The major objective of this proposal is to predict through multi-scale modeling long-term growth and remodeling of both post-infarction scar and undamaged myocardium in response to cardiac resynchronization therapy. Over a million people suffer a myocardial infarction (heart attack) each year in the U.S alone. Most survive the initial event, making post-infarction treatment a high priority. In the weeks, months, and years following myocardial infarction (MI), growth and remodeling (G&R) of the damaged heart determine the clinical course of the patient and the impact of most available therapies. In the infarct, damaged muscle is replaced by scar, and the details of scar formation govern the risk of catastrophic infarct rupture, infarct expansion, and other serious potential complications; in noninfarcted regions of the heart, altered mechanical loading triggers myocyte growth and remodeling that often leads to heart failure. The few successful post-MI therapies available to clinicians and many therapies currently under development - including cardiac resynchronization therapy (CRT) - work by altering scar formation, remote remodeling, or both. Yet these therapies are currently developed with no ability to predict their effects on post-infarction remodeling. Therefore, there is a critical need for computational models that can accurately predict post-infarction remodeling in both the infarct and the undamaged myocardium, as well as the response to therapies that alter those processes. Multi-scale computational models of cardiac electromechanics have become increasingly mechanistic and biophysically detailed over the past decade. They can now predict many acute responses to chemical and physical stimuli or genetic defects. Moreover the availability of imaging modalities such as echocardiographic strain rate imaging and tagged MRI have provided detailed 3D strain fields with which computational models of regional ventricular mechanics can be stringently validated. However, multi-scale models of the heart are not yet capable of predicting long-term adaptation under chronic conditions. Members of the project team recently published a novel myocardial growth law, integrated it into a multi-scale model of the heart and cardiovascular system, and accurately predicted long-term cardiac G&R during pressure overload (PO) and volume overload (VO). Other members of our team developed an innovative agent-based model that accurately predicts scar formation and remodeling in healing infarcts. Here, we propose to integrate our electromechanics, G&R and agent-based models and validate them against published and new experimental data, through the following specific aims:
Aim 1 : To test the hypothesis that strain-dependent growth laws based on the response to relief of pressure and volume overload predict reverse remodeling during CRT;
Aim 2 : To test the hypothesis that larger infarcts promote eccentric hypertrophy in surviving myocardium due to the interaction of infarct stretching and hemodynamic compensations;
Aim 3 : To validate model-predicted G&R in response to post-infarction CRT.
Over a million people suffer a heart attack (myocardial infarct) each year in the U.S. alone. Damage from myocardial infarction triggers many changes in the heart - including replacement of dead muscle cells by scar and enlargement of surviving muscle cells - that often lead to heart failure. One recent advance in heart failure treatment is cardiac resynchronization therapy, which aims to restore mechanical synchrony with a specialized pacemaker; however, this treatment often fails in patients with infarcts. Therefore, the overall goal of this proposal is to develop computer models that predict long-term growth and remodeling of both infarct and undamaged myocardium in response to cardiac resynchronization therapy, in order to understand when and why this therapy fails and design better alternatives.
| Witzenburg, Colleen M; Holmes, Jeffrey W (2018) Predicting the Time Course of Ventricular Dilation and Thickening Using a Rapid Compartmental Model. J Cardiovasc Transl Res 11:109-122 |
| Holmes, Jeffrey W; Lumens, Joost (2018) Clinical Applications of Patient-Specific Models: The Case for a Simple Approach. J Cardiovasc Transl Res 11:71-79 |
| Witzenburg, Colleen M; Holmes, Jeffrey W (2017) A Comparison of Phenomenologic Growth Laws for Myocardial Hypertrophy. J Elast 129:257-281 |
| Spinale, Francis G; Frangogiannis, Nikolaos G; Hinz, Boris et al. (2016) Crossing Into the Next Frontier of Cardiac Extracellular Matrix Research. Circ Res 119:1040-1045 |
