Mechanical characterization of atherosclerotic arteries using finite-element modeling: Feasibility study on mock arteries
Bibliographic record
Abstract
Clinical studies on lipid-lowering therapy have shown that changing the composition of lipid pools reduced significantly the risk of cardiac events associated with plaque rupture. It has been shown also that changing the composition of the lipid pool affects its mechanical properties. However, knowledge about the mechanical properties of human atherosclerotic lesions remains limited due to the difficulty of the experiments. This paper aims to assess the feasibility of characterizing a lipid pool embedded in the wall of a pressurized vessel using finite-element simulations and an optimization algorithm. Finite-element simulations of inflation experiments were used together with nonlinear least squares algorithm to estimate the material model parameters of the wall and of the inclusion. An optimal fit of the simulated experiment and the real experiment was sought with the parameter estimation algorithm. The method was first tested on a single-layer polyvinyl alcohol (PVA) cryogel stenotic vessel, and then, applied on a double-layered PVA cryogel stenotic vessel with a lipid inclusion.
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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".