Vessel wall MRI characteristics of endovascularly treated aneurysms: association with angiographic vasospasm
Bibliographic record
Abstract
OBJECTIVE: The aim of this paper was to evaluate the association between intracranial vessel wall MRI enhancement characteristics and the development of angiographic vasospasm in endovascularly treated aneurysm patients. METHODS: Consecutive cases of both ruptured and unruptured intracranial aneurysms that were treated endovascularly, followed by intracranial vessel wall MRI in the immediate postoperative period, were included. Two raters blinded to clinical data and follow-up imaging independently evaluated for the presence, pattern, and intensity of wall enhancement. Development of angiographic vasospasm was independently evaluated. Delayed cerebral ischemia; cerebral infarct; procedural details; and presence and grade of subarachnoid, parenchymal, and intraventricular hemorrhage were evaluated. Statistical associations were determined on a per-vessel segment and per-patient basis. RESULTS: Twenty-nine patients with 30 treated aneurysms (8 unruptured and 22 ruptured) were included in this study. Interobserver agreement was substantial for the presence of enhancement (κ = 0.67) and nearly perfect for distribution (κ = 0.87) and intensity (κ = 0.84) of wall enhancement. Patients with ruptured aneurysms had a significantly greater number of enhancing segments than those with unruptured aneurysms (29.9% vs 7.2%; OR 5.5, 95% CI 2.2-13.7). For ruptured cases, wall enhancement was significantly associated with subsequent angiographic vasospasm while controlling for grade of hemorrhage (adjusted OR 3.9, 95% CI 1.7-9.4). Vessel segments affected by balloon, stent, or flow-diverter use demonstrated greater enhancement than those not affected (OR 22.7, 95% CI 5.3-97.2 for ruptured; and OR 12.9, 95% CI 3.3-49.8 for unruptured). CONCLUSIONS: Vessel wall enhancement after endovascular treatment of ruptured aneurysms is associated with subsequent angiographic vasospasm.
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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 | 0.006 |
| 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".