Alterations of cortical thickness and gray‐white matter contrast in Alzheimer’s disease and Lewy body‐related cognitive impairment
Bibliographic record
Abstract
Abstract Background Gray and white matter alteration has been known in patients with neurodegenerative diseases including Alzheimer’s disease‐ (ADCI) and Lewy body‐related cognitive impairment (LBCI). We examined a distinct pattern of cortical thickness (CTH) and gray‐white matter contrast (GWC) alterations in these degenerative neurological diseases. Since the T1‐weighted MRI signal is closely related to myelin content, the GWC may reflect disease‐related alterations of myeloarchitecture along the cortical surface. Methods T1‐weighted MRIs were obtained from patients (demo‐matched, CDR‐SOB≤9) with ADCI (n=97), LBCI (n=93), and healthy controls (n=37). We measured CTH using the CIVET processing pipeline. GWC was calculated at each vertex as the difference between gray matter (sampled at 50% CTH) and white matter intensity (sampled at 1mm subcortical white matter), then this was normalized by their average. Group differences (controls vs. patients) and correlations (with neuropsychological scores) were examined using general linear models covarying for age, sex, education, intracranial volume, and several vascular risk factors. Results were corrected for multiple comparisons using random field theory p<0.05 (cluster‐forming threshold p=0.001). Results Patients with ADCI showed altered CTH in the brain regions typically affected in AD including the bilateral medial temporal, lateral temporo‐parietal, and posterior cingulate cortices. The pattern of GWC alteration was smaller and no change was shown in the lateral temporal lobe (Figure 1A). LBCI patients showed altered CTH in superior frontal, lateral temporal, basal frontal and occipital cortices. The GWC alteration pattern was shown in larger area, notably in the limbic and occipital cortices (Figure 1B). Memory function, in the AD‐spectrum, was more closely associated with CTH, while in the LB‐spectrum, it was more closely with GWC (Figure 2). Frontal/executive function has stronger association with CTH than with GWC in the AD‐spectrum, while the LB‐spectrum showed independent patterns of association in those measures (Figure 3). The visuospatial function was only associated with CTH in AD‐spectrum, and in LB‐spectrum, it was greater in CTH than in GWC (Figure 4). Conclusions We demonstrated distinct patterns of CTH and GWC alteration in ADCI and LBCI. Consideration of heterogeneous atrophy patterns may be important when planning prevention and treatment strategies, as they may have different responses to treatment in the disease progression.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".