Date Available
4-28-2016
Year of Publication
2016
Document Type
Master's Thesis
Degree Name
Master of Science in Mechanical Engineering (MSME)
College
Engineering
Department/School/Program
Mechanical Engineering
Advisor
Dr. Jonathan F. Wenk
Abstract
Statistical data suggests that increased use of evidence-based medical therapies has largely contributed to the decrease in American death rate caused by heart disease. And my studies are about two applications of magnetic resonance imaging (MRI) as a non-invasive approach in evidence-based health care research. In my first study, the achievement of a pulmonary valve replacement surgery was assessed on a patient with tetralogy of Fallot (TOF). In order to evaluate the remodeling of right ventricle, two biventricular finite element models were built up for pre-surgical images and post-surgical images. In my second study, 3D Lagrangian strains and torsion in the left ventricle of ten rats were investigated using Displacement ENcoding with Stimulated Echoes (DENSE) cardiac magnetic resonance (CMR) images. Tools written in MATLAB were developed for 2D contouring, 3D modeling, strain and torsion computations, and statistical comparison across subjects.
Digital Object Identifier (DOI)
http://dx.doi.org/10.13023/ETD.2016.187
Recommended Citation
Liu, Zhanqiu, "BIVENTRICULAR FINITE ELEMENT MODELING AND QUANTIFICATION OF 3D LANGRAGIAN STRAINS AND TORSION USING DENSE MRI" (2016). Theses and Dissertations--Mechanical Engineering. 80.
https://uknowledge.uky.edu/me_etds/80
Included in
Applied Mechanics Commons, Bioimaging and Biomedical Optics Commons, Biomechanical Engineering Commons, Cardiovascular System Commons, Investigative Techniques Commons