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 and Pavlovic, Davor (2020). Temporal irregularity quantification and mapping of optical action potentials using wave morphology similarity. Progress in Biophysics and Molecular Biology, 157 pp. 84–93.

DOI: https://doi.org/10.1016/j.pbiomolbio.2019.12.004


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.

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.

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