Literature DB >> 25845576

Regional segmentation of ventricular models to achieve repolarization dispersion in cardiac electrophysiology modeling.

L E Perotti1,2,3, S Krishnamoorthi1, N P Borgstrom2, D B Ennis2,3, W S Klug1.   

Abstract

The electrocardiogram (ECG) is one of the most significant outputs of a computational model of cardiac electrophysiology because it relates the numerical results to clinical data and is a universal tool for diagnosing heart diseases. One key features of the ECG is the T-wave, which is caused by longitudinal and transmural heterogeneity of the action potential duration (APD). Thus, in order to model a correct wave of repolarization, different cell properties resulting in different APDs must be assigned across the ventricular wall and longitudinally from apex to base. To achieve this requirement, a regional parametrization of the heart is necessary. We propose a robust approach to obtain the transmural and longitudinal segmentation in a general heart geometry without relying on ad hoc procedures. Our approach is based on auxiliary harmonic lifting analyses, already used in the literature to generate myocardial fiber orientations. Specifically, the solution of a sequence of Laplace boundary value problems allows parametrically controlled segmentation of both heart ventricles. The flexibility and simplicity of the proposed method is demonstrated through several representative examples, varying the locations and extents of the epicardial, midwall, and endocardial layers. Effects of the control parameters on the T-wave morphology are illustrated via computed ECGs.
Copyright © 2015 John Wiley & Sons, Ltd.

Entities:  

Keywords:  T-wave; cardiac modeling; harmonic lifting; repolarization dispersion; ventricular segmentation

Mesh:

Year:  2015        PMID: 25845576      PMCID: PMC4519348          DOI: 10.1002/cnm.2718

Source DB:  PubMed          Journal:  Int J Numer Method Biomed Eng        ISSN: 2040-7939            Impact factor:   2.747


  29 in total

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5.  Transmural and apicobasal gradients in repolarization contribute to T-wave genesis in human surface ECG.

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6.  Estimation of tissue contractility from cardiac cine-MRI using a biomechanical heart model.

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Journal:  Int J Numer Method Biomed Eng       Date:  2013-07-19       Impact factor: 2.747

10.  Simulation Methods and Validation Criteria for Modeling Cardiac Ventricular Electrophysiology.

Authors:  Shankarjee Krishnamoorthi; Luigi E Perotti; Nils P Borgstrom; Olujimi A Ajijola; Anna Frid; Aditya V Ponnaluri; James N Weiss; Zhilin Qu; William S Klug; Daniel B Ennis; Alan Garfinkel
Journal:  PLoS One       Date:  2014-12-10       Impact factor: 3.240

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2.  Generating Purkinje networks in the human heart.

Authors:  Francisco Sahli Costabal; Daniel E Hurtado; Ellen Kuhl
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3.  In silico evaluation of the acute occlusion effect of coronary artery on cardiac electrophysiology and the body surface potential map.

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4.  Personalized Cardiac Computational Models: From Clinical Data to Simulation of Infarct-Related Ventricular Tachycardia.

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5.  Estimating cardiomyofiber strain in vivo by solving a computational model.

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6.  Electrophysiology of Heart Failure Using a Rabbit Model: From the Failing Myocyte to Ventricular Fibrillation.

Authors:  Aditya V S Ponnaluri; Luigi E Perotti; Michael Liu; Zhilin Qu; James N Weiss; Daniel B Ennis; William S Klug; Alan Garfinkel
Journal:  PLoS Comput Biol       Date:  2016-06-23       Impact factor: 4.475

  6 in total

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