Three-dimensional cardiac electrical imaging from intracavity recordings.
A novel approach is proposed to image 3-D cardiac electrical activity from intracavity electrical recordings with the aid of a catheter. The feasibility and performance were evaluated by computer simulation studies, where a 3-D cellular-automaton heart model and a finite-element thorax volume conductor model were utilized. The finite-element method (FEM) was used to simulate the intracavity recordings induced by a single-site and dual-site pacing protocol. The 3-D ventricular activation sequences as well as the locations of the initial activation sites were inversely estimated by minimizing the dissimilarity between the intracavity potential "measurements" and the model-generated intracavity potentials. Under single-site pacing, the relative error (RE) between the true and estimated activation sequences was 0.03 +/- 0.01 and the localization error (LE) (of the initiation site) was 1.88 +/- 0.92 mm, as averaged over 12 pacing trials when considering 25 microV additive measurement noise using 64 catheter electrodes. Under dual-site pacing, the RE was 0.04 +/- 0.01 over 12 pacing trials and the LE over 24 initial pacing sites was 2.28 +/- 1.15 mm, when considering 25 microV additive measurement noise using 64 catheter electrodes. The proposed 3-D cardiac electrical imaging approach using intracavity electrical recordings was also tested under various simulated conditions and robust inverse solutions obtained. The present promising simulation results suggest the feasibility of obtaining 3-D information of cardiac electrical activity from intracavity recordings. The application of this inverse method has the potential of enhancing electrocardiographic mapping by catheters in electrophysiology laboratories, aiding cardiac resynchronization therapy, and other clinical applications.
He
Bin
B
University of Minnesota, Department of Biomedical Engineering, 7-105 NHH, 312 Church Street SE, Minneapolis, MN 55455, USA. binhe@umn.edu
Liu
Chenguang
C
Zhang
Yingchun
Y
D000465:Algorithms; D001185:Artificial Intelligence; D018780:Body Surface Potential Mapping / Q000379:methods*; D003198:Computer Simulation; D003952:Diagnostic Imaging / Q000379:methods*; D005240:Feasibility Studies; D006329:Heart Conduction System / Q000502:physiology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008955:Models, Cardiovascular