Characterization of Conventional Endovascular Devices in Treatment of Abdominal Aortic Aneurysms
Bibliographic record
Abstract
Abstract Abdominal aortic aneurysms (AAA) are often repaired through an endovascular approach known as endovascular aneurysm repair (EVAR). The success and duration of these challenging procedures are primarily attributable to the accuracy and reliability of navigating corresponding interventional devices. This study investigates the performance of conventional nonsteerable and steerable catheters in EVAR procedures, focusing on two primary metrics: reachable workspace and gate cannulation success. We developed two abdominal aortic aneurysm (AAA) phantoms using patient CT images for our experiments. Under X-ray fluoroscopy guidance, the reachable workspace was quantified, and gate cannulation success rates, cannulation time, and fluoroscopy times were recorded for both nonsteerable and steerable catheters and were compared. We were unable to observe statistically significant differences between the two catheter types in overall cannulation success rates or fluoroscopy time. However, in challenging anatomical scenarios (particularly a more challenging gate location), the steerable catheter showed statistically significant advantages in success rates and cannulation times. While there were no statistical differences in reachable workspace between nonsteerable and steerable catheters when considering the whole aneurysm, segmented analysis showed that the steerable catheter performed better in the central region, and nonsteerable catheters performed better in the peripheral region. This study provides a systematic method for quantifying the performance of endovascular devices. The findings suggest that while steerable catheters may offer advantages in complex anatomical conditions, nonsteerable catheters are preferable in peripheral areas of the aneurysm. These insights can inform catheter selection in EVAR, potentially influencing device design and clinical practice.
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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 | 0.000 | 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 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".