{"title":"A Coupling Physics Model for Real-Time 4D Simulation of Cardiac Electromechanics","authors":"Rui Chen, Jiahao Cui, Shuai Li, Aimin Hao","doi":"10.1016/j.cad.2024.103747","DOIUrl":null,"url":null,"abstract":"<div><p>Cardiac simulators can assist in the diagnosis of heart disease and enhance human understanding of this leading cause of mortality. The coupling of multiphysics, such as electrophysiology and active–passive mechanics, in the simulation of the heart poses challenges in utilizing existing methodologies for real-time applications. The low efficiency of physically-based simulation is mostly caused by the need for electrical-stress conduction to use tiny time steps in order to prevent numerical instability. Additionally, the mechanical simulation experiences sluggish convergence when dealing with significant deformation and stiffness, and there are also concerns regarding volume inversion. We provide a coupling physics model that transforms the active–passive dynamics into multiphysics solving constraints, aiming at boosting the real-time efficiency of the cardiac electromechanical simulation. The multiphysics processes are initially divided into two levels: cell-level electrical stimulation and organ-level electrical-stress diffusion/conduction. This separation is achieved by employing operator splitting in combination with the quasi-steady-state method, which simplifies the system equations. Next, utilizing spatial discretization, we employ the matrix-free conjugate gradient approach to solve the electromechanical model, therefore improving the efficiency of the simulation. The experimental results illustrate that our simulation model is capable of replicating intricate cardiac physiological phenomena, including 3D spiral waves and rhythmic contractions. Moreover, our model achieves a significant advancement in real-time computation while maintaining a comparable level of accuracy to current methods. This improvement is advantageous for interactive medical applications.</p></div>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010448524000745","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Cardiac simulators can assist in the diagnosis of heart disease and enhance human understanding of this leading cause of mortality. The coupling of multiphysics, such as electrophysiology and active–passive mechanics, in the simulation of the heart poses challenges in utilizing existing methodologies for real-time applications. The low efficiency of physically-based simulation is mostly caused by the need for electrical-stress conduction to use tiny time steps in order to prevent numerical instability. Additionally, the mechanical simulation experiences sluggish convergence when dealing with significant deformation and stiffness, and there are also concerns regarding volume inversion. We provide a coupling physics model that transforms the active–passive dynamics into multiphysics solving constraints, aiming at boosting the real-time efficiency of the cardiac electromechanical simulation. The multiphysics processes are initially divided into two levels: cell-level electrical stimulation and organ-level electrical-stress diffusion/conduction. This separation is achieved by employing operator splitting in combination with the quasi-steady-state method, which simplifies the system equations. Next, utilizing spatial discretization, we employ the matrix-free conjugate gradient approach to solve the electromechanical model, therefore improving the efficiency of the simulation. The experimental results illustrate that our simulation model is capable of replicating intricate cardiac physiological phenomena, including 3D spiral waves and rhythmic contractions. Moreover, our model achieves a significant advancement in real-time computation while maintaining a comparable level of accuracy to current methods. This improvement is advantageous for interactive medical applications.