Abstract TP338: The Dynamic CT Angiography Spot Sign: Prevalence, Predictive Value, and Rate of Contrast Extravasation
Bibliographic record
Abstract
Introduction: Hematoma expansion is a predictor of poor clinical outcome in intracerebral hemorrhage (ICH). The CT angiography (CTA) spot sign is a validated predictor of hematoma expansion, but its predictive performance is modest. This is in part because traditional “static” CTA can miss delayed spot signs, depending on the timing of image acquisition. Dynamic CTA (dCTA) can detect delayed spot sign formation and allows calculation of contrast extravasation rate. However, the predictive performance of a delayed “dynamic spot” and the relationship between rate of extravasation and hematoma expansion are not known. Our primary objective was to calculate the prevalence and predictive performance of the dynamic spot sign with dCTA. Our secondary objective was to determine whether the rate of contrast extravasation predicts significant hematoma expansion. Methods: We prospectively enrolled 79 patients who presented with primary ICH and underwent dCTA within 6 hours from onset. Primary outcomes were the prevalence of dCTA spot sign and its predictive performance for significant hematoma expansion (increase in hematoma by 6mL or 33% from baseline). For the secondary objective, we calculated the rate of contrast extravasation as the slope of the time curve from the first appearance of contrast at a spot sign to the maximal volume of contrast in 19 acquisitions over 60 seconds. We assessed the relationship between rate of extravasation and hematoma expansion using Mann-Whitney U test and logistic regression. Results: The prevalence of the dCTA spot sign was 45.6% (95% CI, 34.5-56.6%). Significant HE was seen in 58.1% (18/31) of spot-positive patients versus 29.0% (9/31) of spot-negative patients (P=0.04). The sensitivity and specificity of the dCTA spot sign in predicting significant HE was 67% and 63%, respectively. Median rate of extravasation was 0.0022 mL/min in patients with hematoma expansion vs 0.0013 mL/min in those without (p=0.05). Conclusion: Dynamic CTA had a higher spot sign prevalence than conventional CTA. While the sensitivity in predicting expansion was higher with dCTA, the specificity was lower, possibly due to a lower risk of expansion with delayed spot signs. The rate of extravasation was roughly double in patients with hematoma expansion.
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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 | 0.001 | 0.001 |
| 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) | 0.003 | 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".