IC‐03‐05: Estimating the impact of differences among protocols for manual hippocampal segmentation on Alzheimer's disease‐related atrophy: Preparatory phase for a harmonized protocol
Bibliographic record
Abstract
To quantify the impact of the differences among Magnetic Resonance Imaging (MRI)-based hippocampal segmentation protocols on volume estimates of Alzheimer's disease (AD)-related atrophy, in order to support evidence-based decisions for an internationally harmonized protocol. A harmonized procedure is required, since quantitative MRI should help diagnosis and tracking of AD. A survey of segmentation protocols allowed to operationalize the landmarks variability into segmentation units (SUs) (Figure), and their impact on volume estimates has been preliminarily quantified. A power analysis was carried out on a preliminary sample, to define the sample size allowing reliable computation. Then, we manually traced each SU within the right and left hippocampi of a larger sample of Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, which included Mild Cognitive Impairment (MCI) patients who subsequently converted to AD and AD patients, all with abnormal Cerebrospinal Fluid (CSF) Aß levels, and controls (CTRL), with normal CSF Aß levels. The power analysis indicated a required sample size for the quantification of SUs impact on AD-related volume differences of n=77 (31 CTRL, 23 MCI, 23 AD). So far, 40 subjects (16 CTRL, 12 MCI, 12 AD) have been traced and analyzed. The minimum hippocampal body (red SU in Figure) accounted for over 62% of AD-related volume difference across groups (left: 68.5%, right: 62%, p<0.001); the left alveus/fimbria (yellow SU in Figure) for 7.5% (p=0.01) and the right alveus/fimbria for 3% (p=0.7); the subiculum (green SUs in Figure) for 5% bilaterally (left: p=0.08; right: p=0.03); the left tail (blue SUs in Figure) for 19% (p=0.003), and the right tail for the 30% (p=0.001) of the global difference across groups. 3D rendering of segmentation units (SUs) as traced out from the right hippocampus of a normal subject. SUs represent the differences in tracing criteria among protocols.7 Red = minimum hippocampal body, common to all protocols; Yellow = alveus/fimbria; Green = different criteria to trace the medial border at the level of the subiculum; Blue = different criteria to trace the most caudal portion (tail).
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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 | 0.160 | 0.206 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".