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Published in: Medical & Biological Engineering & Computing 5/2020

24-02-2020 | Original Article

Computational prediction of the effect of D172N KCNJ2 mutation on ventricular pumping during sinus rhythm and reentry

Authors: Aulia Khamas Heikhmakhtiar, Chung Hao Lee, Kwang Soup Song, Ki Moo Lim

Published in: Medical & Biological Engineering & Computing | Issue 5/2020

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Abstract

The understanding of cardiac arrhythmia under genetic mutations has grown in interest among researchers. Previous studies focused on the effect of the D172N mutation on electrophysiological behavior. In this study, we analyzed not only the electrophysiological activity but also the mechanical responses during normal sinus rhythm and reentry conditions by using computational modeling. We simulated four different ventricular conditions including normal case of ten Tusscher model 2006 (TTM), wild-type (WT), heterozygous (WT/D172N), and homozygous D172N mutation. The 2D simulation result (in wire-shaped mesh) showed the WT/D172N and D172N mutation shortened the action potential duration by 14%, and by 23%, respectively. The 3D electrophysiological simulation results showed that the electrical wavelength between TTM and WT conditions were identical. Under sinus rhythm condition, the WT/D172N and D172N reduced the pumping efficacy with a lower left ventricle (LV) and aortic pressures, stroke volume, ejection fraction, and cardiac output. Under the reentry conditions, the WT condition has a small probability of reentry. However, in the event of reentry, WT has shown the most severe condition. Furthermore, we found that the position of the rotor or the scroll wave substantially influenced the ventricular pumping efficacy during arrhythmia. If the rotor stays in the LV, it will cause very poor pumping performance.

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Appendix
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Metadata
Title
Computational prediction of the effect of D172N KCNJ2 mutation on ventricular pumping during sinus rhythm and reentry
Authors
Aulia Khamas Heikhmakhtiar
Chung Hao Lee
Kwang Soup Song
Ki Moo Lim
Publication date
24-02-2020
Publisher
Springer Berlin Heidelberg
Published in
Medical & Biological Engineering & Computing / Issue 5/2020
Print ISSN: 0140-0118
Electronic ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-020-02124-w

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