Author: Boyle PM1, Karathanos TV2, Trayanova NA2.
Affiliation:
1Institute for Computational Medicine, Johns Hopkins University, 316 Hackerman Hall, 3400 N Charles Street, Baltimore, MD 21218; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD. Electronic address: pmjboyle@jhu.edu. 2Institute for Computational Medicine, Johns Hopkins University, 316 Hackerman Hall, 3400 N Charles Street, Baltimore, MD 21218; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD.
Conference/Journal: Trends Cardiovasc Med.
Date published: 2014 Oct 16
Other:
Pages: S1050-1738(14)00179-0 , Special Notes: doi: 10.1016/j.tcm.2014.10.004 , Word Count: 183
Optogenetics is an exciting new technology in which viral gene or cell delivery is used to inscribe light sensitivity in excitable tissue to enable optical control of bioelectric behavior. Initial progress in the fledgling domain of cardiac optogenetics has included in vitro expression of various light-sensitive proteins in cell monolayers and transgenic animals to demonstrate an array of potentially useful applications, including light-based pacing, silencing of spontaneous activity, and spiral wave termination. In parallel to these developments, the cardiac modeling community has developed a versatile computational framework capable of realistically simulating optogenetics in biophysically detailed, patient-specific representations of the human heart, enabling the exploration of potential clinical applications in a predictive virtual platform. Toward the ultimate goal of assessing the feasibility and potential impact of optogenetics-based therapies in cardiovascular medicine, this review provides (1) a detailed synopsis of in vivo, in vitro, and in silico developments in the field and (2) a critical assessment of how existing clinical technology for gene/cell delivery and intra-cardiac illumination could be harnessed to achieve such lofty goals as light-based arrhythmia termination.
Copyright © 2014 Elsevier Inc. All rights reserved.
PMID: 25453984