P1‐417: Cortical atrophy rates in Alzheimer's patients and subjects with mild cognitive impairment from the AddNeuroMed data collection
Bibliographic record
Abstract
Background: The AddNeuroMed project is a multi-centre European project which aims to identify biomarkers in Alzheimer's disease (AD). In this study we measured the rate of cortical atrophy in AD patients, subjects with mild cognitive impairment (MCI), and healthy controls (HC) using MRI. Methods: High resolution sagittal 3D T1w MP-RAGE scans were acquired from patients diagnosed with AD (n = 58,MMSE:21.6 ± 4.4), MCI subjects (n = 85,MMSE:27.2 ± 1.6), and HC (n = 75,MMSE:29.0 ± 1.3) at baseline, and at three and 12 months follow-up. Only subjects with three completed scans which all passed quality control for both the acquisition and image processing were included in the study. Cortical thickness was measured using FACE (fast accurate cortex extraction) and averaged within main lobes using a stereotaxic atlas. Atrophy rates were calculated as percent decrease in cortical thickness and rate differences between groups were evaluated using one tailed t-tests. Results: Cortical atrophy rates for the main lobes at 12 months follow-up are shown in the tables together with p-values for testing group differences. At three months follow-up significantly higher atrophy rates were found in the right temporal and frontal lobe and both occipital lobes in AD compared to HC (p < 0.05). There were no differences in lobar atrophy rates when comparing AD and MCI at three months follow-up, though the right temporal lobe showed a trend towards a higher rate in AD (p = 0.06). MCI subjects showed significantly higher atrophy rates in the left and right occipital lobes compared to HC at three months follow-up (p < 0.02). Conclusions: Atrophy rates based on cortical thickness can be used to measure the progression of cortical neurodegeneration in AD. Based on 12 months observations widespread accelerated atrophy rates can be found in AD patients compared to HC and MCI. Even three months after baseline accelerated atrophy can be observed in AD compared to HC, however, the results indicate that three months is too short a period to distinguish the atrophy rates in AD and MCI. The results suggest that atrophy rates in the occipital lobes can be used to distinguish MCI from HC and atrophy rates in the temporal lobes, especially the right, can be used to distinguish AD from MCI.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".