Vessel Wall Magnetic Resonance Imaging Identifies the Site of Rupture in Patients With Multiple Intracranial Aneurysms
Bibliographic record
Abstract
BACKGROUND: High-resolution magnetic resonance vessel wall imaging (MR-VWI) is increasingly used to study steno-occlusive cerebrovascular disease, but has not yet been applied to patients with aneurysmal subarachnoid hemorrhage (SAH). OBJECTIVE: To study the ability of high-resolution MR-VWI to determine the site of rupture in patients with aneurysmal SAH. METHODS: Medical records of patients admitted with aneurysmal SAH between December 2011 and May 2012 were reviewed. MR-VWI was routinely performed for patients treated in the IMRIS Neurovascular Suite immediately before definitive treatment of the ruptured aneurysm. RESULTS: We report for the first time high-resolution MR-VWI in 5 patients with aneurysmal SAH. Three patients harbored multiple intracranial aneurysms. The ruptured aneurysms demonstrated thick vessel wall enhancement in all cases. None of the associated unruptured aneurysms demonstrated this MR imaging finding. CONCLUSION: High-resolution MR-VWI identified the site of rupture in patients with aneurysmal SAH, including those patients harboring multiple intracranial aneurysms. It may represent a useful tool in the investigation of aneurysmal SAH.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".