A collocation-Galerkin finite element model of cardiac action potential propagation

Rogers, Jack M.; McCulloch, Andrew D.

doi:10.1109/10.310090

Cited by 350 publications

(235 citation statements)

References 36 publications

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“…A modification of this original model was suggested by Rogers and McCulloch in 1994 [11], that allows to get rid of this unphysiological overshoot in repolarisaton. In order to implement the depolarisation and repolarisation propagation on the heart, a laplacian is introduced in the first equation.…”

Section: Numerical Modellingmentioning

confidence: 99%

Generation of computational meshes from MRI and CT-scan data

Sermesant

Frey

2005

ESAIM: Proc.

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Abstract. There are fields of engineering where accurate and personalised data are required; biomedical applications are one such example. We describe here a general purpose method to create computational meshes based on the analysis and segmentation of raw medical imaging data. The various ingredients are not new: a segmentation method based on deformable contours and a surface and volume mesh adaptation method based on discrete metric specifications; but the challenge that motivated this paper is to put them together in an attempt to design an automatic, easy to use and efficient 3D code.For non-engineering (like biomedical) applications, the user interface is often a key point. In this project, we put a great deal of emphasis on the automation of the whole procedure, making then possible to envisage large scale simulations with a minimal amount of user interaction. In particular, the user knowledge is required to help segmenting the image (the user is expected to have the knowhow of the body anatomy), all meshing steps rely on fully automatic algorithms depending on a few parameters (for the external surface approximation).One application example is presented and commented, for which the data preparation takes a few hours and results can be obtained overnight on a PC workstation.Résumé. Dans certains domaines du calcul scientifique il est nécessaire de disposer de données précises et personnalisées; les applications biomédicales en sont un bon exemple. Nous présentons ici une méthode générique permettant de générer des maillages de calculà partir de l'analyse et de la segmentation de données médicales discrètes. Si les divers composants ne sont pas nouveaux: une méthode de segmentation d'images basées sur des contours déformables et des techniques d'adaptation de maillage de surfaces et de volumes basées sur la notion de métrique, le challenge est ici d'assembler ces constituants de manièreà obtenir un code de simulation efficace et facileà utiliser.Pour des applications telles que biomédicales, l'interface utilisateur est un point clé. Dans ce projet, nous avons particulièrement soigné l'automatisation de la procédure, ce qui permet d'envisager des simulations de larges tailles pratiquement sans intervention de l'utilisateur. En particulier, les compétences de celui-ci (i.e., ses connaissances en anatomie) sont utilisées pour la segmentation des images, lesétapes de maillageétant entièrement automatisées et ne faisant intervenir qu'un ensemble réduit de paramètres (contrôle de l'approximation des surfaces notamment). * We are grateful to the CEA-LIST for funding this work

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Section: Numerical Modellingmentioning

confidence: 99%

Generation of computational meshes from MRI and CT-scan data

Sermesant

Frey

2005

ESAIM: Proc.

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“…Due to large number of mesh elements and therefore computational complexity of realistic 3D whole-heart model we used computationally efficient and simple equations for cellular activation -modified FitzHugh-Nagumo (FHN) equations to simulate action potentials in different subdomains / regions of the heart [10,11].…”

Section: Equationsmentioning

confidence: 99%

“…The bidomain equations were based on modified FitzHugh-Nagumo equations [10,11]. For the n/a Torso n/a n/a 0.2 *a deflated, *b inflated, *c longitudinal, *d transversal, *e parallel, *f normal, *g marrow.…”

Section: Subdomainsmentioning

confidence: 99%

3D Cardiac Electrical Activity Model

2016

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Original scientific paperThe aim of this study is to develop a new, computationally-efficient, anatomically-realistic 3D bidomain cardiac electrical activity model using widely available software and standard low-cost hardware. The model incorporates whole-heart embedded in a human torso, spontaneous activation of sinoatrial node and specialized conduction system with heterogeneous action potential morphologies. The model is capable of generating realistic body surface electrocardiograms (ECGs) and is proposed as a useful tool for investigating some major issues in heart pathophysiology and in stimulation; such as simulating and optimizing synchronized electrical cardioversion, defibrillation and pacing stimulation.Key words: Bidomain model, cardiac simulation, ECG, whole-heart 3D model električne aktivnosti srca. Cilj studije je razviti računalno efikasan, anatomski realističan 3D model električne aktivnosti cijelog ljudskog srca na široko dostupnoj računalnoj opremi. Model uključuje cijelo srce okruženo plućima i postavljeno unutar ljudskog torza, sa spontanom aktivacijom sinus-atrijskogčvora i specijaliziranim vodljivim putevima s heterogenim morfologijama akcijskih potencijala. Model omogućuje simuliranje elektrokardiograma (EKG) realističnog oblika te ga je moguće koristiti za istraživanje srčanih patofiziologija, simuliranje i optimizaciju sinkronizirane električne kardioverzije, defibrilacije ili simulacije različitih srčanih stimulacija.

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“…For phenomenological description of the membrane kinetics according to the Rogers-McCulloch model [6], system (3.1) reads…”

Section: Activation Models and Numerical Examplesmentioning

confidence: 99%

Active strain and activation models in cardiac electromechanics

Rossi

Ruiz–Baier

Pavarino

et al. 2011

Proc Appl Math and Mech

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We present a model for mechanical activation of the cardiac tissue depending on the evolution of the transmembrane electrical potential and certain gating/ionic variables that are available in most of electrophysiological descriptions of the cardiac membrane. The basic idea consists in adding to the chosen ionic model one ordinary differential equation for the kinetics of the mechanical activation function. A relevant example illustrates the desired properties of the proposed model, such as delayed muscle contraction and correct magnitude of the muscle fibers' shortening.

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A collocation-Galerkin finite element model of cardiac action potential propagation

Cited by 350 publications

References 36 publications

Generation of computational meshes from MRI and CT-scan data

Generation of computational meshes from MRI and CT-scan data

3D Cardiac Electrical Activity Model

Active strain and activation models in cardiac electromechanics

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