White Matter Changes are Associated with Ventricular Expansion in Aging, Mild Cognitive Impairment, and Alzheimer’s Disease
Bibliographic record
Abstract
White matter lesions are highly prevalent in individuals with Alzheimer's disease (AD). Although these lesions are presumed to be of vascular origin and linked to small vessel disease in older adults, little information exists about their relationship to markers of classical AD neurodegeneration. Thus, we examined the link between these white matter changes (WMC) segmented on T1-weighted MRI and imaging markers presumed to be altered due to primary AD neurodegenerative processes. Tissue microstructure of WMC was quantified using diffusion tensor imaging and the relationship of WMC properties and volume to neuroimaging markers was examined in 219 cognitively healthy older adults and individuals with mild cognitive impairment and AD using data from the Alzheimer's Disease Neuroimaging Initiative. No significant group differences in WMC properties were found. However, there were strong associations between diffusivity of WMC and ventricular volume, volume of WMC and total WM volume. In comparison, group differences in parahippocampal white matter microstructure were found for all diffusion metrics and were largely explained by hippocampal volume. Factor analysis on neuroimaging markers suggested two independent sets of covarying degenerative changes, with potentially age- and vascular-mediated tissue damage contributing to one factor and classical neurodegenerative changes associated with AD contributing to a second factor. These data demonstrate two potentially distinct classes of degenerative change in AD, with one factor strongly linked to aging, ventricular expansion, and both volume and tissue properties of white matter lesions, while the other factor related to classical patterns of cortical and hippocampal neurodegeneration in AD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".