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Title: Incorporating inter-sample variability into cardiac electrophysiology simulations
Author: Walmsley, John
ISNI:       0000 0004 5366 7482
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2014
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Sudden cardiac death kills 5-10 people per 10,000 population in Europe and the US each year. Individual propensity to arrhythmia and sudden cardiac death is typically assessed through clinical biomarkers. Variability in these biomarkers is a major challenge for risk stratification. Variability is observed at a wide range of spatio-temporal scales within the heart, from temporal fluctuations in ion channel behaviour, to inter-cell and inter-regional differences in ion channel expression, to structural differences between hearts. The extent to which variability manifests between spatial and temporal scales remains unclear but has a potentially crucial role in determining susceptibility to arrhythmia. In this dissertation we present a multi-scale study of the causes and consequences of variability in electrophysiology. At a sub-cellular level we demonstrate that, taking into account inter-individual variability in ion channel conductance, mRNA expression levels in failing human hearts predict the electrophysiological remodelling observed experimentally. On a tissue scale, we advocate the use of phenomenological models where information on subcellular processes is unavailable. We introduce a modification to a phenomenological model to capture beat-to-beat variability in action potential repolarisation recorded from four individual guinea pig myocytes. We demonstrate that, whilst temporal variability is dramatically reduced by inter-cell coupling, differences in their mean action potential duration may become apparent at a tissue level. The ventricular myocardium has a heterogeneous structure not captured by the simplified representation of conduction used above. In our final case study, we challenge a model of conduction by directly comparing simulations to optical mapping recordings of ventricular activation from failing and non-failing human hearts. We observe that good fits to experimental data are obtained only when endocardially bound structures are not in view, suggesting a role in conduction for these structures that are often ignored in cardiac simulations. Finally, we present future directions for the work presented. We make the case for reporting of inter-sample variability in experimental results and conclude that whilst variability may not always manifest across scales, its impact should be considered in both theoretical and experimental studies.
Supervisor: Burrage, Kevin; Rodriguez, Blanca; Mirams, Gary R. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Computer Science (Computational Biology) ; cardiac electrophysiology ; simulation ; computational biology ; variability