Abstract
The ability to record and analyse electrical behaviour across the heart using optical and electrode mapping has revolutionised cardiac research. However, wider uptake of these technologies is constrained by the lack of multi-functional and robustly characterised analysis and mapping software. We present ElectroMap, an adaptable, high-throughput, open-source software for processing, analysis and mapping of complex electrophysiology datasets from diverse experimental models and acquisition modalities. Key innovation is development of standalone module for quantification of conduction velocity, employing multiple methodologies, currently not widely available to researchers. ElectroMap has also been designed to support multiple methodologies for accurate calculation of activation, repolarisation, arrhythmia detection, calcium handling and beat-to-beat heterogeneity. ElectroMap implements automated signal segmentation, ensemble averaging and integrates optogenetic approaches. Here we employ ElectroMap for analysis, mapping and detection of pro-arrhythmic phenomena in silico, in cellulo, animal model and in vivo patient datasets. We anticipate that ElectroMap will accelerate innovative cardiac research and enhance the uptake, application and interpretation of mapping technologies leading to novel approaches for arrhythmia prevention.
Highlights
The incidence and prevalence of cardiac diseases continues to increase every year[1,2]
We have developed a comprehensive conduction velocity (CV) analysis module within ElectroMap (Supplementary Fig. IV), to overcome a multitude of complexities and potential user-bias associated with CV calculations[18,24]
We demonstrate the compatibility of ElectroMap with a variety of camera types, species and experimental models
Summary
The incidence and prevalence of cardiac diseases continues to increase every year[1,2]. Further uptake and wider application is hindered by limitations with respect to data processing and analysis This challenge is intensified as developing camera technology provides ever-increasing spatio-temporal resolution. Multiple processing algorithms are employed before the underlying data can be interpreted[14,15] These algorithms require computational expertise to implement and are commonly developed and used within individual research groups, utilising techniques specific to camera resolution, file type and animal species. We present novel and robust open-source software, ElectroMap, for analysis of voltage and calcium optical mapping data. A key innovation is the introduction of a comprehensive CV module for robust investigation of CV changes This module integrates established single vector[18] and multi vector[20] techniques for CV measurement as well as a novel “activation constant” analysis. We employ ElectroMap for analysis, mapping and detection of pro-arrhythmic phenomena in silico, in cellulo, animal model and in vivo patient datasets, and demonstrate its utility for cardiac research
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