Date of Award
Master of Science (MS)
Electrical & Computer Engineering
Biomedical Engineering - Cardiovascular Engineering
Long QT Syndrome (LQTS) is an increasingly studied condition that leads to potentially fatal heart rhythm disorders, called arrhythmias, and sudden cardiac death. The alterations in the electrocardiograms (ECGs) seen in LQTS patients is caused by mutations to genes related to ion channels in cardiac cells. Computational modeling allows the mechanistic study of these ion channel mutations in LQTS by providing quantitative predictors of cardiac behavior in human and rabbit heart models. This work hypothesizes that the repolarization reserve in cardiac Purkinje cells (PC), that form the cardiac conduction system, is lower than that of ventricular myocytes (VM), resulting in a higher propensity of electrophysiological abnormalities in the form of spontaneous activity, particularly early and delayed afterdepolarizations (EADs and DADs, respectively). To investigate this hypothesis, detailed computational methods were created by incorporating experimental data. The computer models were then utilized to reproduce the experimentally observed behavior in single cells as well as 3-dimensional ventricular models. The computational results show more profound effects of the LQTS mutations on action potential duration (APD) prolongation in PCs when compared to VMs. Ectopic beats exist in isoproterenol conditions for human PCs. Future research includes determining the effect of these APD differences on the entirety of the heart using an anatomical 3D model of a rabbit heart.
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
Lam, Victoria L..
"Investigating Arrhythmia Potential in Cardiac Myocytes in Presence of Long QT Syndrome"
(2022). Master of Science (MS), Thesis, Electrical & Computer Engineering, Old Dominion University, DOI: 10.25777/fbqm-9x48