4.5 Review

Three-dimensional cardiac computational modelling: methods, features and applications

Journal

BIOMEDICAL ENGINEERING ONLINE
Volume 14, Issue -, Pages -

Publisher

BMC
DOI: 10.1186/s12938-015-0033-5

Keywords

Cardiac modelling; Three-dimensional (3D) modelling; Computational modelling; Fibre orientation; Cardiac conduction system (CCS); Cardiac image segmentation; Biophysical simulation; Personalisation; Patient-specific modelling

Funding

  1. VI Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica from the Ministerio de Economia y Competitividad of Spain [TIN2012-37546-C03-01, TIN2011-28067]
  2. European Commission (European Regional Development Funds - ERDF - FEDER)
  3. eTorso project from the Generalitat Valenciana (Spain) [GVA/2013-001404]
  4. program Ayudas para contratos predoctorales para la formacion de doctores from the Ministerio de Economia y Competitividad of Spain [BES-2013-064089]

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The combination of computational models and biophysical simulations can help to interpret an array of experimental data and contribute to the understanding, diagnosis and treatment of complex diseases such as cardiac arrhythmias. For this reason, three-dimensional (3D) cardiac computational modelling is currently a rising field of research. The advance of medical imaging technology over the last decades has allowed the evolution from generic to patient-specific 3D cardiac models that faithfully represent the anatomy and different cardiac features of a given alive subject. Here we analyse sixty representative 3D cardiac computational models developed and published during the last fifty years, describing their information sources, features, development methods and online availability. This paper also reviews the necessary components to build a 3D computational model of the heart aimed at biophysical simulation, paying especial attention to cardiac electrophysiology (EP), and the existing approaches to incorporate those components. We assess the challenges associated to the different steps of the building process, from the processing of raw clinical or biological data to the final application, including image segmentation, inclusion of substructures and meshing among others. We briefly outline the personalisation approaches that are currently available in 3D cardiac computational modelling. Finally, we present examples of several specific applications, mainly related to cardiac EP simulation and model-based image analysis, showing the potential usefulness of 3D cardiac computational modelling into clinical environments as a tool to aid in the prevention, diagnosis and treatment of cardiac diseases.

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