<p>Structural changes in white matter lesion patients and their correlation with cognitive impairment</p>
Bibliographic record
Abstract
Background: White matter lesions (WMLs) play a role in cognitive decline and dementia. Little is known about gray matter (GM) changes in WMLs. This study aimed to investigate GM changes in WML patients. Materials and methods: Correlations between altered structural volume and cognitive assessment scores were investigated. GM and white matter (WM) changes in 23 WML-vascular dementia (VaD) patients, 22 WML-non-dementia vascular cognitive impairment (VCIND) patients, and 23 healthy control (HC) subjects were examined. Gray matter density (GMD) was calculated by measuring local proportions of GM at thousands of homologous cortical locations. WM volume was obtained by fully automated software using voxel-based morphometry (VBM). Results: Widespread GMD was significantly lower in WML patients compared to control subjects in cortical and subcortical regions ( p <0.05). Greatest differences were found in the bilateral anterior cingulate cortex, inferior frontal gyrus, insula, angular gyrus, caudate, precentral gyrus, and right middle temporal gyrus, right thalamus. Secondary region of interest (ROI) analysis indicated significantly greater GMD in the bilateral caudate among WML-VCIND patients (n=22) compared to HCs ( p <0.05). There was a significant difference in WM volume between WML patients and control subjects ( p <0.05). Greatest differences were located in the genu/body/splenium of the corpus callosum and superior corona radiata L, and posterior corona radiata L. There was a significant association between structural changes and cognitive scores (Montreal Cognitive Assessment [MoCA] score) ( p <0.05). There was no significant correlation between structural changes and Mini Mental State Examination (MMSE) scores ( p >0.05). Conclusion: GMD and WM volume were changed in WMLs, and the changes were detectable. Correlation between structural changes and cognitive function was promising in understanding the pathological and physiological mechanisms of WMLs. Keywords: white matter lesions, vascular dementia, gray matter density, dementia
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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".