An isogeometric analysis framework for ventricular cardiac mechanics

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2 Citaten (Scopus)
14 Downloads (Pure)


The finite element method (FEM) is commonly used in computational cardiac simulations. For this method, a mesh is constructed to represent the geometry and, subsequently, to approximate the solution. To accurately capture curved geometrical features many elements may be required, possibly leading to unnecessarily large computation costs. Without loss of accuracy, a reduction in computation cost can be achieved by integrating geometry representation and solution approximation into a single framework using the isogeometric analysis (IGA) paradigm. In this study, we propose an IGA framework suitable for echocardiogram data of cardiac mechanics, where we show the advantageous properties of smooth splines through the development of a multi-patch anatomical model. A nonlinear cardiac model is discretized following the IGA paradigm, meaning that the spline geometry parametrization is directly used for the discretization of the physical fields. The IGA model is benchmarked with a state-of-the-art biomechanics model based on traditional FEM. For this benchmark, the hemodynamic response predicted by the high-fidelity FEM model is accurately captured by an IGA model with only 320 elements and 4700 degrees of freedom. The study is concluded by a brief anatomy-variation analysis, which illustrates the geometric flexibility
of the framework. The IGA framework can be used as a first step toward an efficient workflow for an improved understanding of, and clinical decision support for, the treatment of cardiac diseases like heart rhythm disorders.
Originele taal-2Engels
Pagina's (van-tot)465-506
Aantal pagina's42
TijdschriftComputational Mechanics
Nummer van het tijdschrift3
Vroegere onlinedatum31 aug. 2023
StatusGepubliceerd - mrt. 2024


This publication is part of the COMBAT-VT project (Project No. 17983) of the research program High Tech Systems and Materials which is partly financed by the Dutch Research Council (NWO). Additionally, this work was performed within the IMPULS framework under the Picasso project (Reference No. TKI HTSM/20.0022) of the Eindhoven MedTech Innovation Center (e/MTIC, incorporating Eindhoven University of Technology, Philips Research, and Catharina Hospital), including a PPS-supplement from the Dutch Ministry of Economic Affairs and Climate Policy. The research of the second author is sponsored by the European Union’s Horizon 2020 research and innovation program under Grant Agreement 874827 (BRAVE).

Horizon 2020 Framework Programme874827
Nederlandse Organisatie voor Wetenschappelijk Onderzoek


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