• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2947-2950
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• 2007

A 3D human ventricular model is proposed to simulate an integrative analysis of heart physiology and blood hemodynamics. This consists of the models of electrophysiology of human cells, electric wave propagation of tissue, heart solid mechanics, and 3D blood hemodynamics. The 3D geometry of human heart is discretized to a finite element mesh for the simulation of electric wave propagation and mechanics of heart. In cellular level, excitations by action potential are simulated using the existing human model. Then the contraction mechanics of a whole cell is incorporated to the excitation model. The excitation propagation to ventricular cells are transiently computed in the 3D cardiac tissue using a mono-domain method of electric wave propagation in cardiac tissue. Blood hemodynamics in heart is also considered and incorporated with muscle contraction. We use a PISO type finite element method to simulate the blood hemodynmaics in the human ventricular model.

• International Journal of Vascular Biomedical Engineering
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• v.3 no.1
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• pp.23-29
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• 2005

We developed a three dimensional cardiac tissue model based on human cardiac cell and mono-domain approximation for action potential propagation. The human myocyte model proposed by ten Tusscher et al. (TNNP model) (2004) for cell electrophysiology and a mono-domain method for electric wave propagation are used to simulate the cardiac tissue propagation mechanism using a finite element method. To delineate non-homogeneity across cardiac tissue layer, we used three types of cardiac cell models. Ansiotropic effect of action potential propagation is also considered in this study. In this 3D anisotropic cardiac tissue with three cell layers, we generated a reentrant wave using S1-S2 protocol. Computational results showed that the reentrant wave was affected by the anisotropic properties of the cells. To test the reentrant wave under pathological state, we simulated a hypertopic model with non-excitable fibroblasts in stochastic manner. Compared with normal tissue, the hypertropic tissue result showed another center of reentrant wave, indicating that the wave pattern can be more easily changed from regular with a concentric focus to irregular multi-focused reentrant waves in case of patients with hypertrophy.

• Journal of Biomedical Engineering Research
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• v.41 no.3
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• pp.128-137
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• 2020

Cardiac electrophysiology studies often use simulation to predict how cardiac will behave under various conditions. To observe the cardiac tissue movement, it needs to use the high--resolution heart mesh with a sophisticated and large number of nodes. The higher resolution mesh is, the more computation time is needed. To improve computation speed and performance, parallel processing using multi-core processes and network computing resources is performed. In this study, we compared the computational speeds of CPU parallelization and GPU parallelization in virtual heart simulation for efficiently calculating a series of ordinary differential equations (ODE) and partial differential equations (PDE) and determined the optimal CPU and GPU parallelization architecture. We used 2D tissue model and 3D ventricular model to compared the computation performance. Then, we measured the time required to the calculation of ODEs and PDEs, respectively. In conclusion, for the most efficient computation, using GPU parallelization rather than CPU parallelization can improve performance by 4.3 times and 2.3 times in calculations of ODEs and PDE, respectively. In CPU parallelization, it is best to use the number of processors just before the communication cost between each processor is incurred.

• Journal of Biomedical Engineering Research
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• v.38 no.3
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• pp.123-128
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• 2017

Background and aims: The KCNQ1 S140G mutation involved in $I_{ks}$ channel is a typical gene mutation affecting atrial fibrillation. However, despite the possibility that the S140G gene mutation may affect not only atrial but also ventricular action potential shape and ventricular responses, there is a lack of research on the relationship between this mutation and ventricular fibrillation. Therefore, in this study, we analyzed the correlation and the influence of the KCNQ1 S140G mutant gene on ventricular fibrillation through computer simulation studies. Method: This study simulated a 3-dimensional ventricular model of the wild type(WT) and the S140G mutant conditions. It was performed by dividing into normal sinus rhythm simulation and reentrant wave propagation simulation. For the sinus rhythm, a ventricular model with Purkinje fiber was used. For the reentrant propagation simulation, a ventricular model was used to confirm the occurrence of spiral wave using S1-S2 protocol. Results: The result showed that 41% shortening of action potential duration(APD) was observed due to augmented $I_{ks}$ current in S140G mutation group. The shortened APD contributed to reduce wavelength 39% in sinus rhythm simulation. The shortened wavelength in cardiac tissue allowed re-entrant circuits to form and increased the probability of sustaining ventricular fibrillation, while ventricular electrical propagation with normal wavelength(20.8 cm in wild type) are unlikely to initiate re-entry. Conclusion: In conclusion, KCNQ1 S140G mutation can reduce the threshold of the re-entrant wave substrate in ventricular cells, increasing the spatial vulnerability of tissue and the sensitivity of the fibrillation. That is, S140G mutation can induce ventricular fibrillation easily. It means that S140G mutant can increase the risk of arrhythmias such as cardiac arrest due to heart failure.