Cardiovascular diseases are the leading cause of death worldwide, and are estimated to kill over 17 million people each year, about 31% of all deaths. In the clinic, the first diagnostic procedure for a suspected cardiac abnormality is often acquisition of an electrocardiogram (ECG), which measures the electrical potential of the heart at the body surface. Understanding the mechanisms underlying generation of the ECG waveforms is crucial for optimal clinical benefit. Computer simulations possess several strengths as a tool to gain this understanding, particularly in terms of human-specificity, flexibility, repeatability, and ethics. The ventricles make up the majority of the cardiac volume and are therefore responsible for the majority of ECG waveforms. Ventricular disorders are the most life-threatening, because the ventricles are responsible for pumping blood to the body. Due to their size it has only recently become possible to perform biophysically detailed simulations of the ventricles and torso using supercomputers. In this thesis, multiscale, mathematical models of the ventricles and torso using the Chaste software library are simulated on high performance computing systems. A description is included of the performance enhancements made in Chaste to improve resource efficiency and accelerate job turnaround, particularly in data storage and the auxiliary tasks of post-processing and data conversion. A novel model of ventricular activation is presented and parametrized using multi-modal human data, and successfully used to simulate normal and pathological QRS complexes. Similarly, repolarization gradients are imposed based on the literature and result in a variety of T waves. Finally, the developed human whole-ventricular and torso models are utilized to gain new insights into possible ionic mechanisms underlying the clinical manifestations of the early repolarization syndrome. Overall, this thesis presents a novel framework for simulation of the human ECG using high performance computers, with possible applications in basic science and computational medicine.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:730034 |
| Date | January 2016 |
| Creators | Cardone-Noott, Louie |
| Contributors | Bueno, Alfonso ; Burrage, Kevin ; MincholeĢ, Ana ; Rodriguez, Blanca |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://ora.ox.ac.uk/objects/uuid:6d1521dc-e490-40c3-97ac-86fa54bf570e |
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