Temporal irregularity quantification and mapping of optical action potentials using wave morphology similarity

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Temporal irregularity quantification and mapping of optical action potentials using wave morphology similarity. / O'Shea, Christopher; Winter, James; Holmes, Andrew P; Johnson, Daniel M; Correia, Joao N; Kirchhof, Paulus; Fabritz, Larissa; Rajpoot, Kashif; Pavlovic, Davor.

In: PROG BIOPHYS MOL BIO, Vol. 157, 11.2020, p. 84-93.

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@article{2c936b7027ca47ef8cbcb6654e1ae3ff,
title = "Temporal irregularity quantification and mapping of optical action potentials using wave morphology similarity",
abstract = "BACKGROUND: Cardiac optical mapping enables direct and high spatio-temporal resolution recording of action potential (AP) morphology. Temporal alterations in AP morphology are both predictive and consequent of arrhythmia. Here we sought to test if methods that quantify regularity of recorded waveforms could be applied to detect and quantify periods of temporal instability in optical mapping datasets in a semi-automated, user-unbiased manner.METHODS AND RESULTS: We developed, tested and applied algorithms to quantify optical wave similarity (OWS) to study morphological temporal similarity of optically recorded APs. Unlike other measures (e.g. alternans ratio, beat-to-beat variability, arrhythmia scoring), the quantification of OWS is achieved without a restrictive definition of specific signal points/features and is instead derived by analysing the complete morphology from the entire AP waveform. Using model datasets, we validated the ability of OWS to measure changes in AP morphology, and tested OWS mapping in guinea pig hearts and mouse atria. OWS successfully detected and measured alterations in temporal regularity in response to several proarrhythmic stimuli, including alterations in pacing frequency, premature contractions, alternans and ventricular fibrillation.CONCLUSION: OWS mapping provides an effective measure of temporal regularity that can be applied to optical datasets to detect and quantify temporal alterations in action potential morphology. This methodology provides a new metric for arrhythmia inducibility and scoring in optical mapping datasets.",
keywords = "Action Potentials/physiology, Algorithms, Animals, Arrhythmias, Cardiac/physiopathology, Guinea Pigs, Heart/physiology, Heart Atria/physiopathology, Mice, Normal Distribution, Optics and Photonics, Time Factors, Ventricular Fibrillation/physiopathology",
author = "Christopher O'Shea and James Winter and Holmes, {Andrew P} and Johnson, {Daniel M} and Correia, {Joao N} and Paulus Kirchhof and Larissa Fabritz and Kashif Rajpoot and Davor Pavlovic",
note = "Copyright {\textcopyright} 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.",
year = "2020",
month = nov,
doi = "10.1016/j.pbiomolbio.2019.12.004",
language = "English",
volume = "157",
pages = "84--93",
journal = "PROG BIOPHYS MOL BIO",
issn = "0079-6107",
publisher = "Elsevier Limited",

}

RIS

TY - JOUR

T1 - Temporal irregularity quantification and mapping of optical action potentials using wave morphology similarity

AU - O'Shea, Christopher

AU - Winter, James

AU - Holmes, Andrew P

AU - Johnson, Daniel M

AU - Correia, Joao N

AU - Kirchhof, Paulus

AU - Fabritz, Larissa

AU - Rajpoot, Kashif

AU - Pavlovic, Davor

N1 - Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

PY - 2020/11

Y1 - 2020/11

N2 - BACKGROUND: Cardiac optical mapping enables direct and high spatio-temporal resolution recording of action potential (AP) morphology. Temporal alterations in AP morphology are both predictive and consequent of arrhythmia. Here we sought to test if methods that quantify regularity of recorded waveforms could be applied to detect and quantify periods of temporal instability in optical mapping datasets in a semi-automated, user-unbiased manner.METHODS AND RESULTS: We developed, tested and applied algorithms to quantify optical wave similarity (OWS) to study morphological temporal similarity of optically recorded APs. Unlike other measures (e.g. alternans ratio, beat-to-beat variability, arrhythmia scoring), the quantification of OWS is achieved without a restrictive definition of specific signal points/features and is instead derived by analysing the complete morphology from the entire AP waveform. Using model datasets, we validated the ability of OWS to measure changes in AP morphology, and tested OWS mapping in guinea pig hearts and mouse atria. OWS successfully detected and measured alterations in temporal regularity in response to several proarrhythmic stimuli, including alterations in pacing frequency, premature contractions, alternans and ventricular fibrillation.CONCLUSION: OWS mapping provides an effective measure of temporal regularity that can be applied to optical datasets to detect and quantify temporal alterations in action potential morphology. This methodology provides a new metric for arrhythmia inducibility and scoring in optical mapping datasets.

AB - BACKGROUND: Cardiac optical mapping enables direct and high spatio-temporal resolution recording of action potential (AP) morphology. Temporal alterations in AP morphology are both predictive and consequent of arrhythmia. Here we sought to test if methods that quantify regularity of recorded waveforms could be applied to detect and quantify periods of temporal instability in optical mapping datasets in a semi-automated, user-unbiased manner.METHODS AND RESULTS: We developed, tested and applied algorithms to quantify optical wave similarity (OWS) to study morphological temporal similarity of optically recorded APs. Unlike other measures (e.g. alternans ratio, beat-to-beat variability, arrhythmia scoring), the quantification of OWS is achieved without a restrictive definition of specific signal points/features and is instead derived by analysing the complete morphology from the entire AP waveform. Using model datasets, we validated the ability of OWS to measure changes in AP morphology, and tested OWS mapping in guinea pig hearts and mouse atria. OWS successfully detected and measured alterations in temporal regularity in response to several proarrhythmic stimuli, including alterations in pacing frequency, premature contractions, alternans and ventricular fibrillation.CONCLUSION: OWS mapping provides an effective measure of temporal regularity that can be applied to optical datasets to detect and quantify temporal alterations in action potential morphology. This methodology provides a new metric for arrhythmia inducibility and scoring in optical mapping datasets.

KW - Action Potentials/physiology

KW - Algorithms

KW - Animals

KW - Arrhythmias, Cardiac/physiopathology

KW - Guinea Pigs

KW - Heart/physiology

KW - Heart Atria/physiopathology

KW - Mice

KW - Normal Distribution

KW - Optics and Photonics

KW - Time Factors

KW - Ventricular Fibrillation/physiopathology

U2 - 10.1016/j.pbiomolbio.2019.12.004

DO - 10.1016/j.pbiomolbio.2019.12.004

M3 - SCORING: Journal article

C2 - 31899215

VL - 157

SP - 84

EP - 93

JO - PROG BIOPHYS MOL BIO

JF - PROG BIOPHYS MOL BIO

SN - 0079-6107

ER -