Intracranial Atherosclerotic Plaque Enhancement in Patients with Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Inflammation of an atherosclerotic plaque is a well-known risk factor in the development of ischemic stroke and myocardial infarction. MR imaging is capable of characterizing inflammation by assessing plaque enhancement in both extracranial carotid arteries and coronary arteries. Our goal was to determine whether enhancing intracranial atherosclerotic plaque was present in the vessel supplying the territory of infarction by using high-resolution vessel wall MR imaging. MATERIALS AND METHODS: High-resolution vessel wall 3T MR imaging studies performed in 29 patients with ischemic stroke and intracranial vascular stenoses were reviewed for presence and strength of plaque enhancement. RESULTS: Sixteen patients were studied during the acute phase (<4 weeks from acute stroke), 5 patients in the subacute phase (4-12 weeks), and 8 patients in the chronic phase (>12 weeks) of the ischemic injury. In all of the acute phase patients, atherosclerotic plaque in the vessel supplying the stroke territory demonstrated strong enhancement. There was a trend of decreasing enhancement as the time of imaging relative to the ischemic event increased. CONCLUSIONS: Strong pathologic enhancement of intracranial atherosclerotic plaque was seen in all patients imaged within 4 weeks of ischemic stroke in the vessel supplying the stroke territory. The strength and presence of enhancement of the atherosclerotic plaque decreased with increasing time after the ischemic event. These findings suggest a relationship between enhancing intracranial atherosclerotic plaque and acute ischemic stroke.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".