Heart failure (HF), one of the leading causes of death worldwide, results from adverse remodeling of the left ventricle (LV) of the heart after myocardial infarction (MI). To ameliorate LV remodeling, it has been shown that infarction modification through direct injection of biomaterials has the potential to limit infarct expansion. However, little effort has been directed toward determination of the optimal physical characteristics of the injectate, its interaction with infarcted myocardium, and the effect of patient-specific geometric patterns of injection. The ability of injected HA-based hydrogels to reduce infarct expansion and ameliorate adverse post- MI remodeling is dependent on HA hydrogel properties (elastic modulus, degradation rate, and distribution). The design of optimal materials and their deployment can be accomplished in-silico using organ-level models of the post-MI remodeling LV, thus allowing optimized materials to be developed with a limited need for animal and clinical experimentation. The proposed work employs a novel tunable hyaluronic acid (HA)-based injectable material and a clinically relevant ovine infarct model. State-of-the-art magnetic resonance imaging methodologies, combined with experimentally determined 3D infarct material properties, serve as input for a finite element model for assessing LV geometry and microstructure of healthy, infarcted, and injected myocardium. Use of the approach will yield substantially more accurate models capable of faithful prediction of injection therapies? impact on tissue- and organ-level events post-MI, allowing for the development of patient- specific therapies for MI and improvement of patient outcomes.
Heart failure, one of the leading causes of death worldwide, results from adverse remodeling of the heart after myocardial infarction (MI). Infarction modification through direct injection of biomaterials to reinforce the tissue has the ability to attenuate the risk of developing heart failure. The design of optimal materials for injection and their deployment can be accomplished in-silico using computational models of the post-MI remodeling heart, allowing for the development of patient-specific therapies for MI, as well as improvement of patient outcomes.