Gray and white matter changes in Alzheimer's disease: A diffusion tensor imaging study
Bibliographic record
Abstract
PURPOSE: To investigate microstructural changes in cortical and white matter pathways in patients with Alzheimer's disease using diffusion tensor imaging (DTI). MATERIALS AND METHODS: Measures of mean diffusivity (MD) and fractional anisotropy (FA) were compared in the brains of 13 Alzheimer's disease (AD) patients and a group of 13 aged-matched control participants employing an optimized DTI technique involving a fully automated, voxel-based morphometric (VBM) analysis. RESULTS: After rigorous control for anatomical variation and confounding partial volume effects, we found significantly elevated MD measures within the hippocampus, amygdala, and medial temporal, parietal, and frontal lobe gray matter regions in the AD participants. The largest number of pixels with increased MD was localized bilaterally, within the posterior cingulate gyrus. The FA was significantly reduced within the thalamus, parietal white matter, and posterior limbs of the internal capsule, indicating significant involvement of corticothalamic and thalamocortical radiations. CONCLUSION: This study demonstrates that rigorous VBM analysis of DTI data can be used to investigate microstructural changes in cortical, subcortical, and white matter regions in AD.
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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 | 0.001 |
| 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) | 0.001 | 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".