Semi-invasive 3D Mapping System for Cardiac Arrhythmias
Heart rhythm disturbances (arrhythmias) are common and may pose an imminent threat to patients. Some arrhythmias are responsible for a highly increased risk of ischemic strokes leading to a higher morbidity and mortality. Therefore, early detection and prevention of adverse arrhythmia-related events are crucial. Our project proposes a semi-invasive 3D mapping system for cardiac arrhythmias.
- Lead-Departement Technik und Informatik
- Institut Institute for Human Centered Engineering (HUCE)
- Förderorganisation SNF
- Laufzeit (geplant) 01.05.2016 - 31.12.2019
- Projektverantwortung Dr. Marcel Jacomet
- Projektleitung Dr. Marcel Jacomet
Dr. Marcel Jacomet
Dr. Josef Goette
Dr. Dr. med. Reto Wildhaber
Dr. Thomas Niederhauser
- Partner Inselspital Bern: Prof. Dr. med. Hildegard Tanner, Dr. Dr. med. Andreas Häberlin, Dr. Romy Sweda
- Schlüsselwörter Speiseröhren EKG, Herzrhythmusstörung, Katheterablation, Interventionsplanung, 3D Katheter, Sensorik, Elektroden, Hardware-Algorithmen, Mikroelektronik
Heart rhythm disturbances (arrhythmias) are common and may pose an imminent threat to patients. Some arrhythmias are responsible for a highly increased risk of ischemic strokes leading to a higher morbidity and mortality. Therefore, early detection and prevention of adverse arrhythmia-related events are crucial. In case where an interventional treatment of arrhythmias is indicated, the planning of the intervention strongly relies on the type of arrhythmia diagnosed based on standard 12-channel body surface electrocardiograms (ECGs). The diagnostic accuracy of this standard approach is however limited. Our approach is to complement these 12-channel surface ECGs by ECGs captured additionally from inside of the esophagus. The signal quality of these esophageal ECGs is superior to the surface ECGs due to the proximity of the measuring electrodes to the origin of the electrical signals from the heart’s muscle, the myocardium; additionally, we devise specially constructed catheters that allow a 3-dimensional description of the heart depolarization process. We expect that our new approach outperforms the diagnostic accuracy of the 12-channel ECGs and renders itself suitable to bedside decision making by providing more detailed information on arrhythmias.
The overall aim of the research project is to find technically realizable solutions that achieve the above stated objectives, and to validate the feasibility of the approach and to characterize its performance quality. In detail we research as follows: First, to exhaust the full potential of esophageal ECG measurements, we investigate on esophageal catheters with complex electrode configurations and algorithms to localize the spatial origin and the evolution of electrical depolarization in the heart. Second, with the resulting catheters we execute clinical trials that simultaneously capture esophageal ECG signals together with measurements of the exact depolarization inside of the heart using heart catheters during electrophysiology (EP) studies. Third, we use these data – the intracardiac measurements and the corresponding ECG signal from the esophagus – to search for an appropriate model for the 3D signal mapping from heart to esophagus as basis to research for an inverse mapping algorithm (esophageal ECG signals to heart depolarization propagation). Fourth, we validate the resulting algorithm with additional clinical electrophysiology studies, thereby we perform dedicated pacing and induction maneuvers to provoke various focal trigger activities in the heart. Healthcare professionals compare sensitivity and specificity of a correct arrhythmia identification using our approach and relate it to the diagnostic accuracy of standard 12-channel ECGs. Fifth, we research on hardware implementation architectures and partitioning of the devised signal processing algorithms for either low-power or high-speed objectives.
The defined research procedure reveals the tight link and strong interdependency of the five steps: the engineering side develops catheters, corresponding measurement techniques, and signal processing algorithms; the medical side uses these tools in their clinical work to produce measurement data, to validate the computational results, and to gain deeper insights for improving diagnosis and bedside decision making based on more detailed information on arrhythmias.