Assessment of veins in T2*-weighted MR angiography predicts infarct growth in hyperacute ischemic stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: T2*-weighted magnetic resonance angiography (SWAN) detects hemodynamic insufficiency as hypointense areas in medullary or cortical veins. We therefore investigated whether SWAN can help predict ischemic penumbra-like lesions in patients with acute ischemic stroke (AIS). MATERIALS AND METHODS: Magnetic resonance imaging (MRI) records-including SWAN, diffusion-weighted imaging (DWI), and magnetic resonance angiography (MRA)-of consecutive patients with major vessel occlusion within 6 h from AIS onset were analyzed. Acute recanalization was defined as an arterial occlusive lesion score of 2-3. A modified Alberta Stroke Program Early CT Score (mASPECTS) was used to evaluate ischemic areas revealed by SWAN and DWI. SWAN- and DWI-based mASPECTSs were calculated, and correlations between DWI-SWAN mismatches with final infarct lesions or clinical outcomes were evaluated. RESULTS: Among the 35 patients included in this study, we confirmed cardioembolic stroke in 26, atherothrombotic stroke in 4, and unknown stroke etiology in 5. Overall, recanalization was achieved in 23 patients, who showed a higher follow-up DWI-based mASPECTS and lower modified Rankin Scale (mRS) score at 90 days than patients without recanalization. Initial SWAN- and follow-up DWI-based mASPECTSs were significantly higher for atherothrombotic stroke than for cardioembolic stroke. Of 12 patients without recanalization, DWI-SWAN mismatch was significantly correlated with infarct growth. Patients with recanalization showed no such correlation. In the assessment of clinical outcome, follow-up DWI-based mASPECTS and patient's age were significantly correlated with mRS at 90 days after stroke. A multivariate logistic regression analysis revealed that the follow-up DWI-based mASPECTS was independently associated with a favorable outcome 90 days after stroke. CONCLUSIONS: For patients with AIS, DWI-SWAN mismatch might show penumbra-like lesions that would predict infarct growth without acute recanalization. Assessment of ischemic lesions from the venous side appears to be useful for considering the etiology and revascularization therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".