Human cardiac systems electrophysiology and arrhythmogenesis: iteration of experiment and computation. Review uri icon

Overview

abstract

  • Human cardiac electrophysiology (EP) is a unique system for computational modelling at multiple scales. Due to the complexity of the cardiac excitation sequence, coordinated activity must occur from the single channel to the entire myocardial syncytium. Thus, sophisticated computational algorithms have been developed to investigate cardiac EP at the level of ion channels, cardiomyocytes, multicellular tissues, and the whole heart. Although understanding of each functional level will ultimately be important to thoroughly understand mechanisms of physiology and disease, cardiac arrhythmias are expressly the product of cardiac tissue-containing enough cardiomyocytes to sustain a reentrant loop of activation. In addition, several properties of cardiac cellular EP, that are critical for arrhythmogenesis, are significantly altered by cell-to-cell coupling. However, relevant human cardiac EP data, upon which to develop or validate models at all scales, has been lacking. Thus, over several years, we have developed a paradigm for multiscale human heart physiology investigation and have recovered and studied over 300 human hearts. We have generated a rich experimental dataset, from which we better understand mechanisms of arrhythmia in human and can improve models of human cardiac EP. In addition, in collaboration with computational physiologists, we are developing a database for the deposition of human heart experimental data, including thorough experimental documentation. We anticipate that accessibility to this human heart dataset will further human EP computational investigations, as well as encourage greater data transparency within the field of cardiac EP.

publication date

  • November 1, 2014

Research

keywords

  • Arrhythmias, Cardiac
  • Computer Simulation
  • Heart Conduction System
  • Models, Cardiovascular

Identity

PubMed Central ID

  • PMC4455663

Scopus Document Identifier

  • 84965188164

Digital Object Identifier (DOI)

  • 10.1529/biophysj.105.069534

PubMed ID

  • 25362174

Additional Document Info

volume

  • 16 Suppl 4

issue

  • Suppl 4