Serial Quantitative Computed Tomography Perfusion in Aneurysmal Subarachnoid Hemorrhage
Bibliographic record
Abstract
PURPOSE: Computed tomography perfusion (CTP) has been performed to predict which patients with aneurysmal subarachnoid hemorrhage are at risk of developing delayed cerebral ischemia (DCI). Patients with severe arterial narrowing may have significant reduction in perfusion. However, many patients have less severe arterial narrowing. There is a paucity of literature evaluating perfusion changes which occur with mild to moderate narrowing. The purpose of our study was to investigate serial whole-brain CTP/computed tomography angiography in aneurysm-related subarachnoid hemorrhage (aSAH) patients with mild to moderate angiographic narrowing. METHODS: We retrospectively studied 18 aSAH patients who had baseline and follow-up whole-brain CTP/computed tomography angiography. Thirty-one regions of interest/hemisphere at six levels were grouped by vascular territory. Arterial diameters were measured at the circle of Willis. The correlation between arterial diameter and change in CTP values, change in CTP in with and without DCI, and response to intra-arterial vasodilator therapy in DCI patients was evaluated. RESULTS: There was correlation among the overall average cerebral blood flow (CBF; R=0.49, p<0.04), mean transit time (R=-0.48, p=0.04), and angiographic narrowing. In individual arterial territories, there was correlation between changes in CBF and arterial diameter in the middle cerebral artery (R=0.53, p=0.03), posterior cerebral artery (R=0.5, p=0.03), and anterior cerebral artery (R=0.54, p=0.02) territories. Prolonged mean transit time was correlated with arterial diameter narrowing in the middle cerebral artery territory (R=0.52, p=0.03). Patients with DCI tended to have serial worsening of CBF compared with those without DCI (p=0.055). CONCLUSIONS: Our preliminary study demonstrates there is a correlation between mild to moderate angiographic narrowing and serial changes in perfusion in patients with aSAH. Patients developing DCI tended to have progressively worsening CBF compared with those not developing DCI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".