Analysis and visualization of intracardiac electrograms in diagnosis and research: Concept and application of KaPAVIE. Issue 127 (April 2016) - Oesterlein, Tobias Georg; Schmid, Jochen; Bauer, Silvio; Jadidi, Amir; Schmitt, Claus; Dössel, Olaf; Luik, Armin
Highlights: Need for novel algorithms in diagnosis and treatment of cardiac arrhythmias. Combined development using MATLAB and C++ VTK library. Allows for rapid implementation of new algorithms. Interactive visualization of cardiac anatomy, measured data and analysis results. Promotes interdisciplinary research and discussion. Abstract: Background and objective: Progress in biomedical engineering has improved the hardware available for diagnosis and treatment of cardiac arrhythmias. But although huge amounts of intracardiac electrograms (EGMs) can be acquired during electrophysiological examinations, there is still a lack of software aiding diagnosis. The development of novel algorithms for the automated analysis of EGMs has proven difficult, due to the highly interdisciplinary nature of this task and hampered data access in clinical systems. Thus we developed a software platform, which allows rapid implementation of new algorithms, verification of their functionality and suitable visualization for discussion in the clinical environment. Methods: A software for visualization was developed in Qt5 and C++ utilizing the class library of VTK. The algorithms for signal analysis were implemented in MATLAB. Clinical data for analysis was exported from electroanatomical mapping systems. Results: The visualization software KaPAVIE (Karlsruhe Platform for Analysis and Visualization of Intracardiac Electrograms) was implemented and tested on several clinical datasets. Both common and novel algorithms were implemented which address important clinical questions in diagnosis of different arrhythmias. It proved useful in discussions with clinicians due to its interactive and user-friendly design. Time after export from the clinical mapping system to visualization is below 5 min. Conclusion: KaPAVIE 2 is a powerful platform for the development of novel algorithms in the clinical environment. Simultaneous and interactive visualization of measured EGM data and the results of analysis will aid diagnosis and help understanding the underlying mechanisms of complex arrhythmias like atrial fibrillation.