P2–203: Relationship between cortical thinning and cortical FDG hypometabolism in individuals with progressive MCI and Alzheimer's disease
Bibliographic record
Abstract
The prevailing theory of the development and progression of Alzheimer disease (AD) is that functional changes precede structural changes in the brain. Although patterns of cortical atrophy and FDG hypometabolism have been shown to be generally similar in AD, few studies have directly compared them. For this purpose, we developed a cortical surface framework that integrated cortical thickness and cortical FDG-PET data analysis in the ADNI-1 cohort. We included baseline scans for these 4 groups: cNC-controls with no ApoE4, Ab1–42>192, Ab1–42/Tau<0.39, sMCI-MCI at baseline and have not progressed, pMCI-MCI at baseline but have progressed to AD, and AD. Cortical thickness was measured by FreeSurfer, and co-registered FDG-PET uptake values with partial volume effect correction were projected on the FreeSurfer surface. We first assessed difference with cNC in cortical thickness and FDG-uptake in each patient group. Cortical regions showing difference in either modality were used to compute z-scores for thickness and FDG-uptake at each surface vertex using cNC as references. To assess the relationship between the two modalities, we computed Pearson correlation coefficients between the z-scores. To assess their differences, we performed paired T-tests between the z-scores. All analyses were performed at each vertex within each group separately, accounting for age, gender, education, and adjusting significance level with FDR (p<0.05). The sMCI did not differ from cNC in any region and modality. In pMCI and AD, frontal, temporal and parietal regions showed similarly severe thinning and FDG-hypometabolism (Figure-A-D: positive correlations, non-significant T-scores). In pMCI, hypometabolism was more severe than thinning in many regions (Figure-C, D, Table: positive T-scores, or Thickness-FDG>0) and thinning was more severe than hypometabolism in many others (Figure-C, D, Table: negative T-scores). In AD this pattern is different: hypometabolism was more severe than thinning in relatively few regions while thinning was more severe than hypometabolism in many.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".