Leaflet stress quantification of porcine vs bovine surgical bioprostheses: an <i>in vitro</i> study
Bibliographic record
Abstract
Calcified aortic stenoses are among the most prevalent form of cardiovascular diseases in the industrialized countries. This progressive disease, with no effective medical therapy, ultimately requires aortic valve replacement – either a surgical or very recently transcatheter aortic valve implantation. Increase leaflet mechanical stress is one of the main determinants of the structural deterioration of bioprosthetic aortic valves. We applied a coupled in vitro/in silico method to compare the timing, magnitude, and regional distribution of leaflet mechanical stress in porcine versus pericardial bioprostheses (Mosaic and Trifecta). A double activation simulator was used for in vitro testing of a bioprosthesis with externally mounted pericardium (Abbott, Trifecta) and a bioprosthesis with internally mounted porcine valve (Medtronic, Mosaic). A non-contact system based on stereophotogammetry and digital image correlation (DIC) with high spatial and temporal resolution (2000 img/s) was used to visualize the valve leaflet motion and perform the three-dimensional analysis. A finite element model of the valve was developed, and the leaflet deformation obtained from the DIC analysis was applied to the finite element model calculate local leaflet mechanical stress throughout the cardiac cycle. The maximum leaflet stress was higher with the pericardial versus the porcine bioprosthesis (2.03 vs. 1.30 MPa) For both bioprostheses the highest values of leaflet stress occurred during diastole and were primarily observed in the upper leaflet edge near the commissures and to a lesser extent in the mid-portion of the leaflet body. In conclusion, the coupled in vitro/in silico method described in this study shows that the highest levels of leaflet stress occur in the regions of the commissures and mid-portion of the leaflet body. This method may have important insight with regard to bioprosthetic valve durability. Our results suggest that, compared to porcine bioprostheses, those with externally mounted pericardium have higher leaflet mechanical stress, which may translate into shorter durability.
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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 | 0.001 | 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".