Abstract
Coaptation characteristics are crucial in an assessment of the competence of reconstructed aortic valves. Shell or membrane formulations can be used to model the valve cusps coaptation. In this paper we compare both formulations in terms of their coaptation characteristics for the first time. Our numerical thin shell model is based on a combination of the hyperelastic nodal forces method and the rotation-free finite elements. The shell model is verified on several popular benchmarks for thin-shell analysis. The relative error with respect to reference solutions does not exceed 1–2%. We apply our numerical shell and membrane formulations to model the closure of an idealized aortic valve varying hyperelasticity models and their shear moduli. The coaptation characteristics become almost insensitive to elastic potentials and sensitive to bending stiffness, which reduces the coaptation zone.
Highlights
The human aortic valve prevents regurgitation, i.e., coapts during diastole
In our previous work [11], we proposed the use of a hyperelastic nodal force (HNF) method instead of mass-spring models (MSM)
We study how bending stiffness affects the coaptation characteristics of an idealized aortic valve made of human pericardium
Summary
The human aortic valve prevents regurgitation (backward blood flow), i.e., coapts during diastole. One of the most appealing approaches to treating aortic valve sclerosis is through a reconstruction of the aortic valve using chemically treated auto-pericardium [2]. This procedure is low cost, has no immune response and provides minimal degradation of new cusps (leaflets), according to post-operation clinical follow-up. The key problem for any aortic valve reconstruction procedure is the optimal size and design of new cusps: reliable valve coaptation in its diastolic state contradicts the undesirability of oversized leaflets. The state-of-art design is mostly based on geometrical models [3] or expert decisions [4] that do not account for the anatomical patient-specific characteristics and mechanical properties of the cusp material. An optimal design based on personalized mathematical models is in demand for planing surgery at the preoperative stage and, has restrictions regarding computational time
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