Abstract 16666: Comparison of Wall Stresses After Ross Procedure Using Ex-Vivo Pulmonary Autograft vs in-vivo Autograft Imaging
Bibliographic record
Abstract
Introduction: Ross operation provides young adult and pediatric patients a living valve with excellent hemodynamics and no lifelong anticoagulation. However, autograft dilatation is a concern when it leads to aneurysm formation and autograft insufficiency requiring reoperation. Computational simulations of autograft remodeling are potentially effective to predict autograft dilatation, but require zero-pressure geometry and patient-specific material properties for accuracy. Hypothesis: We hypothesized that pulmonary autograft wall stresses estimated from computational simulations using in-vivo imaging would reasonably correlate with the gold standard, wall stresses determined computationally using ex-vivo autograft specimens at zeto-pressure. We recently showed that autograft wall stresses significantly increased immediately after the Ross operation. Our goal was to compare autograft wall stresses based on in-vivo geometry to those based on ex-vivo autografts. Methods: Magnetic resonance imaging (MRI) was obtained in pre-operative Ross patients and used to reconstruct in-vivo autograft geometry. Pre-stress (zero-pressure) geometry was determined. As controls, pulmonary autografts explanted from normal donor hearts underwent micro-computed tomography scans for reconstruction of ex-vivo geometry. Biaxial stretch testing was performed on both intraoperative tissue from Ross patients and on ex-vivo autografts to determine patient-specific material properties. Finite element simulations using LS-DYNA were performed to determine wall stresses. Results: Imaging from ex-vivo pulmonary autografts (n=6) and Ross patients (n=6) were obtained. Peak stresses were 93 kPa for ex-vivo vs. 113 kPa for in-vivo autografts at 25mmHg and 448kPa vs. 558 kPa, respectively at 120mmHg. Conclusions: Wall stresses at pulmonary and systemic systolic pressure predicted by in-vivo MRI imaging reasonably correlated with wall stresses based upon ex-vivo autograft tissue. Computational simulations using in-vivo imaging provides a suitable surrogate for the gold standard simulations using ex-vivo tissue specimens and broadens clinical applicability of computational simulations for patient-specific outcomes.
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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".