Advanced search
1 file | 5.82 MB Add to list

Numerical methods for the detection of phase defect structures in excitable media

(2022) PLOS ONE. 17(7).
Author
Organization
Project
Abstract
Electrical waves that rotate in the heart organize dangerous cardiac arrhythmias. Finding the region around which such rotation occurs is one of the most important practical questions for arrhythmia management. For many years, the main method for finding such regions was so-called phase mapping, in which a continuous phase was assigned to points in the heart based on their excitation status and defining the rotation region as a point of phase singularity. Recent analysis, however, showed that in many rotation regimes there exist phase discontinuities and the region of rotation must be defined not as a point of phase singularity, but as a phase defect line. In this paper, we use this novel methodology and perform a comparative study of three different phase definitions applied to in silico data and to experimental data obtained from optical voltage mapping experiments on monolayers of human atrial myocytes. We introduce new phase defect detection algorithms and compare them with those that appeared in literature already. We find that the phase definition is more important than the algorithm to identify sudden spatial phase variations. Sharp phase defect lines can be obtained from a phase derived from local activation times observed during one cycle of arrhythmia. Alternatively, similar quality can be obtained from a reparameterization of the classical phase obtained from observation of a single timeframe of transmembrane potential. We found that the phase defect line length was (35.9 +/- 6.2)mm in the Fenton-Karma model and (4.01 +/- 0.55)mm in cardiac human atrial myocyte monolayers. As local activation times are obtained during standard clinical cardiac mapping, the methods are also suitable to be applied to clinical datasets. All studied methods are publicly available and can be downloaded from an institutional web-server.
Keywords
Multidisciplinary

Downloads

  • DierckxPanfilovPLOS2022.pdf
    • full text (Published version)
    • |
    • open access
    • |
    • PDF
    • |
    • 5.82 MB

Citation

Please use this url to cite or link to this publication:

MLA
Kabus, Desmond, et al. “Numerical Methods for the Detection of Phase Defect Structures in Excitable Media.” PLOS ONE, edited by Ivan Kryven, vol. 17, no. 7, Public Library of Science (PLoS), 2022, doi:10.1371/journal.pone.0271351.
APA
Kabus, D., Arno, L., Leenknegt, L., Panfilov, A., & Dierckx, H. (2022). Numerical methods for the detection of phase defect structures in excitable media. PLOS ONE, 17(7). https://doi.org/10.1371/journal.pone.0271351
Chicago author-date
Kabus, Desmond, Louise Arno, Lore Leenknegt, Alexander Panfilov, and Hans Dierckx. 2022. “Numerical Methods for the Detection of Phase Defect Structures in Excitable Media.” Edited by Ivan Kryven. PLOS ONE 17 (7). https://doi.org/10.1371/journal.pone.0271351.
Chicago author-date (all authors)
Kabus, Desmond, Louise Arno, Lore Leenknegt, Alexander Panfilov, and Hans Dierckx. 2022. “Numerical Methods for the Detection of Phase Defect Structures in Excitable Media.” Ed by. Ivan Kryven. PLOS ONE 17 (7). doi:10.1371/journal.pone.0271351.
Vancouver
1.
Kabus D, Arno L, Leenknegt L, Panfilov A, Dierckx H. Numerical methods for the detection of phase defect structures in excitable media. Kryven I, editor. PLOS ONE. 2022;17(7).
IEEE
[1]
D. Kabus, L. Arno, L. Leenknegt, A. Panfilov, and H. Dierckx, “Numerical methods for the detection of phase defect structures in excitable media,” PLOS ONE, vol. 17, no. 7, 2022.
@article{01H3248KYZ64WQ007HHC2Y96EX,
  abstract     = {{Electrical waves that rotate in the heart organize dangerous cardiac arrhythmias. Finding the region around which such rotation occurs is one of the most important practical questions for arrhythmia management. For many years, the main method for finding such regions was so-called phase mapping, in which a continuous phase was assigned to points in the heart based on their excitation status and defining the rotation region as a point of phase singularity. Recent analysis, however, showed that in many rotation regimes there exist phase discontinuities and the region of rotation must be defined not as a point of phase singularity, but as a phase defect line. In this paper, we use this novel methodology and perform a comparative study of three different phase definitions applied to in silico data and to experimental data obtained from optical voltage mapping experiments on monolayers of human atrial myocytes. We introduce new phase defect detection algorithms and compare them with those that appeared in literature already. We find that the phase definition is more important than the algorithm to identify sudden spatial phase variations. Sharp phase defect lines can be obtained from a phase derived from local activation times observed during one cycle of arrhythmia. Alternatively, similar quality can be obtained from a reparameterization of the classical phase obtained from observation of a single timeframe of transmembrane potential. We found that the phase defect line length was (35.9 +/- 6.2)mm in the Fenton-Karma model and (4.01 +/- 0.55)mm in cardiac human atrial myocyte monolayers. As local activation times are obtained during standard clinical cardiac mapping, the methods are also suitable to be applied to clinical datasets. All studied methods are publicly available and can be downloaded from an institutional web-server.}},
  articleno    = {{e0271351}},
  author       = {{Kabus, Desmond and Arno, Louise and Leenknegt, Lore and Panfilov, Alexander and Dierckx, Hans}},
  editor       = {{Kryven, Ivan}},
  issn         = {{1932-6203}},
  journal      = {{PLOS ONE}},
  keywords     = {{Multidisciplinary}},
  language     = {{eng}},
  number       = {{7}},
  pages        = {{31}},
  publisher    = {{Public Library of Science (PLoS)}},
  title        = {{Numerical methods for the detection of phase defect structures in excitable media}},
  url          = {{http://doi.org/10.1371/journal.pone.0271351}},
  volume       = {{17}},
  year         = {{2022}},
}

Altmetric
View in Altmetric
Web of Science
Times cited: