Computational modeling of cardiac optogenetics: Methodology overview & review of findings from simulations

Patrick M. Boyle, Thomas V. Karathanos, Emilia Entcheva, Natalia A. Trayanova
<span title="">2015</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wdwg5aetkjbgpga7kn2jevifmi" style="color: black;">Computers in Biology and Medicine</a> </i> &nbsp;
Cardiac optogenetics is emerging as an exciting new potential avenue to enable spatiotemporally precise control of excitable cells and tissue in the heart with low-energy optical stimuli. This approach involves the expression of exogenous light-sensitive proteins (opsins) in target heart tissue via viral gene or cell delivery. Preliminary experiments in optogenetically-modified cells, tissue, and organisms have made great strides towards demonstrating the feasibility of basic applications,
more &raquo; ... ding the use of light stimuli to pace or disrupt reentrant activity. However, it remains unknown whether techniques based on this intriguing technology could be scaled up and used in humans for novel clinical applications, such as pain-free optical defibrillation or dynamic modulation of action potential shape. A key step towards answering such questions is to explore potential optogenetics-based therapies using sophisticated computer simulation tools capable of realistically representing opsin delivery and light stimulation in biophysically detailed, patient-specific models of the human heart. This review provides (1) a detailed overview of the methodological developments necessary to represent optogenetics-based solutions in existing virtual heart platforms and (2) a survey of findings that have been derived from such simulations and a critical assessment of their significance with respect to the progress of the field. & 2015 Elsevier Ltd. All rights reserved. Methodology overview Simulations conducted in detailed models of the heart (ventricular, atrial, or whole-heart) are increasingly recognized as an essential aspect of the investigation of cardiac disease [16] [17] [18] [19] , with applications ranging from mechanistic analysis of rhythm disorders [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] or pump dysfunction [30] [31] [32] [33] to the development of novel therapeutic methodologies [34] [35] [36] . Excitingly, the emergence of models reconstructed from medical images
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