CT Angiographic Source Images: Flow- or Volume-Weighted?
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: CTA-SI have been previously reported to correlate with CBV. We hypothesized that CTA-SI performed by modern multisection CT scanners are CBF-, not CBV-weighted. MATERIALS AND METHODS: Sixty-four consecutive patients with anterior circulation stroke symptoms were selected from a stroke data base between June 2007 and January 2009. Two independent blinded readers calculated defect volumes of CTA-SI and PCCT, CBF, and CBV images. Spearman correlation of lesion volumes was performed. Linear regression and residual analysis demonstrated factors associated with outliers for CTA or PCCT for CBF and CBV volumes. RESULTS: We found a strong positive correlation between CTA with CBF (r = 0.89, P < .0001) and between PCCT and CBV (r = 0.79, P < .0001). CTA to CBV (r = 0.5, P < .0001) and PCCT to CBF (r = 0.52, P < .0001) correlations were weaker. Positive CTA outliers had lower ASPECTS (P = .01), larger baseline CTA (149 ± 46 cm(3) versus 83 ± 32 cm(3); P = .002, respectively), and final infarct (190 ± 100 cm(3) versus 80 ± 50 cm(3); P = .09, respectively) volumes than nonoutliers. No baseline features were significantly related to PCCT outliers. There was no difference in the vessel occlusion sites for positive or negative outliers for CTA or PCCT (P = .55 and P = 1.00, respectively). CONCLUSIONS: Our results indicate that CTA-SI are CBF- rather than CBV-weighted.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".