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Title: Development of a virtual 3D sheep atria for the study of clinical atrial fibrillation
Author: Butters, Timothy Daniel
ISNI:       0000 0004 2719 2890
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2012
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Cardiovascular disease remains the leading cause of death in the developed world. In this thesis computational modelling techniques were used to study the mechanisms and genesis of atrial arrhythmias. It is separated into 2 parts: (1) The mechanistic links between mutations of the fast Na+ channel (INa) and the ability of the sinoatrial node to pace the surrounding atrial muscle were investigated. The mutations were separated into two groups, one for the mutations affecting the steady-state activation, and the other for those affecting steady-state inactivation. On the single cell level it was found that all mutations slowed the pacing rate of the sinoatrial node in a similar way, but at the 2D level the two mutation groups modulated the excitation of the tissue differently. One caused a conduction block between the sinoatrial node and atrium, where the other abolished pacemaking all together. (2) A new set of mathematical models were then developed for the sheep atria. This was incorporated into an anatomically detailed 3D geometry of the whole sheep atria to form a platform suitable for the study of clinical atrial fibrillation, and other atrial arrhythmias. Due to the lack of single cell electrophysiology data available, a method of cross-species modelling was utilised. A biophysically detailed model of the 3D sheep atria was created, and used in a preliminary study into the susceptibility of tissue to atrial fibrillation from the rapid pacing of the pulmonary vein area. It was found that both electrical heterogeneity and the complex fibre structure of the atria need to be considered for sustained atrial fibrillation to be seen.
Supervisor: Zhang, Henggui Sponsor: EPSRC
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Atrial Fibrillation ; Cardiac Modelling ; Systems Biology