Diagnostic and prognostic computed tomography imaging markers in basilar artery occlusion (Review)
Bibliographic record
Abstract
Acute ischemic stroke treatment has been revolutionized by the addition of mechanical and aspiration thrombectomy. Randomized controlled trials have proven beyond doubt, the substantial clinical impact of endovascular interventions in anterior circulation territory strokes. Unfortunately, patients with vertebrobasilar ischemic stroke could not be included in these early trials due to inherent clinical, radiological, and prognostic particularities of posterior circulation ischemia; thus, indications for the treatment of posterior fossa strokes and basilar artery occlusion (BAO) are mainly based on retrospective studies and registries. BAO carries high morbidity and mortality, despite the new improvements in endovascular therapy. Identifying patients who will likely benefit from invasive treatment and have a good clinical outcome resides in discovering clinical, biological, or imaging markers, that have prognostic implications. Such imaging markers have been described, especially in the last decade. Hyperdense Basilar Artery Sign (HDBA), Posterior Circulations-Alberta Stroke Program Early CT Score (pc-ASPECTS), Pons-Midbrain Index (PMI), Posterior Circulation Collateral Score (pc-CS), Posterior Circulation CT Angiography Score (pc-CTA), and Basilar Artery on CT Prognostic Score (BATMAN), are computed tomography (CT) markers with properties that can aid the diagnosis of BAO and can independently predict clinical outcome. This paper aims to present a comprehensive review of these imaging signs to have a thorough understanding of their diagnostic and prognostic attributes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".