Abstract WP55: Low Predictive Value of Multiphase CT Angiography for CT Perfusion Defined Ischemic Penumbra
Bibliographic record
Abstract
Introduction: Multiphase CT angiography (mCTA) has been proposed as an alternative to CT Perfusion (CTP) for identification of acute stroke patients with the potential for salvage after reperfusion therapy. We tested the hypothesis that poor collateral patterns on mCTA are predictive of large CTP defined ischemic cores. Methods: Multiphase CTA was generated from CTP source images (peak arterial, +8 and +16 s). Two expert raters assessed the collateral pattern on mCTA (absent/moderate/good). An Alberta Stroke Program Early CT (ASPECT) score was also assessed on the first and last phase of the mCTA as well as the non-contrast CT (NCCT). Hypoperfused regions were defined as those without vessel enhancement on the first phase. Core regions were defined as those without vessel enhancement on the final phase and/or NCCT changes. An ASPECTS mismatch score was calculated as a penumbral estimate. Penumbral tissue on CTP was defined as regions with a Delay Time (DT) >3 seconds, and ischemic core was defined as a combination of DT>3 seconds and relative CBF<40% of the contralateral hemisphere. Results: Of 141 patients, 79(56%) had penumbral patterns on CTP. Of these, 71(90%) had moderate/good collaterals. The mean penumbral volume in all patients was 20.8±26.6 ml and that in patients with large vessel occlusions (LVO; n=40) was 44.0±30.5 ml. At an ASPECTS mismatch score threshold of 2, mCTA predicted CTP defined penumbral patterns with a sensitivity of 77% and specificity of only 10%. The positive and negative predictive values were 57.7% and 61.5% respectively. In large vessel occlusion patients, mCTA predicted penumbra with 95.8% sensitivity and 43.8% specificity. The positive predictive value for penumbral patterns was 71.7%, and the negative predictive value was 87.5%. Eight patients were found to have a large core (>70 ml) on CTP, 3 of whom had moderate/good collaterals and 2 of whom also had a NCCT ASPECTS>5. Four large core patients had a mCTA penumbral score ≥ 2. Discussion: mCTA predicts penumbra with relatively high sensitivity, particularly in LVO patients. In some patients, however, mCTA can incorrectly classify penumbral patterns despite the presence of large cores on CTP. In non-LVO patients, mCTA is neither sensitive, nor specific for penumbral patterns.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".