Abstract 20549: Patient-Specific CT Image-Based Engineering Analysis of Transcatheter Aortic Valve Replacement - Implications for Aortic Root Rupture
Bibliographic record
Abstract
Introduction: Despite the increased global experience with transcatheter aortic valve replacement (TAVR), there remain major adverse clinical events. One of the most severe complications of TAVR is aortic rupture. Although several clinical risk factors of TAVR-induced rupture have been identified, the mechanisms remain largely unknown. The objective of this study was to use computational models to predict potential aortic rupture in TAVR patients. Methods: Pre-procedural CT scans of TAVR patients were used to reconstruct patient-specific finite element (FE) models, which included the aortic root, aortic leaflets, calcification, mitral-aortic intervalvular fibrosa, anterior mitral leaflet, fibrous trigones, and left ventricle. Stent deployment was simulated in a total of 25 patients to evaluate the potential for aortic rupture. Our research design consisted of two phases: Phase One, which was to develop and calibrate FE modeling techniques by retrospectively analyzing 7 Edwards SAPIEN cases with known results; and Phase Two, which was to implement the modeling methodology developed in Phase One to conduct a blind study of 18 cases from a database of 60 patients consisting of 50% rupture cases. For the blind study, FE simulations were completed by researchers blind to the clinical outcomes, and data analysis was conducted by an independent researcher. Results: Simulations correctly predicted 83% of the rupture cases. The balloon pressure at time of rupture was approximately 3.52 atm and 2.53 atm for SAPIEN 23 and 26 valves, respectively. The average contact force between the stent and native tissue was about 81N. Conclusion: Our analysis of over 18 patients suggested that the TAVR outcome could depend on the patient-specific aortic sinus shape, calcification volume, shape, location, and orientation. These results demonstrate the potential for simulation-based pre-TAVR planning tools to evaluate device performance and improve clinical outcomes.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".