Abstract 178: In-vitro Fluid Dynamic Investigation of a Novel Hyper Elastic-Thin Film Nitinol Stent and the Pipeline Embolization Device for Cerebral Aneurysm Treatment
Bibliographic record
Abstract
Introduction: Fusiform and wide-neck intracranial aneurysms (ICAs) can be challenging to treat with conventional endovascular or surgical means. Recently developed low porosity stents, such as the pipeline embolization device (PED), are designed to treat these ICAs by diverting flow away from the aneurysmal sac. However, low porosity stents rely on a dense metal mesh to divert flow, which reduces flexibility and increases the risk of perforator blockage. In this study, we compare fluid dynamic performance between the PED and a novel high porosity stent fabricated from Hyper Elastic-Thin Film Nitinol (HE-TFN). Methods: An idealized model of a sidewall ICA with a collateral branch, located immediately upstream of the aneurysm, was constructed from transparent silicone. A blood analog solution was circulated through the model at steady and pulsatile flow rates spanning a range of physiologic conditions. The PED and two HE-TFN stents, with pore densities of 8 and 21 pores/mm 2 for 500 and 300 υm pore meshes respectively, were deployed into the model. Each stent was placed across the aneurysm and collateral. Volumetric flow velocity data were acquired before and after stent placement using particle image velocimetry. Computational fluid dynamic (CFD) simulations were also conducted. Results: For both steady and pulsatile conditions, the 300 HE-TFN stent led to the largest drops in RMS Velocity Magnitude in the aneurysmal sac and in cross-neck flow. Under pulsatile conditions, the average drops in aneurysmal RMS Velocity Magnitude over the cardiac cycle, for the range of parent-vessel flow rates investigated, were 42.8-73.7% for the PED, 46.4-58.1% for the 500 HE-TFN, and 68.9-82.7% for the 300 HE-TFN. The largest drops were observed at lower parent-vessel flow rates and at peak systole. Examination of collateral flows showed that the PED led to the largest drops in collateral RMS Velocity Magnitude. Under pulsatile conditions, the average drops in collateral RMS Velocity Magnitude over the cardiac cycle were 38.3-46.1% for the PED, 14.0-25.9% for the 500 HE-TFN, and 34.5-40.8% for the 300 HE-TFN. For steady flow, both the aneurysmal and collateral performance metrics followed similar trends. Conclusion: The 300 HE-TFN stent led to larger reductions in cross-neck flow than the PED. This may be due to the higher pore density of the HE-TFN, which may be of greater importance for aneurysm occlusion than absolute porosity. Additionally, the ultra low profile, thin struts of the HE-TFN reduce perforator blockage as demonstrated by increased post-treatment collateral flows as compared to the PED. Overall, the 300 HE-TFN device performed best among the flow diversion devices examined by this study. CFD results characterizing the flow dynamics of each device will also be presented.
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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 | 0.000 |
| 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) | 0.001 | 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".