A simple method to estimate the exponential material parameters of heart valve tissue based on analogy between uniaxial tension and micropipette aspiration.
Micropipette aspiration (MA) has been widely used to measure the biomechanical properties of cells and biomaterials. To estimate material parameters from MA experimental data, analytical half-space models and inverse finite element (FE) analyses are typically used. The half-space model is easy to implement but cannot account for nonlinear material properties and complex geometrical boundary conditions that are inherent to MA. Inverse FE approaches can account for geometrical and material nonlinearities, but their implementation is resource-intensive and not widely available. Here, by making analogy between an analytical uniaxial tension model and a FE model of MA, we proposed an easily implementable and accurate method to estimate the material parameters of tissues tested by MA. We first adopted a strain invariant-based isotropic exponential constitutive model and implemented it in both the analytical uniaxial tension model and the FE model. The two models were fit to experimental data generated by MA of porcine aortic valve tissue (45 spots on four leaflets) to estimate material parameters. We found no significant differences between the effective moduli estimated by the two models(p > 0.39),with the effective moduli estimated by the uniaxial tension model correlating significantly with those estimated by the FE model (p < 0.001; R2 = 0.96) with a linear regression slope that was not different than unity (p = 0.38).Thus, the analytical uniaxial tension model, which avoids solving resource-intensive numerical problems, is as accurate as the FE model in estimating the effective modulus of valve tissue tested by MA.
Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
Ruogang
R
Zhao
Craig A
CA
Simmons
D000818:Animals; D001696:Biomechanical Phenomena; D055119:Elastic Modulus / Q000502:physiology; D020342:Finite Element Analysis; D006351:Heart Valves / Q000502:physiology*; D016014:Linear Models; D008954:Models, Biological; D015203:Reproducibility of Results; D013396:Suction; D034421:Sus scrofa; D016474:Weight-Bearing / Q000502:physiology