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Cited by 557Cardiac electrophysiology and arrhythmiasCardiac Arrhythmias and TreatmentsCardiac pacing and defibrillation studies

A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models.

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Bayer, J. D., Blake, R. C., Plank, G., Trayanova, N. A.·2012·Annals of Biomedical Engineering
DOI 10.1007/s10439-012-0593-5PMC PMC3518842
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Abstract

Electrical waves traveling throughout the myocardium elicit muscle contractions responsible for pumping blood throughout the body. The shape and direction of these waves depend on the spatial arrangement of ventricular myocytes, termed fiber orientation. In computational studies simulating electrical wave propagation or mechanical contraction in the heart, accurately representing fiber orientation is critical so that model predictions corroborate with experimental data. Typically, fiber orientation is assigned to heart models based on Diffusion Tensor Imaging (DTI) data, yet few alternative methodologies exist if DTI data is noisy or absent. Here we present a novel Laplace-Dirichlet Rule-Based (LDRB) algorithm to perform this task with speed, precision, and high usability. We demonstrate the application of the LDRB algorithm in an image-based computational model of the canine ventricles. Simulations of electrical activation in this model are compared to those in the same geometrical model but with DTI-derived fiber orientation. The results demonstrate that activation patterns from simulations with LDRB and DTI-derived fiber orientations are nearly indistinguishable, with relative differences ≤6%, absolute mean differences in activation times ≤3.15 ms, and positive correlations ≥0.99. These results convincingly show that the LDRB algorithm is a robust alternative to DTI for assigning fiber orientation to computational heart models.

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Authors
Bayer, J. D., Blake, R. C., Plank, G., & Trayanova, N. A.
Affiliations
  • Johns Hopkins University (US)
  • Medical University of Graz (AT)
Corresponding author
Bayer, J. D.
ORCID
Venue
Annals of Biomedical Engineering
Publisher
Springer Science and Business Media LLC
Published
2012-05-31
Volume
40
Issue
10
Pages
2243-2254
ISSN
  • 0090-6964 (ISSN-L)
  • 1573-9686
DOI
10.1007/s10439-012-0593-5
PMC
PMC3518842
OpenAlex
W2132670047
Cited by
557
References
0
Citations by year
2026: 47 · 2025: 54 · 2024: 45 · 2023: 61 · 2022: 59 · 2021: 59 · 2020: 49 · 2019: 47 · 2018: 35 · 2017: 24 · 2016: 23 · 2015: 24 · 2014: 14 · 2013: 14 · 2012: 1
FWCI
10.91
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Annals of Biomedical Engineering (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Science Foundation
  • American Heart Association
  • Austrian Science Fund
  • Université de Bordeaux
  • National Institutes of Health
  • National Heart, Lung, and Blood Institute (R01HL103428, R01 HL10119601, R01HL101196, R01HL105216, HL103428, R01HL082729)
  • Division of Chemical, Bioengineering, Environmental, and Transport Systems
Topics
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac electrophysiology and arrhythmias
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac Arrhythmias and Treatments
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac pacing and defibrillation studies
Keywords
myocardial fiber orientation, rule-based algorithm, electrical wave propagation, ventricular myocytes, canine ventricle
MeSH terms
Algorithms, Animals, Computer Simulation, Dogs, Humans, Image Processing, Computer-Assisted, Models, Cardiovascular, Myocardium, Myofibrils, Radiography, Diffusion Tensor Imaging

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