Visualizing Braak stages with deformation‐based morphometry in super‐sampled MRI
Bibliographic record
Abstract
Abstract Background Unlike MRI data, histological data collected post‐mortem can’t be used to study the longitudinal formation of neurofibrillary tangles (NFT) and corresponding brain changes over time for individuals. Although structural MRI offers the possibility of non‐invasive longitudinal antemortem imaging, its resolution is a limiting factor. Using image processing and super‐sampling techniques, we examined the possibility of employing structural MRI to observe the NFT footprints in the brain. Method Data included baseline MRI scans of 1473 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset including ADNI1, 2, and GO. Voxel size was super‐sampled to 0.5×0.5×0.5mm (Manjón et al. 2010) before non‐linear registration to an ADNI‐based unbiased symmetric MRI template. The resulting deformation fields were used to compute the Jacobian determinant map for each subject as a proxy for local volume. For each subject, the sex‐ and age‐corrected z‐scored Jacobian maps were then calculated and averaged for each diagnostic group: normal subjects(CN), early MCI, late MCI, and AD. The average map for CN group was subtracted from the other average maps to show the AD‐stage differences. Result The Braak tau staging pattern (Braak & Braak, 1995) is seen in average Jacobian maps as the disease progresses. Subjects in the MCI groups showed on average more pronounced neurodegeneration in the transentorhinal and entorhinal region (Braak Stages 1‐2), followed by degeneration in the hippocampus (Stages 3‐4). Later on, this neurodegeneration progresses toward the neocortex (Stages 5‐6). Figure 1 illustrates these results: A) the template, B)EMCI vs CN, C) LMCI vs EMCI, D) LMCI vs CN, E) AD vs CN. Red color shows an increase and blue indicates a decrease in local volume. Conclusion Using novel image processing techniques, we were able to verify the staging of AD‐related neurofibrillary pathology progression in MRI data. This shows that structural MRI data, although limited in resolution, can still offer in‐depth insight into the brain antemortem which will in return allow the longitudinal and possible lifespan studies with an accuracy close to histological data.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".