Electrocardiographic Imaging (ECGI) is an approach that aims to improve noninvasive cardiac abnormality detection and treatment, but its translation into clinical use is still hindered by technical challenges. The Consortium for ECG Imaging (CEI) has formed several collaborative projects to evaluate and improve technical aspects of ECGI including: model generation, inverse calculation method, activation and recovery time determination, signal pre-processing, and others. Each of these groups has made progress to improve ECGI, but these efforts are not yet implemented into an integrated software framework.
We developed a framework to unify the multiple techniques and stages of ECGI into one pipeline. This framework merges existing open source packages: SCIRun, a problem solving environment; the Forward/Inverse toolkit, a series of SCIRun modules for ECGI; and PFEIFER, a cardiac signal pre-processing tool.
Our unified ECGI tool, combined with the EDGAR dataset, allows users to test and validate a vast array of parameters within each stage of the ECGI pipeline. Users can input geometry and bioelectric signals, pre-process the data, compute the ECGI, evaluate the results, and visualize all stages in one pipeline. Users can also modify each aspect of the pipeline, for instance, PFEIFER can be used to test the roles of beat selection and filter choice in the ECGI pipeline. Users can also replace each stage with custom MATLAB or Python methods through SCIRun's scripting interfaces.
This new framework unites many of pieces in ECGI, which have typically been performed by separate tools, into one pipeline. We expect that this unified tool will help introduce researchers to ECGI, facilitate interaction between the various groups working on ECGI, and establish a common approach for researchers to test and validate their ECGI techniques.