Computer Methods in Applied Mechanics and Engineering · 2021 · 87 citations · 92 references
Life SciencesBioengineeringBiomedical EngineeringBiological Systems ModelingComputational BiophysicsPhysiological Systems ModelingBiomechanical ModelingCardiac PhysiologyCardiovascular System ModelingHemodynamics ModelingCardiac MechanicsCardiac Tissue MechanicsComputational Cardiac ModelingComputational EfficiencyLoop CirculationMyocardial Contraction ModelingVentricular Diastolic FunctionVentricular Mechanics Modeling
Computer models of cardiac electro-mechanics (EM) show promise as an effective means for the quantitative analysis of clinical data and, potentially, for predicting therapeutic responses. To realize such advanced applications methodological key challenges must be addressed. Enhanced computational efficiency and robustness is crucial to facilitate, within tractable time frames, model personalization, the simulation of prolonged observation periods under a broad range of conditions, and physiological completeness encompassing therapy-relevant mechanisms is needed to endow models with predictive capabilities beyond the mere replication of observations. Here, we introduce a universal feature-complete cardiac EM modeling framework that builds on a flexible method for coupling a 3D model of bi-ventricular EM to the physiologically comprehensive 0D CircAdapt model representing atrial mechanics and closed-loop circulation. A detailed mathematical description is given and efficiency, robustness, and accuracy of numerical scheme and solver implementation are evaluated. After parameterization and stabilization of the coupled 3D–0D model to a limit cycle under baseline conditions, the model’s ability to replicate physiological behaviors is demonstrated, by simulating the transient response to alterations in loading conditions and contractility, as induced by experimental protocols used for assessing systolic and diastolic ventricular properties. Mechanistic completeness and computational efficiency of this novel model render advanced applications geared towards predicting acute outcomes of EM therapies feasible.
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