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 goals of our proposed research are to identify the mechanical culprits that dictate the bifurcation of the system from the stable healthy state into the instable state of HF and to determine the borderline between physiological/compensatory and pathophysiological/non-compensatory growth and remodeling (G&R). To address these goals, our research approach is to experimentally inform and validate multiscale laws of myocardial growth and remodeling (G&R) using three different clinically relevant large animal HF preparations in order to predict the propensity of patients with a myocardial infarction (MI) developing HF.
Our specific Aim 1 is to elucidate a predictive validated multiscale law of myocardial G&R in eccentric hypertrophy associated with cardiac dilation. We hypothesize that a fiber-strain-based growth law can predict cardiac G&R in response to volume-overload, i.e., elevated myofiber strains stimulate concentric growth. Competing hypotheses based on stress-, strain rate-, and strain energy will be tested.
Aim 2 is to validate a predictive multi-scale law of myocardial G&R in concentric hypertrophy associated with wall thickening. We hypothesize that a unified cross-fiber strain based growth law can predict cardiac G&R in response to pressure-overload. Similar competing hypotheses as in Aim 1 will be tested.
In Aim 3, we will apply these G&R laws to predict the propensity for HF in ischemic heart disease based on specific mechanical indices of myocardial function. We hypothesize that there exists a threshold of a maximal rate of change of strain in reference to sarcomere length, above which compensatory G&R is not possible and the physiological negative feedback loop to maintain homeostasis gives way to a positive feedback loop that leads to progress remodeling and ultimate demise of the myocardium. Successful completion of this work will provide a fundamental understanding of the response of myocardium to mechanical stimuli that has substantial clinical relevance. Scientifically, this approach will provide the first ever validated and calibrated predictive micro-structural model of myocardial growth and remodeling that is fundamental to cardiology, tissue engineering, cardiac rehabilitation, and cardiac surgery. Clinically, we will provide a specific mechanical index to predict the propensity of HF in ischemic heart disease that may have a significant healthcare implication.

Public Health Relevance

The progression of ischemic heart disease to heart failure is a significant healthcare problem. The use of mathematical and experimental models of heart failure will enhance our understanding of the principles of disease progression and allow the prediction of propensity to heart failure.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Project--Cooperative Agreements (U01)
Project #
Application #
Study Section
Special Emphasis Panel (ZEB1)
Program Officer
Lee, Albert
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of California San Francisco
Schools of Medicine
San Francisco
United States
Zip Code
Sack, Kevin L; Baillargeon, Brian; Acevedo-Bolton, Gabriel et al. (2016) Partial LVAD restores ventricular outputs and normalizes LV but not RV stress distributions in the acutely failing heart in silico. Int J Artif Organs 39:421-430
Sáez, P; Kuhl, E (2016) Computational modeling of acute myocardial infarction. Comput Methods Biomech Biomed Engin 19:1107-15
Kassab, Ghassan S; An, Gary; Sander, Edward A et al. (2016) Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective. Ann Biomed Eng 44:2611-25
Genet, M; Lee, L C; Baillargeon, B et al. (2016) Modeling Pathologies of Diastolic and Systolic Heart Failure. Ann Biomed Eng 44:112-27
Sack, Kevin L; Davies, Neil H; Guccione, Julius M et al. (2016) Personalised computational cardiology: Patient-specific modelling in cardiac mechanics and biomaterial injection therapies for myocardial infarction. Heart Fail Rev 21:815-826
Tepole, Adrian Buganza; Gart, Michael; Purnell, Chad A et al. (2016) The Incompatibility of Living Systems: Characterizing Growth-Induced Incompatibilities in Expanded Skin. Ann Biomed Eng 44:1734-52
Buganza Tepole, A; Kuhl, E (2016) Computational modeling of chemo-bio-mechanical coupling: a systems-biology approach toward wound healing. Comput Methods Biomech Biomed Engin 19:13-30
Eskandari, Mona; Javili, Ali; Kuhl, Ellen (2016) Elastosis during airway wall remodeling explains multiple co-existing instability patterns. J Theor Biol 403:209-18
Lee, L C; Kassab, G S; Guccione, J M (2016) Mathematical modeling of cardiac growth and remodeling. Wiley Interdiscip Rev Syst Biol Med 8:211-26
Sahli Costabal, Francisco; Hurtado, Daniel E; Kuhl, Ellen (2016) Generating Purkinje networks in the human heart. J Biomech 49:2455-65

Showing the most recent 10 out of 31 publications