Patterns and implications of artery remodeling based on high-resolution vessel wall imaging in symptomatic severe basilar artery stenosis
Bibliographic record
Abstract
Background: Knowledge regarding the influence of arterial remodeling patterns on plaque characteristics and postoperative outcomes in patients with severe basilar artery (BA) stenosis after endovascular treatment is lacking. The purpose of this study was to investigate plaque characteristics, remodeling patterns, and perioperative outcomes in patients with severe BA stenosis. Methods: A prospective cohort study was conducted on symptomatic patients with severe BA stenosis who underwent high-resolution MRI before endovascular treatment. The remodeling index, plaque burden, and area of stenosis were evaluated for each plaque. Based on the remodeling index calculated by high-resolution MRI, remodeling patterns were classified as negative remodeling (NR) or non-negative remodeling (non-NR). Baseline demographics, plaque features, and treatment characteristics were compared between the NR and non-NR groups. Correlations between the remodeling index, plaque burden, and stenosis severity were also examined. Results: In total, 140 eligible patients were included and analyzed, including 91 non-NR cases and 49 NR cases. A strong correlation existed between the remodeling index and plaque burden (r=0.973, P<0.001), and a marginal correlation was observed between the remodeling index and degree of stenosis by area (r=-0.261, P=0.0019). There was no significant difference between the two groups in terms of perioperative complications related to ischemic events and new ischemic cerebral lesions (NICLs). Conclusions: Under the current submaximal angioplasty and/or stenting treatment paradigms, remodeling patterns may not influence the outcome of ischemic events and NICLs. However, the remodeling index is strongly associated with plaque burden, which may provide insight for the evaluation of severe BA stenosis. Further research is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".