Relative Filling Time Delay based on CT Perfusion Source Imaging: A Simple Method to Predict Outcome in Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Collateral vessel status is strongly associated with clinical outcome in ischemic stroke but can be challenging to assess. The aim of this study was to develop a tomography perfusion source imaging–based assessment of collateral vessel status. MATERIALS AND METHODS: Consecutive patients with ischemic stroke who received intravenous thrombolysis or intra-arterial reperfusion therapy after CTP were retrospectively analyzed. In those with middle cerebral artery or internal carotid artery occlusion, CT perfusion source imaging was used to identify the relative filling time delay between the normal MCA Sylvian branches and those in the affected hemisphere. Receiver operating characteristic analysis and logistic regression were used to assess the association of the relative filling time delay with the 24-hour Alberta Stroke Program Early CT Score based on noncontrast CT and the 90-day modified Rankin Scale score. RESULTS: There were 217 patients treated in 2009–2011 who had CTP data, of whom 60 had MCA or ICA occlusion and 55 had 90-day mRS data. The intraclass correlation coefficient for relative filling time delay was 0.95. Relative filling time delay was correlated with 24-hour ASPECTS (Spearman ρ = −0.674; P < .001) and 90-day mRS score (ρ = 0.516, P < .01). Increased relative filling time delay was associated with poor radiologic outcome (ASPECTS, 0–7) (area under the curve = 0.79, P < .001) and poor functional outcome (mRS score, 3–6) (area under the curve = 0.77, P = .001). In multivariate logistic regression, the association of longer relative filling time delay with poor outcome remained significant, independent of age, sex, and baseline National Institutes of Health Stroke Scale score. CONCLUSIONS: Relative filling time delay is a useful independent predictor of clinical outcome after ischemic stroke. CTP-SI : CT perfusion source imaging rFTD : relative filling time delay
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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) | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".