Background Optical mapping is a powerful methodology, offering unparalleled high spatio-temporal resolution imaging of cardiac action potential and calcium handling across the heart. Processing and analysis of optical mapping data is computationally challenging to apply, preventing wider use of the technology. We have built-upon and extended established techniques to develop a standalone software platform (ElectroMap) for high-throughput analysis of optical mapping data. We developed and validated conduction velocity (CV) analysis module within ElectroMap, supporting established ’single‘ and ’multi‘ vector methods, as well as a novel method where tissue activation is visualised as an ‘activation curve’. Furthermore, automated pacing frequency recognition, comprehensive calcium handling analysis algorithms and alternans analysis module are developed and tested.

Methods and results All algorithms are developed in MATLAB. Conduction module and automated pacing frequency algorithms were validated in model data, and all three CV methodologies accurately measured changes in conduction. Further validation was performed on MF1 mouse atria (n=8) loaded with di-4-ANEPPS. Under normoxia (95% O2/5% CO2), increase in pacing frequency (3Hz>10 Hz) caused CV slowing (54.85±4.45 cm/s >48.71±4.75 cm/s) and increased time to 50% activation (1.95±0.53 ms to 2.37±0.81 ms, p<0.05). Hypoxia (95% N2/5% CO2) decreased CV to 39.33±4.14 cm/s (3 Hz, multi-vector method, p<0.0001) and increased activation time to 3.26±1.06 ms (p<0.01).

Calcium analysis algorithms were validated in mouse atria paced at incremental frequencies (3>8.33>10>12.5 Hz). Increasing pacing frequency led to progressively shorter calcium decay constant (T) values. Alternans induced at 12.5 Hz were accurately detected and quantified (peak, duration, release, load alternans) by the alternans analysis module. Spatial discordance could be visualised across the tissue.

Conclusions We present ElectroMap, a novel, high-throughput, software platform for processing and analysis of complex optical mapping datasets. We anticipate that ElectroMap will support future innovative cardiac research and broaden access to this exciting technology.