Correlation between dual-phase CTA-SI ASPECTS and automated CT perfusion imaging in patients with acute ischemic stroke beyond the 6-hour window
Bibliographic record
Abstract
Background: There is controversy regarding the need to use advanced imaging to select candidates for thrombectomy in late window acute ischemic stroke (AIS).Hypoattenuation on CT angiography source images (CTA-SI) in arterial phase has been shown to be more sensitive than Alberta Stroke Program Early CT Score (ASPECTS) of brain parenchyma to determine tissue at risk of ischemia.Our hypothesis is that the addition of a second acquisition at 35-50 seconds could complement the assessment of hypoperfused tissue that fails to receive flow through pial vessels.Methods: Patients with large vessel occlusion and 6-24 hours from symptom onset, admitted between August 2019 and July 2023, were evaluated with dual-phase CT angiography (CTA) and CT-Perfusion.A vascular neurologist estimated CTA-SI ASPECTS in both phases at the time of data entry into the RECCA registry.In contrast, the post-processing of CT-Perfusion images was performed in an automated way through RAPID© software.The association between automated CT-perfusion values and dual-phase CTA-SI ASPECTS was assessed through a correlation coefficient.Results: Pearson's coefficient demonstrated a high correlation between ischemic core volume and delayed phase CTA (CTA-DP) ASPECTS with an inverse association of -0.93 and between Tmax ≥ 6 sec volume and arterial phase CTA (CTA-AP) ASPECTS with a value of -0.88.Conclusions: CTA-derived source images (CTA-SI) in two phases may be useful in the selection of patients with AIS presenting beyond the 6-hour window.
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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".