Vessel Wall Magnetic Resonance Imaging in Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The aim of the study was to determine the effects of thromboembolism and mechanical thrombectomy on the vessel wall magnetic resonance imaging (VW-MRI) appearance of the intracranial arterial wall. METHODS: This was a cross-sectional study of consecutive patients with acute intracranial arterial occlusion who underwent high-resolution contrast-enhanced VW-MRI within days of stroke presentation. For each patient, we categorized arterial wall thickening and enhancement as definite, possible, or none using contralateral arteries as a reference standard. We performed χ(2) tests to compare the effects of medical therapy and mechanical thrombectomy. RESULTS: Sixteen patients satisfied inclusion criteria. Median time from symptom onset to VW-MRI was 3 days (interquartile range, 2 days). Among 6 patients treated with mechanical thrombectomy using a stent retriever, VW-MRI demonstrated definite arterial wall thickening in 5 (83%) and possible thickening in 1 (17%); there was definite wall enhancement in 4 (67%) and possible enhancement in 2 (33%). Among 10 patients treated with medical therapy alone, VW-MRI demonstrated definite arterial wall thickening in 3 (30%) and possible thickening in 2 (20%); there was definite wall enhancement in 2 (20%) and possible enhancement in 2 (20%). Arterial wall thickening and enhancement were more common in patients treated with mechanical thrombectomy than with medical therapy alone (P=0.037 and P=0.016, respectively). CONCLUSIONS: Mechanical thrombectomy results in intracranial arterial wall thickening and enhancement, potentially mimicking the VW-MRI appearance of primary arteritis. This arterial wall abnormality is less common in patients with arterial occlusion who have been treated with medical therapy alone.
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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".