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Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models

Author

Listed:
  • Hermenegild J. Arevalo

    (Johns Hopkins University)

  • Fijoy Vadakkumpadan

    (Johns Hopkins University)

  • Eliseo Guallar

    (Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health)

  • Alexander Jebb

    (Johns Hopkins University)

  • Peter Malamas

    (Johns Hopkins University)

  • Katherine C. Wu

    (Johns Hopkins Medical Institutions)

  • Natalia A. Trayanova

    (Johns Hopkins University)

Abstract

Sudden cardiac death (SCD) from arrhythmias is a leading cause of mortality. For patients at high SCD risk, prophylactic insertion of implantable cardioverter defibrillators (ICDs) reduces mortality. Current approaches to identify patients at risk for arrhythmia are, however, of low sensitivity and specificity, which results in a low rate of appropriate ICD therapy. Here, we develop a personalized approach to assess SCD risk in post-infarction patients based on cardiac imaging and computational modelling. We construct personalized three-dimensional computer models of post-infarction hearts from patients’ clinical magnetic resonance imaging data and assess the propensity of each model to develop arrhythmia. In a proof-of-concept retrospective study, the virtual heart test significantly outperformed several existing clinical metrics in predicting future arrhythmic events. The robust and non-invasive personalized virtual heart risk assessment may have the potential to prevent SCD and avoid unnecessary ICD implantations.

Suggested Citation

  • Hermenegild J. Arevalo & Fijoy Vadakkumpadan & Eliseo Guallar & Alexander Jebb & Peter Malamas & Katherine C. Wu & Natalia A. Trayanova, 2016. "Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models," Nature Communications, Nature, vol. 7(1), pages 1-8, September.
  • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms11437
    DOI: 10.1038/ncomms11437
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    Cited by:

    1. Sergey Pravdin & Pavel Konovalov & Hans Dierckx & Olga Solovyova & Alexander V. Panfilov, 2020. "Drift of Scroll Waves in a Mathematical Model of a Heterogeneous Human Heart Left Ventricle," Mathematics, MDPI, vol. 8(5), pages 1-13, May.
    2. Dolors Serra & Pau Romero & Ignacio Garcia-Fernandez & Miguel Lozano & Alejandro Liberos & Miguel Rodrigo & Alfonso Bueno-Orovio & Antonio Berruezo & Rafael Sebastian, 2022. "An Automata-Based Cardiac Electrophysiology Simulator to Assess Arrhythmia Inducibility," Mathematics, MDPI, vol. 10(8), pages 1-21, April.
    3. Tobias Gerach & Steffen Schuler & Jonathan Fröhlich & Laura Lindner & Ekaterina Kovacheva & Robin Moss & Eike Moritz Wülfers & Gunnar Seemann & Christian Wieners & Axel Loewe, 2021. "Electro-Mechanical Whole-Heart Digital Twins: A Fully Coupled Multi-Physics Approach," Mathematics, MDPI, vol. 9(11), pages 1-33, May.
    4. Pravdin, Sergei F. & Dierckx, Hans & Panfilov, Alexander V., 2019. "Drift of scroll waves in a generic axisymmetric model of the cardiac left ventricle," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 222-233.
    5. William A. Ramírez & Alessio Gizzi & Kevin L. Sack & Simonetta Filippi & Julius M. Guccione & Daniel E. Hurtado, 2020. "On the Role of Ionic Modeling on the Signature of Cardiac Arrhythmias for Healthy and Diseased Hearts," Mathematics, MDPI, vol. 8(12), pages 1-19, December.
    6. Pavel Konovalov & Daria Mangileva & Arsenii Dokuchaev & Olga Solovyova & Alexander V. Panfilov, 2021. "Rotational Activity around an Obstacle in 2D Cardiac Tissue in Presence of Cellular Heterogeneity," Mathematics, MDPI, vol. 9(23), pages 1-15, November.
    7. Arsenii Dokuchaev & Alexander V. Panfilov & Olga Solovyova, 2020. "Myocardial Fibrosis in a 3D Model: Effect of Texture on Wave Propagation," Mathematics, MDPI, vol. 8(8), pages 1-16, August.
    8. Daria Mangileva & Pavel Konovalov & Arsenii Dokuchaev & Olga Solovyova & Alexander V. Panfilov, 2021. "Period of Arrhythmia Anchored around an Infarction Scar in an Anatomical Model of the Human Ventricles," Mathematics, MDPI, vol. 9(22), pages 1-15, November.

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