The Role of Geometric and Mechanical Properties in Bird-beak Configuration Formation in Thoracic Endovascular Aneurysm Repair
Bibliographic record
Abstract
Thoracic endovascular aortic repair (TEVAR) is a minimally invasive treatment for thoracic aortic conditions including aneurysms and is associated with a number of postoperative stent graft related complications. Bird-beak configuration is a wedge-shaped gap at the proximal end of the deployed stent graft in TEVAR that leads to incomplete seal and other complications such as type Ia endoleak (failure of proximal stent graft seal). In this study it is hypothesized that the geometric and mechanical properties of aorta and stent graft contribute to bird-beak. This study proposes a novel framework for creating realistic population-based computational models of TEVAR focused on aneurysms that allow for developing various clinically relevant geometric configurations and scenarios that are not easily attainable with limited patient data. This framework is employed to conduct a sensitivity analysis on the geometric and mechanical characteristics of aorta and stent graft in relation to bird-beak formation. The most significant parameters contributing to bird-beak are identified as aortic arch angle, TEVAR landing zone, and stent graft oversizing. The computational framework is further used to investigate the impact of various stent graft design parameters on bird-beak formation through testing a number of conceptual device designs by varying several design parameters from a commercial stent graft model as the baseline for this study. A stent graft with reduced stent height and fabric gap is identified to have the most significant impact on reduction of bird-beak size. This stent graft design maintains the radial forces within an acceptable range. Furthermore, the computational models are used to simulate patient-specific TEVAR cases to verify the accuracy of the proposed framework in predicting the proximal position of deployed stent graft as well as the presence of bird-beak. The patient-specific TEVAR simulations can predict bird-beak length and angle size with less than 10 and 24% error, respectively. The findings of this study can provide insight into the surgical planning and device selection process with the goal of minimizing bird-beak formation. The proposed framework has the potential to predict bird-beak formation in TEVAR preoperatively and modify surgical plans accordingly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".