Cortical thickness in clinical moyamoya disease: A magnetic resonance imaging study
Bibliographic record
Abstract
Moyamoya disease (MMD) is a progressive cerebrovascular disorder, with an unknown pathogenesis and aetiology. MMD is characterized by steno-occlusive changes at the terminal portion of the internal carotid artery (ICA), which is accompanied by variable development of the basal collaterals, also known as moyamoya vessels. Patients with MMD show variable patterns of brain damage and may experience recurrent multiple transient ischaemic attacks, intracranial bleeding and cerebral infarction. In this study, we investigate the potential for structural T1 magnetic resonance imaging (MRI) to help characterize abnormal cortical development in MMD clinically, with an analysis of both average and variability of regional cortical thicknesses. This study also included a machine learning analysis to assess the predictive capacity of the cortical thickness abnormalities observed in this research. This study included 993 MRI examinations from neurotypical controls and 269 MRI examinations from MMD patients. Results demonstrate abnormal cortical presentation of the insula, caudate, postcentral, precuneus and cingulate regions, in agreement with previous literature cortical thickness findings as well as alternative methods such as functional MRI (fMRI) and digital angiography. To the best of our knowledge, this is the first manuscript to report cortical thickness abnormalities in the middle temporal visual area in MMD and the first study to report on cortical thickness variability abnormalities in MMD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".