Computational modeling

What does it tell us about atrial fibrillation therapy?

Eleonora Grandi, Dobromir Dobrev, Jordi Heijman

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Atrial fibrillation (AF) is a complex cardiac arrhythmia with diverse etiology that negatively affects morbidity and mortality of millions of patients. Technological and experimental advances have provided a wealth of information on the pathogenesis of AF, highlighting a multitude of mechanisms involved in arrhythmia initiation and maintenance, and disease progression. However, it remains challenging to identify the predominant mechanisms for specific subgroups of AF patients, which, together with an incomplete understanding of the pleiotropic effects of antiarrhythmic therapies, likely contributes to the suboptimal efficacy of current antiarrhythmic approaches. Computer modeling of cardiac electrophysiology has advanced in parallel to experimental research and provides an integrative framework to attempt to overcome some of these challenges. Multi-scale cardiac modeling and simulation integrate structural and functional data from experimental and clinical work with knowledge of atrial electrophysiological mechanisms and dynamics, thereby improving our understanding of AF mechanisms and therapy. In this review, we describe recent advances in our quantitative understanding of AF through mathematical models. We discuss computational modeling of AF mechanisms and therapy using detailed, mechanistic cell/tissue-level models, including approaches to incorporate variability in patient populations. We also highlight efforts using whole-atria models to improve catheter ablation therapies. Finally, we describe recent efforts and suggest future extensions to model clinical concepts of AF using patient-level models.

Original languageEnglish (US)
JournalInternational Journal of Cardiology
DOIs
StatePublished - Jan 1 2019

Fingerprint

Atrial Fibrillation
Therapeutics
Cardiac Arrhythmias
Cardiac Electrophysiology
Catheter Ablation
Disease Progression
Theoretical Models
Maintenance
Morbidity
Mortality
Research
Population

Keywords

  • Antiarrhythmic drugs
  • Arrhythmia mechanisms
  • Atrial fibrillation
  • Catheter ablation
  • Computational modeling

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Cite this

Computational modeling : What does it tell us about atrial fibrillation therapy? / Grandi, Eleonora; Dobrev, Dobromir; Heijman, Jordi.

In: International Journal of Cardiology, 01.01.2019.

Research output: Contribution to journalArticle

@article{357893ec35dd4518aaaeddda96a1e259,
title = "Computational modeling: What does it tell us about atrial fibrillation therapy?",
abstract = "Atrial fibrillation (AF) is a complex cardiac arrhythmia with diverse etiology that negatively affects morbidity and mortality of millions of patients. Technological and experimental advances have provided a wealth of information on the pathogenesis of AF, highlighting a multitude of mechanisms involved in arrhythmia initiation and maintenance, and disease progression. However, it remains challenging to identify the predominant mechanisms for specific subgroups of AF patients, which, together with an incomplete understanding of the pleiotropic effects of antiarrhythmic therapies, likely contributes to the suboptimal efficacy of current antiarrhythmic approaches. Computer modeling of cardiac electrophysiology has advanced in parallel to experimental research and provides an integrative framework to attempt to overcome some of these challenges. Multi-scale cardiac modeling and simulation integrate structural and functional data from experimental and clinical work with knowledge of atrial electrophysiological mechanisms and dynamics, thereby improving our understanding of AF mechanisms and therapy. In this review, we describe recent advances in our quantitative understanding of AF through mathematical models. We discuss computational modeling of AF mechanisms and therapy using detailed, mechanistic cell/tissue-level models, including approaches to incorporate variability in patient populations. We also highlight efforts using whole-atria models to improve catheter ablation therapies. Finally, we describe recent efforts and suggest future extensions to model clinical concepts of AF using patient-level models.",
keywords = "Antiarrhythmic drugs, Arrhythmia mechanisms, Atrial fibrillation, Catheter ablation, Computational modeling",
author = "Eleonora Grandi and Dobromir Dobrev and Jordi Heijman",
year = "2019",
month = "1",
day = "1",
doi = "10.1016/j.ijcard.2019.01.077",
language = "English (US)",
journal = "International Journal of Cardiology",
issn = "0167-5273",
publisher = "Elsevier Ireland Ltd",

}

TY - JOUR

T1 - Computational modeling

T2 - What does it tell us about atrial fibrillation therapy?

AU - Grandi, Eleonora

AU - Dobrev, Dobromir

AU - Heijman, Jordi

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Atrial fibrillation (AF) is a complex cardiac arrhythmia with diverse etiology that negatively affects morbidity and mortality of millions of patients. Technological and experimental advances have provided a wealth of information on the pathogenesis of AF, highlighting a multitude of mechanisms involved in arrhythmia initiation and maintenance, and disease progression. However, it remains challenging to identify the predominant mechanisms for specific subgroups of AF patients, which, together with an incomplete understanding of the pleiotropic effects of antiarrhythmic therapies, likely contributes to the suboptimal efficacy of current antiarrhythmic approaches. Computer modeling of cardiac electrophysiology has advanced in parallel to experimental research and provides an integrative framework to attempt to overcome some of these challenges. Multi-scale cardiac modeling and simulation integrate structural and functional data from experimental and clinical work with knowledge of atrial electrophysiological mechanisms and dynamics, thereby improving our understanding of AF mechanisms and therapy. In this review, we describe recent advances in our quantitative understanding of AF through mathematical models. We discuss computational modeling of AF mechanisms and therapy using detailed, mechanistic cell/tissue-level models, including approaches to incorporate variability in patient populations. We also highlight efforts using whole-atria models to improve catheter ablation therapies. Finally, we describe recent efforts and suggest future extensions to model clinical concepts of AF using patient-level models.

AB - Atrial fibrillation (AF) is a complex cardiac arrhythmia with diverse etiology that negatively affects morbidity and mortality of millions of patients. Technological and experimental advances have provided a wealth of information on the pathogenesis of AF, highlighting a multitude of mechanisms involved in arrhythmia initiation and maintenance, and disease progression. However, it remains challenging to identify the predominant mechanisms for specific subgroups of AF patients, which, together with an incomplete understanding of the pleiotropic effects of antiarrhythmic therapies, likely contributes to the suboptimal efficacy of current antiarrhythmic approaches. Computer modeling of cardiac electrophysiology has advanced in parallel to experimental research and provides an integrative framework to attempt to overcome some of these challenges. Multi-scale cardiac modeling and simulation integrate structural and functional data from experimental and clinical work with knowledge of atrial electrophysiological mechanisms and dynamics, thereby improving our understanding of AF mechanisms and therapy. In this review, we describe recent advances in our quantitative understanding of AF through mathematical models. We discuss computational modeling of AF mechanisms and therapy using detailed, mechanistic cell/tissue-level models, including approaches to incorporate variability in patient populations. We also highlight efforts using whole-atria models to improve catheter ablation therapies. Finally, we describe recent efforts and suggest future extensions to model clinical concepts of AF using patient-level models.

KW - Antiarrhythmic drugs

KW - Arrhythmia mechanisms

KW - Atrial fibrillation

KW - Catheter ablation

KW - Computational modeling

UR - http://www.scopus.com/inward/record.url?scp=85061790764&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85061790764&partnerID=8YFLogxK

U2 - 10.1016/j.ijcard.2019.01.077

DO - 10.1016/j.ijcard.2019.01.077

M3 - Article

JO - International Journal of Cardiology

JF - International Journal of Cardiology

SN - 0167-5273

ER -