Cargando…

Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm

Sequences of low-energy electrical pulses can effectively terminate ventricular fibrillation (VF) and avoid the side effects of conventional high-energy electrical defibrillation shocks, including tissue damage, traumatic pain, and worsening of prognosis. However, the systematic optimisation of sequ...

Descripción completa

Detalles Bibliográficos
Autores principales: Aron, Marcel, Lilienkamp, Thomas, Luther, Stefan, Parlitz, Ulrich
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406519/
https://www.ncbi.nlm.nih.gov/pubmed/37555132
http://dx.doi.org/10.3389/fnetp.2023.1172454
_version_ 1785085761189576704
author Aron, Marcel
Lilienkamp, Thomas
Luther, Stefan
Parlitz, Ulrich
author_facet Aron, Marcel
Lilienkamp, Thomas
Luther, Stefan
Parlitz, Ulrich
author_sort Aron, Marcel
collection PubMed
description Sequences of low-energy electrical pulses can effectively terminate ventricular fibrillation (VF) and avoid the side effects of conventional high-energy electrical defibrillation shocks, including tissue damage, traumatic pain, and worsening of prognosis. However, the systematic optimisation of sequences of low-energy pulses remains a major challenge. Using 2D simulations of homogeneous cardiac tissue and a genetic algorithm, we demonstrate the optimisation of sequences with non-uniform pulse energies and time intervals between consecutive pulses for efficient VF termination. We further identify model-dependent reductions of total pacing energy ranging from ∼4% to ∼80% compared to reference adaptive-deceleration pacing (ADP) protocols of equal success rate (100%).
format Online
Article
Text
id pubmed-10406519
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-104065192023-08-08 Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm Aron, Marcel Lilienkamp, Thomas Luther, Stefan Parlitz, Ulrich Front Netw Physiol Network Physiology Sequences of low-energy electrical pulses can effectively terminate ventricular fibrillation (VF) and avoid the side effects of conventional high-energy electrical defibrillation shocks, including tissue damage, traumatic pain, and worsening of prognosis. However, the systematic optimisation of sequences of low-energy pulses remains a major challenge. Using 2D simulations of homogeneous cardiac tissue and a genetic algorithm, we demonstrate the optimisation of sequences with non-uniform pulse energies and time intervals between consecutive pulses for efficient VF termination. We further identify model-dependent reductions of total pacing energy ranging from ∼4% to ∼80% compared to reference adaptive-deceleration pacing (ADP) protocols of equal success rate (100%). Frontiers Media S.A. 2023-07-24 /pmc/articles/PMC10406519/ /pubmed/37555132 http://dx.doi.org/10.3389/fnetp.2023.1172454 Text en Copyright © 2023 Aron, Lilienkamp, Luther and Parlitz. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Network Physiology
Aron, Marcel
Lilienkamp, Thomas
Luther, Stefan
Parlitz, Ulrich
Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm
title Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm
title_full Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm
title_fullStr Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm
title_full_unstemmed Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm
title_short Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm
title_sort optimising low-energy defibrillation in 2d cardiac tissue with a genetic algorithm
topic Network Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406519/
https://www.ncbi.nlm.nih.gov/pubmed/37555132
http://dx.doi.org/10.3389/fnetp.2023.1172454
work_keys_str_mv AT aronmarcel optimisinglowenergydefibrillationin2dcardiactissuewithageneticalgorithm
AT lilienkampthomas optimisinglowenergydefibrillationin2dcardiactissuewithageneticalgorithm
AT lutherstefan optimisinglowenergydefibrillationin2dcardiactissuewithageneticalgorithm
AT parlitzulrich optimisinglowenergydefibrillationin2dcardiactissuewithageneticalgorithm