Beat-to-beat action potential (AP) alternants in the heart arise during tachycardia and are widely used as medium- and long-term electrocardiogram (ECG) empirical parameters to estimate the risk of sudden cardiac death. Recently, there has been an increased interest in repolarization alternants because they help to predict cardiac arrhythmias in the short term and to choose anti-arrhythmic therapy. Unfortunately, the technical possibilities to investigate such a relationship directly are very limited. Optical mapping (OM) provides the most data because it simultaneously allows voltage registration from many surface points. However, OM produces only 2-D images, and signals interfere from various depths of the myocardium because of inhomogeneities. Therefore, AP carries data not only about ion current dynamics but also about anatomical obstacles. We will investigate such phenomena using a numerical and experimental approach. Electrical excitation in the heart propagates through gap junctions (GJ). In all previous cardiac tissue models, there was the assumption that GJ conductance is constant, though now there is widely accepted evidence that it is sensitive to intercellular voltage. We will develop a numeric model of a cardiomyocyte network that reproduces cardiac tissue electrophysiological and optical properties and find model parameters from experiments (electrophysiological and optical mapping) data using global optimization and/or machine learning methods. We believe that such a method could be applied not only to investigate alternant mechanisms in the physiological and ischemic heart but also this method may be used in the development of more effective clinical therapies or treatment strategies.
Project funding:
Research Council of Lithuania (RCL), Projects of Postdoctoral fellowships funded by the state budget of the Republic of Lithuania
Project results:
It is planned to develop software models, describe them in a high-level scientific journal publication, and disseminate the results at two conferences.
Period of project implementation: 2024-01-15 - 2026-01-14
Project coordinator: Kaunas University of Technology
