Overcoming Barriers to Quantification and Comparison of Electrocardiographic Imaging Methods: A Community-Based Approach.

Abstract

There has been a recent upsurge in the development of electrocardiographic imaging (ECGI) methods, along with a significant increase in clinical application. To better assess the state-of-the-art, enable reliable progress, and facilitate clinical adoption, it is important to be able to compare results in a comprehensive manner, scientifically and clinically. However, studies vary in modeling choices, computational methods, validation mechanisms and metrics, and clinical applications, making unified evaluation and comparison of ECGI a critical challenge. This paper describes initial results of a project to address this challenge via a community-based approach organized by the Consortium for Electrocardiographic Imaging (CEI). We detail different aspects of this collective effort including a data sharing repository, a platform for comparison of different algorithms and modeling approaches on the same datasets, several active workgroups and progress made along these directions. We also summarize the results from groups participating in this collaboration and contributing solutions by applying their methods to the same dataset for comparison.