Timing of Spot Sign Appearance, Spot Sign Volume, and Leakage Rate among Phases of Multiphase CTA Predict Intracerebral Hemorrhage Growth
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The presence of spot sign is associated with a high risk of hematoma growth. Our aim was to investigate the timing of the appearance, volume, and leakage rate of the spot sign for predicting hematoma growth in acute intracerebral hemorrhage using multiphase CTA. MATERIALS AND METHODS: In this single-center retrospective study, multiphase CTA in 3 phases was performed in acute intracerebral hemorrhage (defined as intraparenchymal ± intraventricular hemorrhages). Phases of the spot sign first appearance, spot sign volumes (microliter), and leakage rates among phases (microliter/second) were measured. Associations between baseline clinical and imaging variables including spot sign volume parameters (volume and leakage rate divided by median) and hematoma growth (>6 mL) were investigated using regression models. Receiver operating characteristic analysis was used as appropriate. RESULTS: Two hundred seventeen patients (131 men; median age, 70 years) were included. The spot sign was detected in 21.7%, 30.0%, and 29.0% in the first, second, and third phases, respectively, with median volumes of 19.7, 31.4, and 34.8 μl in these phases. Hematoma growth was seen in 44 patients (20.3%). By means of modeling, the following variables, namely the spot sign appearing in the first phase, first phase spot sign volume, spot sign appearing in the second or third phase, and spot sign positive and negative leakage rates, were associated with hematoma growth. Among patients with a spot sign, the absolute leakage rate accounting for both positive and negative leakage rates was also associated with hematoma growth (per 1-μl/s increase; OR, 1.26; 95% CI, 1.04–1.52). Other hematoma growth predictors were stroke history, baseline NIHSS score, onset-to-imaging time, and baseline hematoma volume (all P values < .05). CONCLUSIONS: The timing of the appearance of the spot sign, volume, and leakage rate were all associated with hematoma growth. Development of automated software to generate these spot sign volumetric parameters would be an important next step to maximize the potential of temporal intracerebral hemorrhage imaging such as multiphase CTA for identifying those most at risk of hematoma growth.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".