Computational studies, both biomechanical and electrophysiological, based on structural models of the myocardium have provided valuable insight into the functions of both normal and diseased hearts beyond empirical experimentation. However, to date, few computational models of the heart are available, and most existing models are methodologically hampered by the labor-intensive and destructive nature of conventional histological techniques. More importantly, since previous models were constructed from limited numbers of specimens, the degree to which they represent the "typical" heart, even of the same species, gender, age and contractile state, is unclear. These challenges are exacerbated for structural models of the mouse heart because of its small physical size, despite that the species is often preferred for investigating the pathophysiology and treatment of human diseases. The current proposal seeks to address these critical needs by developing and combining advanced high-resolution MRI acquisition methods and imaged-based population "atlas" analysis techniques. The overall hypothesis is that structural models representative of the normal mouse myocardium across gender, strain, age, and cardiac cycle can be constructed from a finite number of diffusion MRI datasets.
Specific aims i nclude (1a) develop multi-dimensional constrained reconstruction of reduced k- space sampling data and optimize diffusion-encoding schemes to accelerate diffusion imaging scan time, (1b) enhance the utility of diffusion MRI for characterizing myocardial structures, (2a) construct and validate static structural atlases of the normal mouse myocardium, (2b) apply diffeomorphic mapping to investigate the gender and genotype-dependence of mouse heart structural atlases, (2c) combine group regression analysis and diffeomorphic mapping to investigate the maturational adaptive modulation of the normal mouse heart, and (3) generate validated dynamic structural models of the beating normal mouse myocardium by applying Hyperelastic Warping analysis to static structural models.

Public Health Relevance

The overall aim of this proposal is to construct structural atlases of the normal mouse heart that are representative of the species regardless of gender, strain, age, and cardiac contractile state. Results of this research will provide essential foundations for computational studies of the anatomy, electrophysiology and biomechanics of both normal and diseased hearts.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL092055-04
Application #
8234076
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Applebaum-Bowden, Deborah
Project Start
2009-05-01
Project End
2014-02-28
Budget Start
2012-03-01
Budget End
2014-02-28
Support Year
4
Fiscal Year
2012
Total Cost
$372,488
Indirect Cost
$124,988
Name
University of Utah
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
009095365
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112
Abdullah, Osama M; Drakos, Stavros G; Diakos, Nikolaos A et al. (2014) Characterization of diffuse fibrosis in the failing human heart via diffusion tensor imaging and quantitative histological validation. NMR Biomed 27:1378-86
Gomez, Arnold David; Zou, Huashan; Shiu, Yan-Ting et al. (2014) Characterization of regional deformation and material properties of the intact explanted vein by microCT and computational analysis. Cardiovasc Eng Technol 5:359-370
Gomez, Arnold D; Merchant, Samer S; Hsu, Edward W (2014) Accurate high-resolution measurements of 3-D tissue dynamics with registration-enhanced displacement encoded MRI. IEEE Trans Med Imaging 33:1350-62
Welsh, Christopher L; Dibella, Edward V R; Adluru, Ganesh et al. (2013) Model-based reconstruction of undersampled diffusion tensor k-space data. Magn Reson Med 70:429-40
Healy, Lindsey J; Jiang, Yi; Hsu, Edward W (2011) Quantitative comparison of myocardial fiber structure between mice, rabbit, and sheep using diffusion tensor cardiovascular magnetic resonance. J Cardiovasc Magn Reson 13:74
Jiao, Fangxiang; Gur, Yaniv; Johnson, Chris R et al. (2011) Detection of crossing white matter fibers with high-order tensors and rank-k decompositions. Inf Process Med Imaging 22:538-49