Structural changes in white matter lesion patients and their correlation with cognitive impairment
Bibliographic record
Abstract
Jinfang Wang,1,2 Yi Liang,2 Hongyan Chen,1 Wanming Wang,2 Yanwen Wang,2 Ying Liang,3 Yumei Zhang1,4 1Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China; 2Department of Neurology, General Hospital of The Yang Tze River Shipping, Wuhan Brain Hospital, Wuhan 430000, China; 3School of Biomedical Engineering, Capital Medical University, Beijing 100050, China; 4Department of Rehabilitation Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China 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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".