On the Role of Ionic Modeling on the Signature of Cardiac Arrhythmias for Healthy and Diseased Hearts

William A. Ramírez, Alessio Gizzi, Kevin L. Sack, Simonetta Filippi, Julius M. Guccione and Daniel E. Hurtado
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William A. Ramírez: Department of Structural and Geotechnical Engineering, School of Engineering, Pontificia Universidad Catolica de Chile, Santiago 4860, Chile
Alessio Gizzi: Nonlinear Physics and Mathematical Modeling Laboratory, Department of Engineering, Campus Bio-Medico University of Rome, 00128 Rome, Italy
Kevin L. Sack: Department of Surgery, University of California at San Francisco, San Francisco, CA 94143, USA
Simonetta Filippi: Nonlinear Physics and Mathematical Modeling Laboratory, Department of Engineering, Campus Bio-Medico University of Rome, 00128 Rome, Italy
Julius M. Guccione: Department of Surgery, University of California at San Francisco, San Francisco, CA 94143, USA
Daniel E. Hurtado: Department of Structural and Geotechnical Engineering, School of Engineering, Pontificia Universidad Catolica de Chile, Santiago 4860, Chile

Mathematics, 2020, vol. 8, issue 12, 1-19

Abstract: Computational cardiology is rapidly becoming the gold standard for innovative medical treatments and device development. Despite a worldwide effort in mathematical and computational modeling research, the complexity and intrinsic multiscale nature of the heart still limit our predictability power raising the question of the optimal modeling choice for large-scale whole-heart numerical investigations. We propose an extended numerical analysis among two different electrophysiological modeling approaches: a simplified phenomenological one and a detailed biophysical one. To achieve this, we considered three-dimensional healthy and infarcted swine heart geometries. Heterogeneous electrophysiological properties, fine-tuned DT-MRI -based anisotropy features, and non-conductive ischemic regions were included in a custom-built finite element code. We provide a quantitative comparison of the electrical behaviors during steady pacing and sustained ventricular fibrillation for healthy and diseased cases analyzing cardiac arrhythmias dynamics. Action potential duration (APD) restitution distributions, vortex filament counting, and pseudo-electrocardiography (ECG) signals were numerically quantified, introducing a novel statistical description of restitution patterns and ventricular fibrillation sustainability. Computational cost and scalability associated with the two modeling choices suggests that ventricular fibrillation signatures are mainly controlled by anatomy and structural parameters, rather than by regional restitution properties. Finally, we discuss limitations and translational perspectives of the different modeling approaches in view of large-scale whole-heart in silico studies.

Keywords: computational cardiology; finite element modeling; myocardial infarction; ventricular fibrillation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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