Effect of White Matter Hyperintensity on Medial Temporal Lobe Atrophy in Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: Medial temporal atrophy (MTA) is a recognized marker of Alzheimer's disease (AD), and white matter hyperintensities (WMH) are frequently observed on MRI of AD. The purpose of this study was to understand the role of WMH in MTA. METHODS: Subjects were 94 probable AD patients and 51 cognitively normal subjects. WMH was assessed based on the severity of deep WMH (DWMH) and periventricular WMH (PWMH). Each structural volume was evaluated using the Individual Brain Atlases from the Statistical Parametric Mapping Toolbox. RESULTS: There were no significant differences between subjects with and without WMH in terms of general cognitive function scales. Subjects with AD with WMH had decreased volume in the bilateral orbital frontal gyrus, frontal rectus gyrus, and olfactory gyrus, but not in the medial temporal lobes. After correcting for differences in DWMH, age and Clinical Dementia Rating Scale (CDR), AD with PWMH showed decreased volumes in the bilateral hippocampi. AD with PWMH showed worse scores on the Clinical Dementia Rating-Sum of Boxes and Barthel-ADL, and some frontal executive function tests. Those with DWMH did not show any reductions in the medial temporal lobes. CONCLUSION: WMH in AD is not associated with medial temporal lobe atrophy, but PWMH is independently correlated with hippocampal volume reduction.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".