A New Framework for Myocardium Constitutive Parameters Estimation

Abstract:

Article Preview

In this study, a new inverse analysis framework for estimation of myocardium constitutive parameters is established. In this framework, by using cardiac magnetic resonance image of realistic human left ventricular, a more realistic, finite element analysis model for analyzing the deformation of left ventricle during diastole is introduced. The anisotropic nonlinear Holzapfel-Ogden constitutive model is used to describe the material behavior of myocardium. Estimating the parameters as for the inverse problem of left ventricle deformation, a novel hybrid simplex and particle swarm optimization algorithm is proposed to estimate the parameters of myocardium’s constitutive model. Numerical examples presents that finite element analysis results and the estimated parameters are in good agreement with the experimental data reported in literature, comparing with current optimization algorithm, the presented hybrid optimal algorithm can estimate the constitutive parameters more efficient. The efficiency and validity of the proposed parameter estimation framework is demonstrated.

Info:

Periodical:

Edited by:

Prof. Dongyan Shi

Pages:

128-132

Citation:

Y. Q. Li and Z. Q. Huang, "A New Framework for Myocardium Constitutive Parameters Estimation", Applied Mechanics and Materials, Vol. 876, pp. 128-132, 2018

Online since:

February 2018

Export:

Price:

$41.00

* - Corresponding Author

[1] L. Cai, H. Gao, X. Y. Luo, et al. Multi-scale modelling of the human left ventricle. Sci. Sin. Phys. Mech. Astron. 45(2) (2015) 247.

DOI: https://doi.org/10.1360/sspma2013-00100

[2] Meng. Biomechanical model guided dual estimation of myocardial motion and material parameters. 46(5) (2012) 912-917.

[3] G. A. Holzapfel, R. W. Ogden. Constitutive modelling of passive myocardium: a structurally based framework for material characterization. Philosoph. Trans. 367(1902) (2009) 3445-3475.

DOI: https://doi.org/10.1098/rsta.2009.0091

[4] R. W. Ogden. Non-Linear Elastic Deformation. Eng. Anal. Bound. Elements, 1(2) (1984) 119.

[5] S. Guchhait, B. Banerjee. Constitutive error based material parameter estimation procedure for hyperelastic material. Comp. Meth. Appl. Mech. Eng. 297 (2015) 455-475.

DOI: https://doi.org/10.1016/j.cma.2015.09.012

[6] X. H. Shia, Y. C. Lianga, H. P. Leeb, et al. An improved GA and a novel PSO-GA-based hybrid algorithm. Inform. Proc. Lett. 93(5) (2005) 255-261.

[7] S. K. S. Fan, E. Zaharaa. A hybrid simplex search and particle swarm optimization for unconstrained optimization. European J. Operat. Res. 181(2) (2007) 527-548.

DOI: https://doi.org/10.1016/j.ejor.2006.06.034

[8] A. Aggarwal, M. S. Sacks. Parameter estimation of heart valve leaflet hyperelastic mechanical behavior using an inverse modeling approach, Northeast Bioengineering Conference. IEEE, (2014), pp.1-2.

DOI: https://doi.org/10.1109/nebec.2014.6972704

[9] H. M. Wang, X. Y. Luo, H. Gao, et al. A modified Holzapfel-Ogden law for a residually stressed finite strain model of the human left ventricle in diastole. Biomech. Model. Mechanobiol. 13(1) (2014) 99-113.

DOI: https://doi.org/10.1007/s10237-013-0488-x

[10] A. Logg, K. Olgaard, M. E. Rognes, et al. The FEniCS project. Continuous Optimization & Tao, (2003).

[11] G. A. Holzapfel, R. W. Ogden. Biomechanics of Soft Tissue in Cardiovascular Systems. Int. Centre Mech. Sci. 441 (2003) 1057–1071.