In response to disease, the myocardium undergoes time-dependent remodeling that manifests as alterations of heart shape and motion during the cardiac cycle. For example, in patients with coronary artery disease and left ventricular dysfunction, ventricular remodeling results in a gradual increase of ventricular end-diastolic and end- systolic volumes, wall thinning, changes of chamber geometry, and alterations of heart motion. At the micro-structure scale, the normal 3D organization of muscle fibers in the myocardium that spirals around the left ventricle with a angle that is determined by their transmural location is perturbed. While there have been attempts to identify genes and proteins that are indicative of disease risk, there have been few efforts to quantify and assess regional cardiac shape, fiber orientation, and motion changes to predict disease and to monitor response in various therapies. Our work will focus on developing new algorithms, from the emerging discipline of computational functional anatomy (CFA), for analyzing changes of heart shape (geometry and fiber structure) and motion and exploring the extent to which such image-derived parameters can be used to describe disease state and progression. We will pursue this by employing a reperfused murine model of infarction to measure differences in ventricular geometry, fiber orientation, and motion of the cardiac ventricles using in-vivo 3D time evolving structural and tagged MRI imaging and ex-vivo diffusion tensor imaging in normal vs. infarcted mouse. Prevention of adverse remodeling after myocardial infarction (MI) is a therapeutic challenge as ventricles in many patients continue to enlarge after MI and mortality and morbidity remain significant in spite of therapy. Several studies indicated that extracellular collagen matrix (ECCM) plays an important role in post-MI remodeling and it may appear that treatments that targeting ECCM remodeling might be beneficial. However, the whole matter is further complicated by the fact that infarct and non-infarct zones demonstrate differential pathophysiological responses. Therefore a detailed understanding of temporal/spatial evolution of ECCM remodeling is a necessary step in developing treatment strategies that target both infarcted and non-infarcted zones. CFA methods that are developed in this proposal will be utilized in future studies to acquire valuable information about the effect of substances such as matrix metalloproteinases that degrade ECCM on the ventricular structural remodeling and cardiac mechanics.

Public Health Relevance

The goal of this project is to develop mathematical tools to characterize ventricular shape (geometry and fiber structure) and function in post myocardial infarction (post-MI) remodeling. The process of post-MI remodeling often leads to the deterioration of cardiac pump function and increased susceptibility to arrhythmias. Therefore developing computational tools that can advance our understanding of the remodeling process will allow design of improved diagnostic and therapeutic interventions that might limit adverse cardiac remodeling.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21HL109968-02
Application #
8311647
Study Section
Special Emphasis Panel (ZRG1-SBIB-Q (80))
Program Officer
Larkin, Jennie E
Project Start
2011-08-05
Project End
2014-04-30
Budget Start
2012-05-01
Budget End
2014-04-30
Support Year
2
Fiscal Year
2012
Total Cost
$205,000
Indirect Cost
$80,000
Name
Johns Hopkins University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218
Ardekani, Siamak; Jain, Saurabh; Sanzi, Alianna et al. (2016) Shape analysis of hypertrophic and hypertensive heart disease using MRI-based 3D surface models of left ventricular geometry. Med Image Anal 29:12-23
Ardekani, Siamak; Gunter, Geoffrey; Jain, Saurabh et al. (2014) Estimating dense cardiac 3D motion using sparse 2D tagged MRI cross-sections. Conf Proc IEEE Eng Med Biol Soc 2014:5101-4