In vitro flow diversion effect of the ReSolv stent with the shelf technique in a bifurcation aneurysm model
Bibliographic record
Abstract
BACKGROUND: Flow-diverting stents are not currently indicated for the treatment of bifurcation aneurysms, and some case series have demonstrated low occlusion rates, possibly due to a lack in neck coverage. The ReSolv stent is a unique hybrid metal/polymer stent that can be deployed with the shelf technique in order to improve neck coverage. METHODS: A Pipeline, unshelfed ReSolv, and shelfed ReSolv stent were deployed in the left-sided branch of an idealized bifurcation aneurysm model. After determining stent porosity, high-speed digital subtraction angiography runs were acquired under pulsatile flow conditions. Time-density curves were created using two region of interest (ROI) paradigms (total aneurysm and left/right), and four parameters were extracted to characterize flow diversion performance. RESULTS: The shelfed ReSolv stent demonstrated better aneurysm outflow alterations compared to the Pipeline and unshelfed ReSolv stent when using the total aneurysm as the ROI. On the left side of the aneurysm, there was no significant difference between the shelfed ReSolv stent and the Pipeline. On the right side of the aneurysm, however, the shelfed ReSolv stent had a significantly better contrast washout profile than the unshelfed ReSolv stent and the Pipeline stent. CONCLUSIONS: The ReSolv stent with the shelf technique demonstrates the potential to improve flow diversion outcomes for bifurcation aneurysms. Further in vivo testing will help to determine whether the additional neck coverage leads to better neointimal scaffolding and long-term aneurysm occlusion.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".