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, Jahrgang 157, 11.2020, S. 84-93.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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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 -