Theoretical investigation of non-invasive methods to identify origins of cardiac arrhythmias

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Abstract

Cardiac disease is one of the leading causes of death in the world, with an increase in cardiac arrhythmias in recent years. In addition, myocardial ischemia, which arises from the lack of blood in the cardiac tissue, can lead to cardiac arrhythmias and even sudden cardiac death. Cardiac arrhythmias, such as atrial fibrillation, are characterised by abnormal wave excitation and repolarization patterns in the myocardial tissue. These abnormal patterns are usually diagnosed through non-invasive electrical measurements on the surface of the body, i.e., the electrocardiogram (ECG). However, the most common lead configuration of the ECG, the 12-lead ECG, has its limitations in providing sufficient information to identify and locate the origin of cardiac arrhythmias. Therefore, there is an increasing need to develop novel methods to diagnose and find the origin of arrhythmic excitation, which will increase the efficacy of the treatment and diagnosis of cardiac arrhythmias.The objective of this research was to develop a family of multi-scale computational models of the human heart and thorax to simulate and investigate the effect of arrhythmic electrical activity in the heart on the electric and magnetic activities on the surface of the body. Based on these simulations, new theoretical algorithms were developed to non-invasively diagnose the origins of cardiac arrhythmias, such as the location of ectopic activities in the atria or ischemic regions within the ventricles, which are challenging to the clinician. These non-invasive diagnose methods were based on the implementation of multi-lead ECG systems, magnetocardiograms (MCGs) and electrocardiographic imaging.

Keyword(s)

Cardiac Arrhythmias; Forward and Inverse problem

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