Measurement of Cerebrovascular Reactivity in Pediatric Patients With Cerebral Vasculopathy Using Blood Oxygen Level-Dependent MRI
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cerebrovascular reactivity (CVR) is an indicator of cerebral hemodynamics. In adults with cerebrovascular disease, impaired CVR has been shown to be associated with an increased risk of stroke. In children, however, CVR studies are not common. This may be due to the difficulties and risks associated with current CVR study methodologies. We have previously described the application of precise control of end-tidal carbon dioxide partial pressure for CVR studies in adults. Our aim is to report initial observations of CVR studies that were performed as part of a larger observational study regarding investigations in pediatric patients with cerebral vascular disease. METHODS: Thirteen patients between the ages of 10 and 16 years (10 with a diagnosis of Moyamoya vasculopathy and 3 with confirmed, or suspected, intracranial vascular stenosis) underwent angiography, MRI, and functional blood oxygen level-dependent MRI mapping of CVR to hypercapnia. The results of the CVR study were then related to both the structural imaging and clinical status. RESULTS: Sixteen blood oxygen level-dependent MRI CVR studies were performed successfully in 13 consecutive patients. Twelve of the 13 patients with angiographic abnormalities also had CVR deficits in the corresponding downstream vascular territories. CVR deficits were also seen in 8 of 9 symptomatic patients and 2 of the asymptomatic patients. Notably, in patients with abnormalities on angiography, the reductions in CVR extended beyond the ischemic lesions identified with MR structural imaging into normal-appearing brain parenchyma. CONCLUSIONS: This is the first case series reporting blood oxygen level-dependent MRI CVR in children with cerebrovascular disease. CVR studies performed so far provide information regarding hemodynamic compromise, which complements traditional clinical assessment and structural imaging.
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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 | 0.000 |
| 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".