White Matter Thresholds for Ischemic Penumbra and Infarct Core in Patients with Acute Stroke: CT Perfusion Study
Bibliographic record
Abstract
PURPOSE: To prospectively determine the parameters derived at admission computed tomographic (CT) perfusion imaging admission that best differentiate ischemic white matter that recovers from that which infarcts, with the latter retrospectively defined at a CT examination performed without contrast material (unenhanced CT) 5-7 days after the event. MATERIALS AND METHODS: Ethics committee approval and informed consent were obtained. Thirty patients with stroke underwent unenhanced CT, CT angiography, and CT perfusion studies at admission. Additionally, CT angiography was performed 24 hours after the stroke, and an unenhanced CT study was performed 5-7 days after the stroke. Five patients were excluded; the remaining patients (10 men, 15 women; mean age, 70 years +/- 13 [standard deviation]) were separated into those with recanalization (n = 16) and those without recanalization (n = 9) at 24 hours. For patients with recanalization, the final infarct was outlined on unenhanced CT images obtained 5-7 days after the event and was superimposed on coregistered maps from the CT perfusion study performed at admission. Ischemic white matter tissue (cerebral blood flow [CBF] < 14 mL/min/100 g) was identified at the admission CT perfusion study, and the penumbra was defined as the difference between the ischemic region and the infarct region. RESULTS: Infarct regions showed a matched decrease in CBF and cerebral blood volume (CBV) at admission, whereas penumbra regions showed a significant (P < .05) decrease in CBF but no change in CBV (P > .05) from contralateral values. A threshold CBF . CBV value of 8.14 was the most sensitive (95%, 20 of 21 regions) and specific (94%, 32 of 34 regions) parameter for differentiating between regions of ischemic white matter that recovered and regions of ischemic white matter that infarcted. CONCLUSION: The product of CBF and CBV derived from CT perfusion data provided the best differentiation between regions of ischemic white matter that infarcted and regions of ischemic white matter that recovered 5-7 days after a stroke.
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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".