Abstract TMP66: Correlation Of Cerebrovascular Reserve Assessed By Acetazolamide-stress Spect With Collaterals On Arterial Spin-labeling MRI In Patients With Carotid Occlusive Disease
Bibliographic record
Abstract
Introduction: We investigated the relationship between the level of cerebral collateral circulation on arterial spin-labeling (ASL) magnetic resonance imaging (MRI) and cerebrovascular reserve (CVR) on acetazolamide (ACZ)-stress single photon emission computed tomography (SPECT) brain scans in internal carotid artery (ICA) stenosis. Methods: This study enrolled 129 patients with severe ICA stenosis (>70%). Collateral circulation was assessed in pulsed ASL images based on the presence of arterial transit artifact (ATA) that late-arriving flow appears as serpiginous high ASL signal within cortical vessels. CVR based on rest-SPECT and ACZ-stress SPECT with Tc-99m-ECD was calculated. The ASL CBF maps were independently assessed by two neuroradiologists blinded to clinical information. The two neuroradiologists graded on two slices of ASL images corresponding to Alberta Stroke Program Early Computed Tomography Score (ASPECTS) location using a 4-point scale for ASL intensity. Results: With ACZ-stress SPECT, the 88/129 (68%) patients showed normal CVR and 41/129 (32%) patients showed decreased CVR. In 73/88 (82%) of the normal CVR group patients, ASL showed ATA in ipsilateral to the stenosis. In 19/41 (46%) of the decreased CVR group patients, ASL showed no evidence of ATA in ipsilateral to the stenosis. Significant positive relationship was observed between the normal CVR group and the ATA showing group in ICA stenosis patients (p = 0.001, chi-square test). The ASL-based ASPECTS scores of brain in the ipsilateral side was lower than the scores in the contralateral side to the ICA stenosis (p < 0.0001, Wilcoxon signed rank test). The ASL-based ASPECTS scores of brain ipsilateral side to the ICA stenosis was lower in the reduced CVR group than normal CVR group (p = 0.005). Conclusion: This study demonstrated the statistically significant positive correlation between good collaterals on ASL MRI and intact CVR in patients with ICA stenosis.
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".