Prominent Vessel Sign on Susceptibility-Weighted Imaging in Acute Stroke: Prediction of Infarct Growth and Clinical Outcome
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Predicting the risk of further infarct growth in stroke patients is critical to therapeutic decision making. We aimed to predict early infarct growth and clinical outcome from prominent vessel sign (PVS) identified on the first susceptibility-weighted image (SWI) after acute stroke. MATERIALS AND METHODS: Twenty-two patients with middle cerebral artery (MCA) infarction had diffusion-weighted imaging, SWI, MR angiography, and clinical evaluation using the National Institutes of Health Stroke Scale at 7-60 hours and 5-14 days after stroke onset. Late-stage clinical evaluation at 1 and 3 months used the modified Rankin Scale. The infarct area and growth were scored from 10 (none) to 0 (infarct or growth in all 10 zones) using the Alberta Stroke Program Early CT Score (ASPECTS) system. RESULTS: Infarct growth on the second MRI occurred in 13 of 15 patients with PVS on the first MRI and not in any patient without PVS (n=7; r=0.86, P<0.001). The extent of PVS was significantly correlated with infarct growth (r=0.82, P<0.001) and early-stage outcome (P=0.02). No between-group difference in late-stage clinical outcome was found. CONCLUSION: PVS on the first SWI after acute MCA territory stroke is a useful predictor of early infarct growth. Extensive PVS within the large MCA territory is related to poor early-stage outcome and could be useful for clinical assessment of 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 | 0.000 |
| 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".