Abstract
Computational models are increasingly being used to investigate the mechanical properties of cardiac tissue. While much insight has been gained from these studies, one important limitation associated with computational modeling arises when using in vivo images of the heart to generate the reference state of the model. An unloaded reference configuration is needed to accurately represent the deformation of the heart. However, it is rare for a beating heart to actually reach a zero-pressure state during the cardiac cycle. To overcome this, a computational technique was adapted to determine the unloaded configuration of an in vivo porcine left ventricle (LV). In the current study, in vivo measurements were acquired using magnetic resonance images (MRI) and synchronous pressure catheterization in the LV (N = 5). The overall goal was to quantify the effects of using early–diastolic filling as the reference configuration (common assumption used in modeling) versus using the unloaded reference configuration for predicting the in vivo properties of LV myocardium. This was accomplished by using optimization to minimize the difference between MRI measured and finite element predicted strains and cavity volumes. The results show that when using the unloaded reference configuration, the computational method predicts material properties for LV myocardium that are softer and less anisotropic than when using the early-diastolic filling reference configuration. This indicates that the choice of reference configuration could have a significant impact on capturing the realistic mechanical response of the heart.
Original language | English |
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Pages (from-to) | 1714-1720 |
Number of pages | 7 |
Journal | Computer Methods in Biomechanics and Biomedical Engineering |
Volume | 19 |
Issue number | 16 |
DOIs | |
State | Published - Dec 9 2016 |
Bibliographical note
Publisher Copyright:© 2016 Informa UK Limited, trading as Taylor & Francis Group.
Keywords
- Finite element modeling
- left ventricle
- optimization
- passive myocardium
ASJC Scopus subject areas
- Bioengineering
- Biomedical Engineering
- Human-Computer Interaction
- Computer Science Applications