Preliminary Study: Learning the Impact of Simulation Time on Reentry Location and Morphology Induced by Personalized Cardiac Modeling - Tong, Lv; Zhao, Caiming; Fu, Zhenyin; Dong, Ruiqing; Wu, Zhenghong; Wang, Zefeng; Zhang, Nan; Wang, Xinlu; Cao, Boyang; Sun, Yutong; Zheng, Dingchang; Xia, Ling; et al. (Frontiers in Physiology, 2021)
Personalized cardiac modeling is widely used for studying the mechanisms of cardiac arrythmias. Due to the high demanding of computational resource of modeling, the arrhythmias induced in the models are usually simulated for just a few seconds. In clinic, it is common that arrhythmias last for more than several minutes and the morphologies of reentries are not always stable, so it is not clear that whether the simulation of arrythmias for just a few seconds is long enough to match the arrhythmias detected in patients. The aim of this study is to studying how long simulation of the induced arrhythmias in the personalized cardiac models is sufficient to match the arrhythmias detected in patients. A total of 5 contrast enhanced magnetic resonance imaging datasets of patient hearts with myocardial infarction were used in this study. Then a classification method based on Gaussian mixture model was used to detect the infarct tissue. For each reentry, three seconds and ten seconds were simulated. The characteristics of each reentry simulated for different duration were studied. Reentries were induced in all 5 ventricular models and sustained reentries were induced at 39 stimulation sites in the model. By analyzing the simulation results, we found that 41% of the sustained reentries in the 3s simulation group terminated in the longer simulation groups (10s). The second finding in our simulation was that only 23.1% of the sustained reentries in the 3s simulation do not changed location and morphology in the extended 10s simulation. The third finding is that 35.9% reentries can not get stable in the 3s simulation, and should be extended for the simulation time. The fourth finding was that the simulation results in 10s simulation matched better with the clinical measurements than the 3s simulation. 10s simulation was sufficient to make simulation results stable. The findings of this study can not only improve the simulation accuracy, but also reduce unnecessary simulation time to achieve the optimal use of computer resources, so as to improve the simulation efficiency and shorten the simulation time to meet the time node requirements of clinical operation on patients.