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Effects of Fibrotic Border Zone on Drivers for Atrial Fibrillation: An In-Silico Mechanistic Investigation

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Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers (STACOM 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14507))

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Abstract

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia that also carries a high risk of stroke. Catheter ablation has emerged as an effective treatment option for paroxysmal AF, but it results in high recurrence rates in persistent AF cases. Recent studies have highlighted the potential of low voltage- and fibrosis-substrate ablation as effective strategies for reducing AF recurrence. However, there is no mechanistic explanation for the success of substrate-based ablation. We use patient imaging and computational modelling to investigate such mechanisms. Left atrial (LA) models were constructed based on late gadolinium enhanced cardiac magnetic resonance (LGE-CMR) imaging data from a cohort of nine AF patients. Tissue conductivity was inversely proportional to the LGE-CMR image intensity. The impact of low-conductive fibrotic border zone (FBZ) was investigated by comparing conduction velocity (CV) maps and phase singularity (PS) distributions associated with re-entrant drivers for AF with and without its inclusion in each patient LA model. The model simulations revealed that PSs associated with AF drivers were predominantly located within regions of low CV (high LGE-CMR image intensity), either with or without of FBZ. The presence of FBZ facilitated the formation of PSs in regions deeper inside the dense fibrotic tissue, which were characterised by the lowest CV values. This contributed to the stabilisation of AF drivers in the fibrotic areas. Therefore, fibrotic areas characterised by the lowest CV provide the most likely substrate for AF drivers and can be targeted by ablation. Such patient-specific areas can include both the FBZ and deeper-lying regions of dense fibrosis.

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Acknowledgements

This work was supported by funding from the Medical Research Council [MR/N013700/1], the British Heart Foundation [PG/15/8/31130], and the Wellcome/EPSRC Centre for Medical Engineering [WT 203148/Z/16/Z].

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Authors and Affiliations

  1. School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK

    Shaheim Ogbomo-Harmitt, George Obada, Andrew P. King & Oleg Aslanidi

  2. Department of Physics and Astronomy, Ghent University, Ghent, Belgium

    Nele Vandersickel

Authors
  1. Shaheim Ogbomo-Harmitt
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  2. George Obada
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  3. Nele Vandersickel
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  4. Andrew P. King
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  5. Oleg Aslanidi
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Corresponding author

Correspondence to Shaheim Ogbomo-Harmitt .

Editor information

Editors and Affiliations

  1. Universitat Pompeu Fabra, Barcelona, Spain

    Oscar Camara

  2. King's College London, London, UK

    Esther Puyol-Antón

  3. Inria, Sophia Antipolis, France

    Maxime Sermesant

  4. King's College London, London, UK

    Avan Suinesiaputra

  5. Technische Universiteit Delft, Delft, The Netherlands

    Qian Tao

  6. Fudan University, Shanghai, China

    Chengyan Wang

  7. King's College London, London, UK

    Alistair Young

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Ogbomo-Harmitt, S., Obada, G., Vandersickel, N., King, A.P., Aslanidi, O. (2024). Effects of Fibrotic Border Zone on Drivers for Atrial Fibrillation: An In-Silico Mechanistic Investigation. In: Camara, O., et al. Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers. STACOM 2023. Lecture Notes in Computer Science, vol 14507. Springer, Cham. https://doi.org/10.1007/978-3-031-52448-6_17

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  • DOI: https://doi.org/10.1007/978-3-031-52448-6_17

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-52448-6

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