Cardiac mesh morphing method for finite element modeling of heart failure with preserved ejection fraction

Journal of the Mechanical Behavior of Biomedical Materials(2022)

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摘要
Numerical modeling of heart biomechanics can realistically capture morphological variations in diseases and has been helpful in advancing our understanding of the physiology. Subject-specific models require anatomic representation of medical images, and it is desirable to have a consistently repeatable models for any given morphology. In this study, we propose a novel and easily adaptable cardiac reconstruction algorithm by morphing an existing discretized mesh of an advanced finite element (FE) model, to match anatomies acquired from porcine cardiac magnetic resonance imaging (cMRI) scans. The morphing algorithm involves iterative FE simulations with visco-hyperelastic material properties. The living heart porcine model (LHPM) was chosen as the input baseline FE mesh, in order to preserve detailed anatomical features that cannot be captured in routine scans such as myofiber orientations and conduction pathways. The algorithm was demonstrated for the recreation of porcine hearts of a healthy subject and of a subject induced with heart failure with preserved ejection fraction (HFpEF) conditions, where there were substantial hypertrophy and anatomical alterations. We further used the morphed meshes for FE modeling of cardiac contraction and relaxation, thus demonstrating the applicability of the proposed algorithm in producing viable meshes. The results show that our algorithm can recreate the characteristic anatomical changes of cardiac remodeling, including heart muscle thickening, as well as replicate the reduction in ventricular volume. This algorithm allows for the creation of subject-specific models with the same mesh connectivity, thus enabling spatial comparison and analysis of pathologic progress.
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关键词
Mesh-morphing,Heart failure with preserved ejection fraction (HFpEF),Cardiac modeling,Finite element,Cardiac magnetic resonance imaging (cMRI)
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