The White Matter Hyperintensity Shape and Brain Clearance (WHIMAS) Study for Identification of Novel 7T Magnetic Resonance Imaging Markers of Cerebral Small Vessel Disease: Protocol for a Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Sporadic cerebral small vessel disease (SVD) has a heterogeneous underlying pathology, and current SVD magnetic resonance imaging (MRI) markers do not accurately capture this heterogeneity. Novel ultrahigh-field (7T) brain MRI markers provide a window of opportunity to study early changes and potential determinants of SVD. White matter hyperintensity (WMH) shape is a relatively novel MRI marker of SVD and has shown prognostic potential. However, the exact microstructural changes within or surrounding WMHs or potential causes related to WMH shape variations are unknown. Furthermore, impaired brain clearance via the recently discovered brain clearance system may be another early change or potential cause of SVD. OBJECTIVE: In the White Matter Hyperintensity Shape and Brain Clearance (WHIMAS) study, we aim to assess the link between WMHs-their shape in particular-and brain clearance and other MRI markers on ultrahigh-field (7T) brain MRI and show whether these markers are associated with cognitive functioning in older adults with memory complaints. METHODS: This is a cross-sectional study conducted at the Leiden University Medical Center. A total of 50 outpatients from the memory or geriatric clinic aged ≥65 years will be recruited for a 3T and 7T MRI scan (including clinical structural scans, eg, 3D T1-weighted, 3D fluid-attenuated inversion recovery), and experimental scans such as cerebrospinal fluid (CSF)-selective T2-prepared readout with acceleration and mobility encoding (CSF-STREAM) and the relationship between blood oxygen level-dependent [BOLD] signals and CSF flow) and magnetic resonance fingerprinting, as well as a standardized neuropsychological test battery (domains: memory, executive function, visuoconstruction, and processing speed). We will assess WMH shape markers (solidity, convexity, concavity index, fractal dimension, and eccentricity) and brain clearance markers (CSF mobility and the relationship between blood oxygen level-dependent signals and CSF flow) and study their relationship to other MRI markers and cognitive functioning using multivariable regression analyses. RESULTS: Patient inclusion started in January 2023, and study enrollment of patients is expected to finish in the second quarter of 2027, whereas the main results are expected to be published in the first quarter of 2028. CONCLUSIONS: We aim to understand variations in WMH shape and find their relationship to cerebral SVD and markers of brain clearance and cognitive functioning. WMH shape and brain clearance markers early in the disease process of SVD are extremely important as they may represent a basis for future patient selection for lifestyle interventions or for treatment trials aimed at the prevention of dementia. TRIAL REGISTRATION: ClinicalTrials.gov NCT06010511; https://clinicaltrials.gov/study/NCT06010511. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/77681.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".