Analysis of the influence of modelling assumptions on the prediction of the elastic properties of cardiac fibres. Issue 10 (27th July 2018)

• Record Type: Journal Article
• Authors: Córdova Aquino, Jacobo; Medellín-Castillo, Hugo I.
• Is Part Of: Computer methods in biomechanics and biomedical engineering. Volume 21:Issue 10(2018)
• Page Start: 601
• Page End: 615
• Publication Date: 2018-07-27
• Subjects: Cardiac fiber -- elastic modulus -- finite element method (FEM) -- Left ventricular (LV); Biomechanics -- Data processing -- Periodicals; Biomedical engineering -- Periodicals; Biomechanics -- Periodicals; Biomedical Engineering -- methods -- Periodicals; Computing Methodologies -- Periodicals; 612.7
• DOI: 10.1080/10255842.2018.1502279
• Languages: English
• ISSNs: 1025-5842

Abstract

Abstract: Although several numerical models of the human heart have been proposed in the literature, there are still several discrepancies among the results predicted by each model. These discrepancies can be attributed to the fact that each model has a number of assumptions and simplifications, which can limit the scope and precision of the numerical predictions obtained. Moreover, none of the works reported in the literature have assessed the influence of modelling assumptions on the predicted cardiac fiber elastic properties. In this paper a new passive mechanical model that combines the left ventricular (LV) pressure–volume in-vivo measurements with an indirect approach based on the finite element method (FEM), is proposed and used to analyze the influence of different modelling assumptions on the estimated elastic properties of the cardiac fiber. This analysis is carried out by varying modelling assumptions that are common to existing passive mechanical models. The results have shown that although the different modelling assumptions have a significant effect on the predicted value of the fiber elastic properties, they tend to lead to the same results. This suggests that simplified passive numerical models in combination with adjustment factors, are valid in comparison with more refined and complex LV passive models.