Utilising an In Silico Approach to Determine Vulnerability to Reentrant Arrhythmias

Student thesis: Doctoral ThesisDoctor of Philosophy

Abstract

Post-myocardial infarction arrhythmias are a leading cause of death in developed countries, motivating research to improve treatment strategies. Ischemic damage occurring due to a myocardial infarction results in the formation of inexcitable infarct scars. Electrical activation waves circumvent these structural barriers and can propagate in perpetual reentrant circuits giving rise to ventricular tachycardia. The success of reentrant propagation depends on the wavelength of the activation wave with respect to the physical path length, determining the extent of wavefront-waveback interactions.

A wide variety of animal and computational models are used to perform research however, the optimal species for studying clinical arrhythmias is unknown. One aim of the research in this Thesis was to suggest a species model which most closely replicates clinical arrhythmia dynamics. Computational models were utilised to compare the susceptibility to reentry, by calculating the effective electrical size of the heart, which takes into consideration both the size of the wavelength and the physical size of the heart. Results suggested that species differences in effective size exist between human and animal models. However, the effective size of the rabbit model was most similar to the human. This conclusion was utilised to formulate methodologies for the following studies.

Current techniques employed to locate ablation lesion sites during radiofrequency catheter ablation are inaccurate, leading to insufficient procedure success rates. Here, a method to accurately locate optimal ablation lesion targets was investigated utilising computational models. Quantification of wavelength permitted the observation of wavefront-waveback interactions to predict susceptibility to reentry. The clinical application of the methodology was modelled to ensure that ablation of the susceptible tissue could terminate reentry and that the limitations of clinical data acquisition did not invalidate the technique. The method accurately located a region of tissue where reentry could potentially occur and ablation of the region terminated reentry even when clinical protocol was simulated.

This research suggests the most suitable species models to research ventricular tachycardia, guiding further in vivo and in silico methodologies. Additionally, a protocol to improve the success of the ablation procedure has been further investigated. Clinical implementation of this technique could vastly improve the treatment of post-myocardial infarction arrhythmias.
Date of Award2016
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorMartin Bishop (Supervisor) & Nicolas Smith (Supervisor)

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