Fluid-Structure Interaction Simulation of Blood Flow Inside a Diseased Left Ventricle With Obstructive Hypertrophic Cardiomyopathy in Early Systole
Bibliographic record
Abstract
Mitral-Septal contact has been proven to be the cause of obstruction in the left ventricle with hypertrophic cardiomyopathy (HC). This paper presents a study on the fluid mechanics of obstruction using two-way loosely coupled fluid-structure interaction (FSI) methodology. A parametric model for the geometry of the diseased left ventricular cavity, myocardium and mitral valve has been developed, using the dimensions extracted from magnetic resonance images. The three-element Windkessel model [1] was modified for HC and solved to introduce pressure boundary condition to the aortic aperture in the systolic phase. The FSI algorithm starts at the beginning of systolic phase by applying the left ventricular pressure to the internal surface of the myocardium to contract the muscle. The displacements of the myocardium and mitral leaflets were calculated using the nonlinear finite element hyperelastic model [2] and subsequently transferred to the fluid domain. The fluid mesh was moved accordingly and the Navier-Stokes equations were solved in the laminar regime with the new mesh using the finite volume method. In the next time step, the left ventricular pressure was increased to contract the muscle further and the same procedure was repeated for the fluid solution. The results show that blood flow jet applies a drag force to the mitral leaflets which in turn causes the leaflet to deform toward the septum thus creating a narrow passage and possible obstruction.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".