Is there a simple and accessible solution to improve acute infarct core imaging? The utility of steady-state CT angiographic source images obtained from a delayed phase acquisition
Bibliographic record
Abstract
BACKGROUND: Early identification and quantification of core infarct is of importance in stroke management for treatment selection, prognostication, and complication prediction. Non-contrast computed tomography (CT) (NCCT) remains the primary tool, but it suffers from limited sensitivity and inter-rater variability; CT perfusion is inconsistently available and commonly blighted by movement artefact. We assessed the performance of a standardised form of CT angiographic source imaging (CTASI) obtained through addition of a delayed phase at 40 seconds post-contrast injection (DP40) following fast-acquisition CT angiography. METHODS: Contrast resolution between ischaemic and normal grey matter (GM) was compared qualitatively and quantitatively to NCCT. Using Alberta Stroke Program Early CT Score (ASPECTS), DP40 low density was compared to NCCT and venous phase CT perfusion source images (CTPSI) and to 24-hour NCCT ASPECTS in patients with timely endovascular recanalisation (Thrombolysis In Cerebral Infarction 2C/3). RESULTS: Seventy-four patients with a proximal middle cerebral artery or terminal internal carotid artery occlusion were included. The mean attenuation difference between ischaemic and normal GM increased from 4.86+/-3.12 HU (NCCT) to 9.30+/-3.14 HU (DP40) (p < 0.0001). Subjective assessment by two raters revealed that DP40 improved ischaemic tissue conspicuity in 39 to 41 (78-82%) of cases (kappa 0.805, standard error 0.108, 95% confidence interval: 0.593-1.000). The correlation between ASPECTS on baseline imaging and eventual 24-hour ASPECTS improved from R = 0.7197 for NCCT to R = 0.9875 for DP40 (z = 7.89, p < 0.0001). The correlation between DP40 and venous phase CTPSI ASPECTS was 0.9681, p < 0.0001. CONCLUSION: DP40 CTASI represent a simple technique for improving detection and estimation of extent of ischaemia over NCCT and show close correlation with surrogate measures of infarct core.
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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".