Assessment of Cerebral Collateral Flow With Single-Phase Computed Tomography Angiography–Based Multimodal Scales in Patients With Acute Ischemic Stroke
Bibliographic record
Abstract
OBJECTIVE: Assessing collateral status is important in acute ischemic stroke (AIS). The purpose of this study was to establish an easy and rapid method for evaluating collateral flow. METHODS: A total of 60 patients with AIS were enrolled. The patients were aged 18 to 85 years with endovascular therapy treatment within 10 hours after the appearance of stroke symptoms, prestroke modified Rankin Scale ≤1, Alberta Stroke Program Early CT Score ≥6, and the occlusion of large vessels in anterior circulation. We reformed imaging strategies by conducting a small-dose group-injection test before normal computed tomography angiography (CTA) scanning and selected the visual collateral score and the regional leptomeningeal score scales as the single-phase CTA collateral flow assessment scales with the replacement of the parasagittal anterior cerebral artery territory by anterior cerebral artery regions adjacent to the longitudinal fissure and then verified, respectively, the consistencies between the 2 single-phase CTA-based collateral scales and the digital subtraction angiography (DSA)-based American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology scale and compared the prognosis of endovascular therapy between the AIS patients in the poor-collateral-flow group and the other patients' group assessed by 2 single-phase CTA-based collateral scales. RESULTS: There was a high consistency between the 2 single-phase CTA-based collateral flow scales with DSA-based American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology scale. The assessment by using CTA-based collateral flow assessment methods generated consistent results. CONCLUSION: The single-phase CTA-based visual collateral score scale and regional leptomeningeal score scale can be used as the imaging evidence for the evaluation of collateral flow in AIS patients in the majority of grassroots hospitals where DSA is difficult to carry out.
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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 | 0.001 | 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".