Abstract

Mathematical modeling has been used for over half a century to advance our understanding of cardiac electrophysiology and arrhythmia mechanisms. Notably, computational studies using mathematical models of the cardiac action potential (AP) have provided important insight into the fundamental nature of cell excitability, mechanisms underlying both acquired and inherited arrhythmia, and potential therapies. Ultimately, an approach that tightly integrates mathematical modeling and experimental techniques has great potential to accelerate discovery. Despite the increasing acceptance of mathematical modeling as a powerful tool in cardiac electrophysiology research, there remain significant barriers to its more widespread use in the field, due in part to the increasing complexity of models and growing need for specialization. To help bridge the gap between experimental and theoretical worlds that stands as a barrier to transformational breakthroughs, we present LongQt, which has the following key features:•Cross-platform, threaded application with accessible graphical user interface.•Facilitates advanced computational cardiac electrophysiology and arrhythmia studies.•Does not require advanced programming skills.

Highlights

  • Mathematical modeling has been used for over half a century to advance our understanding of cardiac electrophysiology and arrhythmia mechanisms

  • Specified data may be visualized in the LongQt user interface at the end of the simulation, it is recommended that raw data files be used to generate publication ready figures offline

  • All variables selected in the “Select output” panel will be graphed as a function of time in the user interface at the end of the simulation

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Summary

Contents lists available at ScienceDirect

a The Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA b Department of Biomedical Engineering, College of Engineering, The Ohio State University, Columbus, OH, USA c Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA

GRAPHICAL ABSTRACT
Structure of LongQt simulation software
Mathematical models available in LongQt to simulate the cardiac action potential
Iion þ
Use of control panels in LongQt
Selecting the simulation mode
Defining a simulation protocol
Altering action potential model parameters
Data output
Executing the simulation
Analyzing and graphing simulation results
Conclusions
Full Text
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