Heart failure (HF) is a worldwide epidemic that contributes considerably to the overall cost of health care in developed nations. The number of people afflicted with this complex disease is increasing at an alarming pace-a trend that is likely to continue for many years to come. The overall goal of our proposed research is to optimize a therapy for HF that involves percutaneous injection of a hydrogel (Algisyl-LVR) in the failing myocardium. Given the cardiovascular system's complexity, a multi-disciplinary expertise across experimental and computational domains is required to fully investigate this novel HF therapy. The three specific aims include the following: First, we will validate mathematical (finite element models of failing left ventricles that have been treated with Algisyl-LVR + coronary artery bypass grafting or Algisyl-LVR alone. The finite element models will have realistic 3D geometries based on magnetic resonance imaging and validated with in-vivo myocardial strain versus left and right ventricular pressure measurements. Additionally, ex-vivo 3D myofiber orientation and direct force measurements in skinned fiber preparations will be made. Second, we will use the validated finite element models and our method for automatically optimizing medical devices for treating HF to design the optimal Algisyl-LVR injection pattern and test it in swine with systolic HF. Lastly, we will deliver Algisyl-LVR percutaneously, using the optimal injection pattern determined in Aim 2, and test it in swine with systolic HF. The proposed approach and methodologies are innovative in simulation of animal-specific device therapy that holds very significant promise for treatment of the epidemic of HF.

Public Health Relevance

Medical and/or surgical treatment of cardiovascular disease, especially heart failure, stands to vastly improve both the longevity and quality of life. Magnetic resonance imaging (MRI) with heart tissue tagging or cardiac tagged MRI combined with physics-based mathematical (finite element) modeling allows for non-invasive quantification of heart wall mechanical properties. If these mechanical properties can be correlated to disease state and the potential effect of therapeutic intervention, then the cardiology community will be able to add a significant new methodology to its armamentarium regarding patient care protocols and in particular the surgical treatment of heart failure as is the focus of this proposa.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Project (R01)
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Modeling and Analysis of Biological Systems Study Section (MABS)
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Lee, Albert
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Northern California Institute Research & Education
San Francisco
United States
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Lee, L C; Genet, M; Acevedo-Bolton, G et al. (2015) A computational model that predicts reverse growth in response to mechanical unloading. Biomech Model Mechanobiol 14:217-29
Lee, Lik Chuan; Wall, Samuel T; Genet, Martin et al. (2014) Bioinjection treatment: effects of post-injection residual stress on left ventricular wall stress. J Biomech 47:3115-9
Ge, Liang; Morrel, William G; Ward, Alison et al. (2014) Measurement of mitral leaflet and annular geometry and stress after repair of posterior leaflet prolapse: virtual repair using a patient-specific finite element simulation. Ann Thorac Surg 97:1496-503
Genet, Martin; Lee, Lik Chuan; Nguyen, Rebecca et al. (2014) Distribution of normal human left ventricular myofiber stress at end diastole and end systole: a target for in silico design of heart failure treatments. J Appl Physiol (1985) 117:142-52
Lee, Lik Chuan; Ge, Liang; Zhang, Zhihong et al. (2014) Patient-specific finite element modeling of the Cardiokinetix Parachute(®) device: effects on left ventricular wall stress and function. Med Biol Eng Comput 52:557-66
Lee, Lik Chuan; Genet, Martin; Dang, Alan B et al. (2014) Applications of computational modeling in cardiac surgery. J Card Surg 29:293-302