BOLD MRI and early impairment of cerebrovascular reserve after aneurysmal subarachnoid hemorrhage
Bibliographic record
Abstract
Currently no biological or radiological marker is available to identify patients at risk of delayed ischemic deficit (DIND) after aneurysmal subarachnoid hemorrhage (aSAH). We hypothesized whether MR-based quantitative assessment of cerebrovascular reserve (CVR) would detect early radiological markers of vasospasm and DIND. This manuscript describes our initial experience with this population. Five patients with aSAH underwent blood-oxygen level dependent-MRI (BOLD-MRI) with CO2 challenge for assessment of whole brain CVR. Patients were examined as soon as possible after aneurysm treatment. We obtained good quality anatomical and functional images without complications. Initial anatomical cerebrovascular imaging showed no vasospasm in all patients. Two patients had abnormal CVR-MRI tests and both developed DIND. Of the 3 others with normal CVR-MRI, one developed posterior circulation DIND. One patient with a normal CVR-MRI developed angiographic vasospasm but no DIND. Changes in CVR maps as early as 36 h after hemorrhage had good spatial correlation with delayed ischemia during short-term follow-up. Our series shows that MRI with CO2 challenge is feasible in this difficult population. Further developments might allow BOLD-MRI with CO2 challenge to identify patients at risk and provide anatomical correlation with future DIND, opening a new venue for prophylactic treatments. Further study is warranted in a larger patient cohort.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".