How computer simulations of the human heart can improve anti‐arrhythmia therapy

Over the last decade, the state‐of‐the‐art in cardiac computational modelling has progressed rapidly. The electrophysiological function of the heart can now be simulated with a high degree of detail and accuracy, opening the doors for simulation‐guided approaches to anti‐arrhythmic drug development...

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Bibliographic Details
Published in:The Journal of physiology 2016-05, Vol.594 (9), p.2483-2502
Main Authors: Trayanova, Natalia A., Chang, Kelly C.
Format: Article
Language:English
Subjects:
Animals
Arrhythmias, Cardiac - physiopathology
Arrhythmias, Cardiac - therapy
Cardiac arrhythmia
Cardiovascular Conditions, Disorders and Treatments
Cardiovascular Physiology
Computational Physiology and modelling
Computer Simulation
Heart - physiopathology
Humans
Models, Cardiovascular
Reviews
Symposium Review
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Summary:Over the last decade, the state‐of‐the‐art in cardiac computational modelling has progressed rapidly. The electrophysiological function of the heart can now be simulated with a high degree of detail and accuracy, opening the doors for simulation‐guided approaches to anti‐arrhythmic drug development and patient‐specific therapeutic interventions. In this review, we outline the basic methodology for cardiac modelling, which has been developed and validated over decades of research. In addition, we present several recent examples of how computational models of the human heart have been used to address current clinical problems in cardiac electrophysiology. We will explore the use of simulations to improve anti‐arrhythmic pacing and defibrillation interventions; to predict optimal sites for clinical ablation procedures; and to aid in the understanding and selection of arrhythmia risk markers. Together, these studies illustrate how the tremendous advances in cardiac modelling are poised to revolutionize medical treatment and prevention of arrhythmia. Block diagram for generation of models of individual hearts from late‐gadolinium enhanced cardiac magnetic resonance images for electrophysiological simulation studies (modified with permission from Ukwatta et al. 2015).
ISSN:0022-3751
1469-7793
DOI:10.1113/JP270532