Injectable biomaterials are an attractive therapy to attenuate left ventricular (LV) remodeling after myocardial infarction (MI). Although studies have shown that injectable hydrogels improve cardiac structure and function in vivo, temporal changes in infarct material properties after treatment have not been assessed. Emerging imaging and modeling techniques now allow for serial, non-invasive estimation of infarct material properties. Specifically, cine MRI assesses global LV structure and function, late-gadolinium enhancement (LGE) MRI enables visualization of infarcted tissue to quantify infarct expansion, and spatial modulation of magnetization (SPAMM) tagging provides passive wall motion assessment as a measure of tissue strain, which can all be used to evaluate infarct properties when combined with finite element (FE) models. In this work, we investigated the temporal effects of degradable hyaluronic acid (HA) hydrogels on global LV remodeling, infarct thinning and expansion, and infarct stiffness in a porcine infarct model for 12 weeks post-MI using MRI and FE modeling. Hydrogel treatment led to decreased LV volumes, improved ejection fraction, and increased wall thickness when compared to controls. FE model simulations demonstrated that hydrogel therapy increased infarct stiffness for 12 weeks post-MI. Thus, evaluation of myocardial tissue properties through MRI and FE modeling provides insight into the influence of injectable hydrogel therapies on myocardial structure and function post-MI.

The results reported here are consistent with previously described ex vivo biaxial extension studies of infarct material properties and the circumferential change of collagen orientation in posterolateral infarcts. The current study represents a significant advance in that the method used allows for the serial assessment of an individual infarct in vivo over time and avoids the inherent limitations related to the testing of excised tissues.

In order to better understand the mechanics of the heart and its disorders, engineers increasingly make use of the finite element method (FEM) to investigate healthy and diseased cardiac tissue. However, FEM is only as good as the underlying constitutive model, which remains a major challenge to the biomechanics community. In this study, a recently developed structurally based constitutive model was implemented to model healthy left ventricular myocardium during passive diastolic filling. This model takes into account the orthotropic response of the heart under loading. In-vivo strains were measured from magnetic resonance images (MRI) of porcine hearts, along with synchronous catheterization pressure data, and used for parameter identification of the passive constitutive model. Optimization was performed by minimizing the difference between MRI measured and FE predicted strains and cavity volumes. A similar approach was followed for the parameter identification of a widely used phenomenological constitutive law, which is based on a transversely isotropic material response. Results indicate that the parameter identification with the structurally based constitutive law is more sensitive to the assigned fiber architecture and the fit between the measured and predicted strains is improved with more realistic sheet angles. In addition, the structurally based model is capable of generating a more physiological End-Diastolic Pressure-Volume Relationship in the ventricle.

The goal of this study was to investigate the sensitivity of computational models of the heart to their incorporated myofiber architecture during diastole. This architecture plays a critical role in the mechanical and electrical function of the heart and changes after myocardial tissue remodeling, which is associated with some of the most common heart diseases. In this study, a left ventricular finite element model of the porcine heart was created using magnetic resonance imaging, which represents the in vivo geometry. Various myofiber architectures were assigned to the finite element mesh, in the form of fiber and sheet angles. A structural-based material law was used to model the behavior of passive myocardium and its parameters were estimated using measured in vivo strains and cavity volume from magnetic resonance imaging. The final results showed noticeable sensitivity of the stress distribution to both the fiber and sheet angle distributions. This implies that a structural-based material law that takes into account the effect of both fiber and sheet angle distributions should be used. The results also show that although the simulation results improve using available data from histological studies of myocardial structure, the need for individualized myofiber architecture data is crucial.

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.