Ghost Infarct Core and Admission Computed Tomography Perfusion: Redefining the Role of Neuroimaging in Acute Ischemic Stroke
Bibliographic record
Abstract
Background: Determining the size of infarct extent is crucial to elect patients for reperfusion therapies. Computed tomography perfusion (CTP) based on cerebral blood volume may overestimate infarct core on admission and consequently include ghost infarct core (GIC) in a definitive lesional area. Purpose: Our goal was to confirm and better characterize the GIC phenomenon using CTP cerebral blood flow (CBF) as the reference parameter to determine infarct core. Methods: We performed a retrospective, single-center analysis of consecutive thrombectomies of middle cerebral or intracranial internal carotid artery occlusions considering noncontrast CT Alberta Stroke Program Early CT Score ≥6 in patients with pretreatment CTP. We used the RAPID® software to measure admission infarct core based on initial CBF. The final infarct was extracted from follow-up CT. GIC was defined as initial core minus final infarct > 10 mL. Results: A total of 123 patients were included. The median National Institutes of Health Stroke Scale score was 18 (13–20), the median time from symptoms to CTP was 188 (67–288) min, and the recanalization rate (Thrombolysis in Cerebral Infarction score 2b, 2c, or 3) was 83%. Twenty patients (16%) presented with GIC. GIC was associated with shorter time to recanalization (150 [105–291] vs. 255 [163–367] min, p = 0.05) and larger initial CBF core volume (38 [26–59] vs. 6 [0–27] mL, p < 0.001). An adjusted logistic regression model identified time to recanalization < 302 min (OR 4.598, 95% CI 1.143–18.495, p = 0.032) and initial infarct volume (OR 1.01, 95% CI 1.001–1.019, p = 0.032) as independent predictors of GIC. At 24 h, clinical improvement was more frequent in patients with GIC (80 vs. 49%, p = 0.01). Conclusions: CTP CBF < 30% may overestimate infarct core volume, especially in patients imaged in the very early time window and with fast complete reperfusion. Therefore, the CTP CBF technique may exclude patients who would benefit from endovascular treatment.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".