Comparison of intra-aneurysmal flow modification using optical flow imaging to evaluate the performance of Evolve and Pipeline flow diverting stents
Bibliographic record
Abstract
BACKGROUND: Flow diverting stent (FDS) devices have revolutionized the treatment of large and complex brain aneurysms, but there is still room for improvement, particularly on the flow diversion properties and technical challenges associated with stent deployment. In this study we compared flow diversion properties between the new generation Surpass Evolve (Stryker) and the Pipeline Flex (Medtronic) devices by quantitatively evaluating intra-aneurysmal flow modification. METHODS: An in vitro experimental set-up was used, consisting of four patient-specific silicone models with internal carotid aneurysms and a circulating hemodynamic simulation system with pulsatile flow. The Evolve and Pipeline stents were deployed across the neck of each aneurysm model, in a randomized fashion, for a total of eight device deployments. A 60 frames/s digital subtraction angiography run was acquired before and after placement of each FDS. An optical flow-analysis method was used to measure intra-aneurysmal flow modification induced by the stent by calculating a mean aneurysm flow amplitude (MAFA) before and after stent placement and computing a ratio. RESULTS: Average MAFA ratio values calculated from pre- and post-stent placement were significantly lower after deployment of the Evolve (n=4, mean=0.62±0.09) compared with the Pipeline device (n=4, mean=0.71±0.06) (p=0.03). CONCLUSIONS: Our in vitro results show that the Evolve stent had a superior flow diversion effect compared with the Pipeline stent, which-based on clinical evidence-suggest it may promote faster aneurysm occlusion rates in patients.
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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 | 0.000 | 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) | 0.000 | 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".