Sudden cardiac death is one of the leading causes of mortality in the western world. One of the main factors is myocardial ischaemia, when there is a mismatch between blood demand and supply to the heart, which may lead to disturbed cardiac excitation patterns, known as arrhythmias. Ischaemia is a dynamic and complex process, which is characterised by many electrophysiological changes that vary through space and time. Ischaemia-induced arrhythmic mechanisms, and the safety and efficacy of certain therapies are still not fully understood. Most experimental studies are carried out in animal, due to the ethical and practical limitations of human experiments. Therefore, extrapolation of mechanisms from animal to human is challenging, but can be facilitated by in silico models. Since the first cardiac cell model was built over 50 years ago, computer simulations have provided a wealth of information and insight that is not possible to obtain through experiments alone. Therefore, mathematical models and computational simulations provide a powerful and complementary tool for the study of multi-scale problems. The aim of this thesis is to investigate pro-arrhythmic electrophysiological consequences of acute myocardial ischaemia, using a multi-scale computational modelling and simulation framework. Firstly, we present a novel method, combining computational simulations and optical mapping experiments, to characterise ischaemia-induced spatial differences modulating arrhythmic risk in rabbit hearts. Secondly, we use computer models to extend our investigation of acute ischaemia to human, by carrying out a thorough analysis of recent human action potential models under varied ischaemic conditions, to test their applicability to simulate ischaemia. Finally, we combine state-of-the-art knowledge and techniques to build a human whole ventricles model, in which we investigate how anti-arrhythmic drugs modulate arrhythmic mechanisms in the presence of ischaemia.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:635264 |
| Date | January 2014 |
| Creators | Dutta, Sara |
| Contributors | Rodriguez, Blanca; Quinn, Alex; Mincholé, Ana |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:f5f68d8b-7a60-4109-91c8-6b1d80c7ee5b |
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