Confirmatory Study of Time-Dependent Computed Tomographic Perfusion Thresholds for Use in Acute Ischemic Stroke
Bibliographic record
Abstract
Background and Purpose— Computed tomographic perfusion (CTP) thresholds associated with follow-up brain infarction may differ by time from symptom onset to imaging and reperfusion. We confirm CTP thresholds over time to imaging and reperfusion in patients with acute ischemic stroke from the HERMES collaboration (Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials) data. Methods— Patients with occlusion on CT angiography were acutely imaged with CTP. Noncontrast CT and magnetic resonance-diffusion weighted imaging at 24 to 48 hours defined follow-up infarction. Reperfusion was assessed on conventional angiogram. Tmax, cerebral blood flow (CBF), and cerebral blood volume maps were derived from delay-insensitive CTP postprocessing. These parameters were analyzed using receiver operator characteristics to derive optimal thresholds based on time from stroke onset-to-CTP or to reperfusion. ANOVA and linear regression were used to test whether the derived CTP thresholds were different by time. Results— One hundred thirty-seven patients were included. Tmax thresholds of >15.7 s and >15.8 s and absolute CBF thresholds of <8.9 and <7.5 mL·min −1 ·100 g −1 for gray matter and white matter respectively were associated with infarct if reperfusion was achieved <90 minutes from CTP with stroke onset-to-CTP <180 minutes. The discriminative ability of cerebral blood volume was modest. There were no statistically significant relationships between stroke onset-to-CTP time and Tmax, CBF, and cerebral blood volume thresholds (all P >0.05). A statistically significant relationship was observed between CTP-to-reperfusion time and the optimal thresholds for Tmax ( P <0.001) and CBF ( P <0.001). Similar but more modest relationship was noted for onset-to-reperfusion time and optimal thresholds for CBF ( P ≤0.01). Conclusions— CTP thresholds based on stroke onset and imaging time and taking into account time needed for reperfusion may improve infarct prediction in patients with acute ischemic 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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".