Predicting Stroke Risk in Pediatric Moyamoya Disease with Xenon-enhanced Computed Tomography
Bibliographic record
Abstract
OBJECTIVE: To determine whether estimates of regional cerebral blood flow (rCBF) using xenon computed tomography (XeCT) in children with moyamoya disease can predict stroke risk before and after treatment. METHOD: Seven patients with moyamoya disease underwent 22 serial Xe computed tomographic scans. Estimates of rCBF were obtained at three computed tomographic levels by use of a 5-minute inhalation of 28% Xe. Acetazolamide challenge was performed in eight scans. For comparison of abnormal vessel distribution and areas of infarction, 17 intra-arterial digital subtraction angiograms, 47 computed tomographic scans, and 15 magnetic resonance imaging scans were available. Follow-up exceeded 36 months in all patients. Mean follow-up for the interventional group was 65.2 months (n = 5; range, 37-109 mo) and 38 months for the nonoperative patients (n = 2; 36 and 40 mo). RESULTS: Of six Xe computed tomographic scans obtained at diagnosis, four revealed regions of oligemia, augmented vertebrobasilar flow, and regions of carotid steal after acetazolamide. In the delay between diagnosis and treatment, three patients had strokes in ischemic areas identified by XeCT. Of the 10 posttreatment scans obtained from 4 patients, 2 revealed improved tissue perfusion with angiography confirming successful encephaloduroangiomyosynangiosis. In 2 others, XeCT performed 6 months posttreatment revealed improved perfusion without angiographic change, and angiography at 1 year revealed failed encephaloduroangiomyosynangiosis and new native collaterals. None of the patients with improved rCBF had new strokes. Eleven of 14 Xe computed tomographic scans were obtained within 30 days of angiography. Comparison of these studies demonstrates that regions of oligemia were confined to areas associated with vessel stenosis and little neovascularity or collateral pathways. CONCLUSION: XeCT, particularly with acetazolamide challenge, objectively quantifies rCBF. Our preliminary data suggest that it may permit assessment of stroke risk in children with moyamoya disease and may predict surgical outcome earlier than angiography.
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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 | 0.001 | 0.001 |
| 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".