White Matter Hyperintensities, Grey Matter Atrophy, and Cognitive Decline in Neurodegenerative Diseases
Bibliographic record
Abstract
Abstract Introduction White matter hyperintensities (WMHs) as seen on T2w and FLAIR scans represent small-vessel disease related changes in the brain. WMHs are associated with cognitive decline in the normal aging population in general and more specifically in patients with neurodegenerative diseases. In this study, we assessed the different spatial patterns and relationships between WMHs and grey matter (GM) atrophy in normal aging, individuals with mild cognitive impairment (MCI), Alzheimer’s dementia (AD), fronto-temporal dementia (FTD), and de novo Parkinson’s disease (PD). Methods Imaging and clinical data were obtained from 3 large multi-center databases: The Alzheimer’s Disease Neuroimaging Initiative (ADNI), the frontotemporal lobar degeneration neuroimaging initiative (NIFD), and the Parkinson’s Progression Markers Initiative (PPMI). WMHs and GM atrophy maps were measured in normal controls (N= 571), MCI (N= 577), AD (N= 222), FTD (N= 144), and PD (N= 363). WMHs were segmented using T1w and T2w/PD or FLAIR images and mapped onto 45 white matter tracts using the Yeh WM atlas. GM volume was estimated from the Jacobian determinant of the nonlinear deformation field required to map the subject’s MRI to a standard template. The CerebrA atlas was used to obtain volume estimates in 84 GM regions. Mixed effects models were used to compare WMH in different WM tracts and volume of multiple GM structures between patients and controls, assess the relationship between regional WMHs and GM loss for each disease, and investigate their impact on cognition. Results MCI, AD, and FTD patients had significantly higher WMH loads than the matched controls. There was no significant difference in WMHs between PD and controls. For each cohort, significant interactions between WMH load and GM atrophy were found for several regions and tracts, reflecting additional contribution of WMH burden to GM atrophy. While these associations were more relevant for insular and parieto-occipital regions in MCI and AD cohorts, WMH burden in FTD subjects had greater impact on frontal and basal ganglia atrophy. Finally, we found additional contribution of WMH burden to cognitive deficits in AD and FTD subjects compared with matched controls, whereas their impact on cognitive performance in MCI and PD were not significantly different from controls. Conclusions WMHs occur more extensively in MCI, AD, and FTD patients than age-matched normal controls. WMH burden on WM tracts also correlates with regional GM atrophy in regions anatomically and functionally related to those tracts, suggesting a potential involvement of WMHs in the neurodegenerative process.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".