000098277 001__ 98277
000098277 005__ 20230914083305.0
000098277 0247_ $$2doi$$a10.23919/CinC49843.2019.9005863
000098277 0248_ $$2sideral$$a121995
000098277 037__ $$aART-2019-121995
000098277 041__ $$aeng
000098277 100__ $$0(orcid)0000-0003-2946-3044$$aMountris, K.A.
000098277 245__ $$aA Novel Paradigm for in Silico Simulation of Cardiac Electrophysiology Through the Mixed Collocation Meshless Petrov-Galerkin Method
000098277 260__ $$c2019
000098277 5060_ $$aAccess copy available to the general public$$fUnrestricted
000098277 5203_ $$aMulti-scale cardiac electrophysiological modeling involves high computational load due to the inherent complexity as well as to limitations of the employed numerical methods (e.g., Finite Element Method - FEM). This study investigates the use of the Meshless Local Petrov-Galerkin Mixed Collocation (MLPG-MC) method to simulate cardiac electrophysiology. MLPG-MC is a truly meshless method where both the unknown function and its gradient are interpolated using nodal collocation. A 3 cm × 3 cm human ventricular tissue was simulated based on the monodomain reaction-diffusion model using the operator splitting technique. MLPG-MC or FEM were used to solve the diffusion term and the O''Hara-Virág-Varró-Rudy AP model to represent cellular electrophysiology at baseline and under 30% IKr inhibition (IKr30). Mean differences between MLPG-MC and FEM in AP duration at 90% (APD90), 50% (APD50) and 20% (APD20) repolarization levels were 4.47%, 4.16% and 3.29% for baseline conditions and 3.66%, 2.10% and 1.62% for IKr30 conditions. The computational time associated with each of the two methods was comparable. In conclusion, considering that MLPG-MC does not involve any mesh requirements and is well suited for massive parallelization, this study shows that it represents a promising alternative to FEM for cardiac electrophysiology simulations.
000098277 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FEDER/T39-17R-BSICoS$$9info:eu-repo/grantAgreement/EUR/ERC-2014-StG-638284$$9info:eu-repo/grantAgreement/ES/MINECO/DPI2016-75458-R
000098277 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000098277 592__ $$a0.296$$b2019
000098277 593__ $$aComputer Science (miscellaneous)$$c2019
000098277 593__ $$aCardiology and Cardiovascular Medicine$$c2019
000098277 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000098277 700__ $$0(orcid)0000-0003-4273-5403$$aSanchez, C.
000098277 700__ $$0(orcid)0000-0002-1960-407X$$aPueyo, E.$$uUniversidad de Zaragoza
000098277 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000098277 773__ $$g46 (2019), [4 pp]$$pComput. cardiol.$$tComputing in Cardiology$$x2325-8861
000098277 8564_ $$s231708$$uhttps://zaguan.unizar.es/record/98277/files/texto_completo.pdf$$yVersión publicada
000098277 8564_ $$s2790753$$uhttps://zaguan.unizar.es/record/98277/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000098277 909CO $$ooai:zaguan.unizar.es:98277$$particulos$$pdriver
000098277 951__ $$a2023-09-13-10:56:09
000098277 980__ $$aARTICLE