Impact of Catheter Configuration on the Mapping of Atrial Fibrillation.

Abstract

Background: Mapping of heart rhythms is influenced by the size and configuration of the mapping electrodes. Whether a recorded electrogram represents near (local) or remote activity influences diagnosis and treatment, yet is affected by mapping characteristics that are often undefined.

Methods: We developed biophysical computational models to predict interactions between the recording tool and cardiac tissue in coherent and disorganized rhythms, which we validated in clinical recordings.

Results: Biophysical computational models demonstrated the ability to quantify and visualize the recording antennae for different electrode configurations. Our results show that unipolar electrograms reflected a recording antenna within 3-dimensional ellipsoids of radius 8 mm across-tissue and 2.7 mm transmurally. Bipolar electrogram antennae align with propagation direction in ellipsoids of long axis radius 1.7, 5.7, and 8.3 mm for 2, 5, and 10 mm spacing, respectively, and often extend beyond the physical extent of electrodes. Notably, omnipolar electrograms, constructed from orthogonal bipoles in a triangular configuration, retained some directional preferences of bipolar electrograms, with a complex relationship between electrode orientation and wave direction. When tested clinically on high-resolution, narrow field (grid) catheters and moderate-to-low resolution, global (basket) catheters, antennae varied more with electrode type (correlation coefficient of 0.43 unipolar, 0.05 bipolar, and 0.26 omnipolar; P<0.001) and spacing (correlation coefficient of 0.36 versus 0.42; P=0.002) than the precise electrode size.

Conclusions: This novel computational-clinical system approach enabled us to systematically compare electrode configurations. This work may help interpret signals in complex biological rhythms, such as atrial fibrillation, and may influence the design of novel catheter configurations and signal processing approaches to identify local tissue signals.