Abstract

Understanding the mechanisms governing left ventricular function and dysfunction is critical to analyze cardiovascular disorders and gaining insights into possible therapies. Left ventricular function can be evaluated using Magnetic Resonance Imaging (MRI). Cardiac displacements and corresponding strains are then computed from the imaging data. In measuring and assessing the left ventricle’s motion, images are taken either in the short axis (top-down) or long axis (side) views. In this project, we will use DENSE MRI data, which measures the displacements of individual tissue voxels during the cardiac cycle.

After extracting the myocardial tissue by segmenting the MR images, strains are computed by differentiating the displacement field in the radial direction (across the thickness of the heart wall), longitudinal direction (along the left ventricle long axis), and in the circumferential direction. Current approaches focus mainly on evaluating cardiac motion and strains during ventricular systole, when the ventricles contract and blood is pumped out of the heart ~\cite{srichai2009cardiovascular}. Our aim is to characterize strains during atrial systole, which corresponds to the late filling of the ventricles before the next contraction occurs. Understanding the deformation of the left ventricle during late filling is particularly important to evaluate the passive response of the myocardium, which is related to several cardiac diseases, such as heart failure with preserved ejection fraction and diabetic cardiomyopathy. During this study we will use preclinical data already acquired in healthy swine subjects. Our goal is to evaluate inter subject variability at peak atrial systole and how different segmentations (intra and inter observer variability) affect the computed strains.

Thesis Completion

2020

Semester

Fall

Thesis Chair

Perotti, Luigi

Degree

Bachelor of Science (B.S.)

College

College of Medicine

Department

Biomedical Sciences

Degree Program

Biomedical Science

Language

English

Access Status

Open Access

Release Date

12-1-2020

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