Comparison of three artificial models of the magnetohydrodynamic effect on the electrocardiogram.

Comput Methods Biomech Biomed Engin

a Department of Engineering Science , Institute of Biomedical Engineering, University of Oxford, Oxford , UK.

Published: January 2016

AI Article Synopsis

  • The study addresses the challenges of the magnetohydrodynamic (MHD) effect, which interferes with ECG analysis during MRI due to the flow of charged particles in blood within a magnetic field.
  • A new MHD model utilizing MRI-based 4D blood flow measurements is proposed, extending evaluations across multiple cardiac cycles to enhance ECG acquisition realism and assess MHD suppression techniques.
  • Results show that the new model offers a better approximation of observed MHD effects compared to existing models, with improved correlation and documentation, and the source code will be available as open-source for further advancements.

Article Abstract

The electrocardiogram (ECG) is often acquired during magnetic resonance imaging (MRI), but its analysis is restricted by the presence of a strong artefact, called magnetohydrodynamic (MHD) effect. MHD effect is induced by the flow of electrically charged particles in the blood perpendicular to the static magnetic field, which creates a potential of the order of magnitude of the ECG and temporally coincident with the repolarisation period. In this study, a new MHD model is proposed by using MRI-based 4D blood flow measurements made across the aortic arch. The model is extended to several cardiac cycles to allow the simulation of a realistic ECG acquisition during MRI examination and the quality assessment of MHD suppression techniques. A comparison of two existing models, based, respectively, on an analytical solution and on a numerical method-based solution of the fluids dynamics problem, is made with the proposed model and with an estimate of the MHD voltage observed during a real MRI scan. Results indicate a moderate agreement between the proposed model and the estimated MHD model for most leads, with an average correlation factor of 0.47. However, the results demonstrate that the proposed model provides a closer approximation to the observed MHD effects and a better depiction of the complexity of the MHD effect compared with the previously published models, with an improved correlation (+5%), coefficient of determination (+22%) and fraction of energy (+1%) compared with the best previous model. The source code will be made freely available under an open source licence to facilitate collaboration and allow more rapid development of more accurate models of the MHD effect.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4208987PMC
http://dx.doi.org/10.1080/10255842.2014.909090DOI Listing

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