CBV_ASPECTS Improvement over CT_ASPECTS on Determining Irreversible Ischemic Lesion Decreases over Time
Bibliographic record
Abstract
The Alberta Stroke Program Early CT Score (ASPECTS) is a useful scoring system for assessing early ischemic signs on noncontrast computed tomography (CT). Cerebral blood volume (CBV) on CT perfusion defines the core lesion assumed to be irreversibly damaged. We aim to explore the advantages of CBV_ASPECTS over CT_ASPECTS in the prediction of final infarct volume according to time. METHODS: Consecutive patients with anterior circulation stroke who underwent endovascular reperfusion according to initial CT_ASPECTS ≥7 were studied. CBV_ASPECTS was assessed blindly later on. Recanalization was defined as thrombolysis in cerebral ischemia score 2b-3. Final infarct volumes were measured on follow-up imaging. We compared ASPECTS on CBV and CT images, and defined ASPECTS agreement as: CT_ASPECTS - CBV_ASPECTS ≤1. RESULTS: Sixty-five patients, with a mean age of 67 ± 14 years and a median National Institutes of Health Stroke Scale score of 16 (range 10-20), were studied. The recanalization rate was 78.5%. The median CT_ASPECTS was 9 (range 8-10), and the CBV_ASPECTS was 8 (range 8-10). The mean time from symptoms to CT was 219 ± 143 min. Fifty patients (76.9%) showed ASPECTS agreement. The ASPECTS difference was inversely correlated to the time from symptoms to CT (r = -0.36, p < 0.01). A ROC curve defined 120 min as the best cutoff point after which the ASPECTS difference becomes more frequently ≤1. After 120 min, 89.5% of the patients showed ASPECTS agreement (as compared with 37.5% for <120 min, p < 0.01). CBV_ASPECTS but not CT_ASPECTS correlated with final infarct (r = -0.33, p < 0.01). However, if CT was done >2 h after symptom onset, CT_ASPECTS also correlated to final infarct (r = -0.39, p = 0.01). CONCLUSIONS: In acute stroke, CBV_ASPECTS correlates with the final infarct volume. However, when CT is performed after 120 min from symptom onset, CBV_ASPECTS does not add relevant information to CT_ASPECTS.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".