Forward and Inverse problems in electrocardiography
Electrocardiography (ECG) is one of the most commonly used clinical evaluation tools in cardiology. The forward problem of electrocardiography aims at answering this question: given the heart geometry and the cellular electrical activity, what would the observed ECG look like? On the other hand, the inverse problem tries to answer the following question: given the ECG reading, what is the most likely underlying electrical pattern that generated it?
Both questions are not trivial. They require intimate knowledge of the heart physiology, sophisticated mathematical techniques and powerful computational tools. In this context, we have been interested in the development of robust and detailed multi-scale models of the heart physiology, from protein to whole body level.
Pullan A, Buist ML, and Cheng LK. Mathematically modelling the electrical activity of the heart: From cell to body surface and back again. World Scientific, Singapore, 2005 (See here for more information, click on the picture to enlarge)
Buist ML and Pullan A. Torso coupling techniques for the forward problem of electrocardiography. Ann Biomed Eng, 30(10):1299–1312, 2002. (doi:10.1114/1.1527045)
Prediction of drug cardiotoxicity
Many drugs have shown adverse side effects involving the heart, sometimes after many years of being in the market. Often, the side effects involve disturbances to the electrical activity of the heart resulting in what is known as arrhythmia. Cardiac toxicity is also one of the primary causes of abandonment of drugs during the testing phases. The pharmaceutical industry has focused its interest on models of cardiac electrophysiology with the aim of predicting possible adverse side effects of novel drugs and improving the high attrition rate during drug development.
We have been involved in several projects aimed at creating a multi-scale modelling framework to PreDiCT drug cardiotoxicity as well as to gaining a quantitative insight into cardiac physiology (Physiome project).
Corrias A,Jie X, Romero L, Bishop MJ, Bernabeu M, Pueyo E and Rodriguez B. Arrhythmic risk biomarkers for the assessment of drug cardiotoxicity: from experiments to computer simulations. Philos Transact A Math Phys Eng Sci, 368(1921):3001–3025, Jun 2010. (doi:10.1098/rsta.2010.0083)
The electrical stimulus that underlies contraction of the heart originates in the sino-atrial node. The task of delivering the stimulus from the sino-atrial node to the ventricles is carried out by a specialized conduction system. Purkinje cells are part of this conduction system. They have been implicated in a variety of cardiac electrical disturbances. Purkinje cells are also widely used by the pharmaceutical industry to test the potential toxicity of drug candidates.
We have developed a model of a rabbit Purkinje cell that reproduces the experimentally observed early-after depolarizations (EAD). We are looking at gaining a better understanding at the conditions when EAD appear and when they may cause life-threatening arrhythmias.
Corrias A, Giles W and Rodriguez B. Ionic mechanisms of electrophysiological properties and repolarization abnormalities in rabbit purkinje fibers. Am J Physiol Heart Circ Physiol, 300(5):H1806–H1813, May 2011. (doi:10.1152/ajpheart.01170.2010)
Effects of fibroblasts on cardiac electrophysiology
Computational models of cardiac electrophysiology have so far been assuming that the electrical activity that underlie contraction in the heart depend only on one cell type: the cardiac myocyte. Recent studies have shown that the fibroblast cellular population in the heart may also have an important role. Many ion channel types have been identified in cardiac fibroblasts, suggesting an active electrical role of these cells in the propagation of the action potential.
We have recently proposed a novel modelling framework - the extended bidomain model - that is capable of describing electrical propagation in presence of two distinct and active cell types electrically coupled with each other.
Corrias A, Pathmanathan P, Gavaghan D and Buist ML. Modelling tissue electrophysiology with multiple cell types: applications of the extended bidomain framework. Integr Biol (Camb), 4(2):192–201, Feb 2012. (doi:10.1039/c2ib00100d)