Fractional Flow on TOF-MRA as a Measure of Stroke Risk in Children with Intracranial Arterial Stenosis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Conventional angiography is the criterion standard for measuring intracranial arterial stenosis. We evaluated signal intensity ratios from TOF-MRA as a measure of intracranial stenosis and infarct risk in pediatric stroke. MATERIALS AND METHODS: A retrospective study was undertaken in children with intracranial arterial stenosis, who had TOF-MRA and conventional angiography performed within 6 months. Arterial diameters were measured for percentage stenosis. ROI analysis on TOF-MRA measured signal intensity in pre- and poststenotic segments, with post-/pre-signal intensity ratios calculated. The Pearson correlation was used to compare percentage stenosis on MRA with conventional angiography and signal intensity ratios with percentage stenosis; the point-biserial correlation was used for infarcts compared with percentage stenosis and signal intensity ratios. Sensitivity, specificity, and positive and negative predictive values were calculated for determining severe (≥70%) stenosis from MRA and signal intensity ratios against the criterion standard conventional angiography. P < .05 was considered statistically significant. RESULTS: Seventy stenotic segments were found in 48 studies in 41 children (median age, 11.0 years; range, 5 months to 17.0 years; male/female ratio, 22:19): 20/41 (48.8%) bilateral, 11/41 (26.8%) right, and 10/41 (24.4%) left, with the most common site being the proximal middle cerebral artery (22/70, 31%). Moyamoya disease accounted for 27/41 (65.9%). Signal intensity ratios and conventional angiography stenosis showed a moderate negative correlation (R = –0.54, P < .001). Receiver operating characteristic statistics showed an area under the curve of 0.86 for using post-/pre-signal intensity ratios to determine severe (≥70%) carotid stenosis, yielding a threshold of 1.00. Sensitivity, specificity, and positive and negative predictive values for severe stenosis were the following—MRA: 42.8%, 58.8%, 30.0%, and 71.4%; signal intensity ratio >1.00: 97.1%, 77.8%, 71.7%, and 97.4%; combination: 75.5%, 100%, 100%, and 76.8%, respectively. Signal intensity ratios decreased with increasing grade of stenosis (none/mild-moderate/severe/complete, P < .001) and were less when associated with infarcts (0.81 ± 0.52 for arteries associated with downstream infarcts versus 1.31 ± 0.55 for arteries without associated infarcts, P < .001). CONCLUSIONS: Signal intensity ratios from TOF-MRA can serve as a noninvasive measure of intracranial arterial stenosis and allow identification of high-risk lesions in pediatric stroke.
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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".