Single‐ and Multiphase CT Angiography Is Associated With Digital Subtraction Angiography Collateral Score ≥3
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Collateral status is an important predictor of reperfusion and mortality in patients with large vessel anterior circulation acute ischemic stroke (AIS). We assess the utility of multiphase computed tomography angiography (CTA) derived from CT perfusion (CTP) source imaging (dCTA) in determining collateral status compared to the reference standard American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN/SIR) collateral score on digital subtraction angiography (DSA). METHODS: We retrospectively analyzed AIS patients treated at our institution from January 9, 2017, to January 10, 2023. Inclusion criteria included CTA-confirmed anterior circulation large vessel occlusion, diagnostic CTP, and mechanical thrombectomy with documented DSA collateral score. The modified treatment in cerebral ischemia score was used to assess reperfusion. Logistic regression analyses evaluated associations between demographic and clinical factors, collateral status, ASITN/SIR, and reperfusion status. RESULTS: A total of 311 patients (mean age 67.35 ± 16.37, 57.4% female) were included. Univariate analysis showed that proximal M2 (PM2) occlusion site (odds ratio [OR] 4.45, p < 0.001), Alberta Stroke Program Early CT Score (OR 1.24, p = 0.006), dCTA (OR 3.81, p < 0.001), and CTA Tan (OR 6.05, p < 0.001) were associated with an ASITN score of ≥3, indicating collateral flow. Multivariate regression, adjusted for race, occlusion site, radiologic features, National Institutes of Health stroke score, and premorbid modified Rankin score, found PM2 occlusion site (aOR 5.99, p < 0.001), dCTA (adjusted OR [aOR] 2.24, p = 0.04), and CTA Tan (aOR 3.71, p < 0.01) to be significant predictors of ASITN ≥3. CONCLUSIONS: dCTA is associated with favorable DSA collateral scores and may aid clinical decision-making in AIS patients with large vessel occlusions. Further studies can assess its role in outcome prediction.
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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 | 0.001 | 0.001 |
| 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".