EP-PINNs: cardiac electrophysiology characterisation using physics-informed neural networks
File(s)
Working paper
Author(s)
Type
Working Paper
Abstract
Accurately inferring underlying electrophysiological (EP) tissue properties
from action potential recordings is expected to be clinically useful in the
diagnosis and treatment of arrhythmias such as atrial fibrillation, but it is
notoriously difficult to perform. We present EP-PINNs (Physics-Informed Neural
Networks), a novel tool for accurate action potential simulation and EP
parameter estimation, from sparse amounts of EP data. We demonstrate, using 1D
and 2D in silico data, how EP-PINNs are able to reconstruct the spatio-temporal
evolution of action potentials, whilst predicting parameters related to action
potential duration (APD), excitability and diffusion coefficients. EP-PINNs are
additionally able to identify heterogeneities in EP properties, making them
potentially useful for the detection of fibrosis and other localised pathology
linked to arrhythmias. Finally, we show EP-PINNs effectiveness on biological in
vitro preparations, by characterising the effect of anti-arrhythmic drugs on
APD using optical mapping data. EP-PINNs are a promising clinical tool for the
characterisation and potential treatment guidance of arrhythmias.
from action potential recordings is expected to be clinically useful in the
diagnosis and treatment of arrhythmias such as atrial fibrillation, but it is
notoriously difficult to perform. We present EP-PINNs (Physics-Informed Neural
Networks), a novel tool for accurate action potential simulation and EP
parameter estimation, from sparse amounts of EP data. We demonstrate, using 1D
and 2D in silico data, how EP-PINNs are able to reconstruct the spatio-temporal
evolution of action potentials, whilst predicting parameters related to action
potential duration (APD), excitability and diffusion coefficients. EP-PINNs are
additionally able to identify heterogeneities in EP properties, making them
potentially useful for the detection of fibrosis and other localised pathology
linked to arrhythmias. Finally, we show EP-PINNs effectiveness on biological in
vitro preparations, by characterising the effect of anti-arrhythmic drugs on
APD using optical mapping data. EP-PINNs are a promising clinical tool for the
characterisation and potential treatment guidance of arrhythmias.
Date Issued
2021-12-14
Citation
2021
Publisher
arXiv
Copyright Statement
© 2021 The Author(s). This work is published under the CC BY 4.0 International license.
License URL
Sponsor
Rosetrees Trust
Identifier
http://arxiv.org/abs/2112.07703v1
Grant Number
A1173/ M577
Subjects
physics.med-ph
physics.med-ph
physics.bio-ph
q-bio.QM
Publication Status
Published