Mapping of cardiac electrophysiology onto a dynamic patient-specific heart model.
Electrophysiological cardiac data mapping is an essential tool for the study of cardiac rhythm disorders, such as atrial fibrillation. Over the past decade, various advanced cardiac mapping systems have been developed to create detailed cardiac maps and assist physicians in diagnosis and therapy guidance. While these systems have increased the ability to study and treat cardiac arrhythmias, inherent limitations exist. The objective of this paper is to describe and evaluate a system that extends current approaches to cardiac mapping, to create a dynamic cardiac map, using patient-specific cardiac models. This paper details novel approaches to collecting a stream of electrophysiological cardiac data, registering the data with patient-specific dynamic cardiac models, and displaying the data directly on the dynamic model surface, giving a more accurate and comprehensive visualization environment when compared to current systems. To validate the system, a series of laboratory and in vivo experiments were conducted. In the laboratory studies, the system was used to test the user's ability to accurately locate a landmark in physical space, as well as their ability to accurately navigate to a virtual location. In the in vivo studies the overall system performance was compared to an existing electrophysiological recording system, where right atrial cardiac maps were created during sinus and paced cardiac rhythms. The results showed that the new dynamic cardiac mapping system was able to maintain high accuracy in locating physical and virtual landmarks, while being able to create a dynamic cardiac map displayed on a dynamic cardiac surface model.
Imaging Research Labs, Robarts Research Institute, London, ON N6A 5K8, Canada. kevin.wilson@vanderbilt.edu
Kevin
K
Wilson
Gerard
G
Guiraudon
Douglas L
DL
Jones
Terry M
TM
Peters
D001281:Atrial Fibrillation / Q000175:diagnosis*; D018780:Body Surface Potential Mapping / Q000379:methods*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008955:Models, Cardiovascular; D009206:Myocardium / Q000473:pathology*; D014584:User-Computer Interface