboration, we evaluated five different DTI analysis strategies across six different cohorts with differing SVD severity.
methodsThose 5 strategies were: (1) conventional mean diffusivity WM histogram measure (MD median), (2) a principal component-derived measure based on conventional WM histogram measures (PC1), (3) peak width skeletonized mean diffusivity (PSMD), (4) diffusion tensor image segmentation θ (DSEG θ) and (5) a WM measure of global network efficiency (Geff). The association between each measure and cognitive function was tested using a linear regression model adjusted by clinical markers. Changes in the imaging measures over time were determined. In three cohort studies, repeated imaging data together with data on incident dementia were available. The association between the baseline measure, change measure and incident dementia conversion was examined using Cox proportional-hazard regression or logistic regression models. Sample size estimates for a hypothetical clinical trial were furthermore computed for each DTI analysis strategy.
resultsThere was a consistent cross-sectional association between the imaging measures and impaired cognitive function across all cohorts. All baseline measures predicted dementia conversion in severe SVD. In mild SVD, PC1, PSMD and Geff predicted dementia conversion. In MCI, all markers except Geff predicted dementia conversion. Baseline DTI was significantly different in patients converting to vascular dementia than to Alzheimer' s disease. Significant change in all measures was associated with dementia conversion in severe but not in mild SVD. The automatic and semi-automatic measures PSMD and DSEG θ required the lowest minimum sample sizes for a hypothetical clinical trial in single-centre sporadic SVD cohorts.
conclusionDTI parameters obtained from all analysis methods predicted dementia, and there was no clear winner amongst the different analysis strategies. The fully automated analysis provided by PSMD offers advantages particularly for large datasets.
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