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Computational Modeling of Scar Formation After Myocardial Infarction

$365,220R01FY2015HLNIH

University Of Virginia, Charlottesville VA

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Abstract

DESCRIPTION (provided by applicant): Over a million Americans suffer a heart attack (myocardial infarction) each year. For the majority who survive the initial event, the risks of serious complications such as infarct rupture and heart failure depend on the structure and mechanical properties of the scar tissue that replaces damaged heart muscle over the first few weeks. That scar tissue is produced by cardiac fibroblasts, and we recently showed that scar structure and mechanical properties are strongly influenced by mechanical stretch during healing. The biology of how fibroblasts respond to individual signals such as mechanical stretch has been studied extensively; yet we still understand relatively little about how fibroblasts integrate and respond to the multiple signals present in a healing wound. We therefore developed an agent-based model (ABM) of scar formation that represents individual fibroblasts - each migrating, aligning, depositing and remodeling collagen, dividing, dying, and responding to individual chemical, structural, and mechanical signals according to experimental measurements - and predicts the resulting evolution of tissue-level collagen content and fiber alignment in scars healing under different patterns of stretch. Here, we propose to couple this ABM with a finite-element model (FEM) of the infarct left ventricle to produce a coupled model that can predict the dynamic interplay between evolving scar structure, scar mechanics, and heart function after infarction and in response to therapies that alter infarct mechanics (Aim 1). Then, we will use a combination of experiments and modeling to better understand the cellular mechanisms by which mechanical stretch regulates collagen content and alignment in healing myocardial infarcts. Specifically, we will test the hypotheses that mechanical regulation of collagen degradation significantly influences collagen content and alignment during mechanical unloading (Aim 2) and that scar compaction significantly influences collagen fiber density but not in-plane fiber alignment across a range of loading conditions (Aim 3). The proposed studies are potentially significant both because they will generate the first validated, predictive model of infarct healing across a range of mechanical conditions - enabling computational screening and design of novel therapies - and because they will provide important new insight into the cellular mechanisms by which mechanical environment regulates scar formation, which could lead to the identification of new therapeutic approaches to modulating infarct healing.

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