A technique for measuring anisotropy in atrial conduction to estimate conduction velocity and atrial fibre direction

Highlights

• We developed a technique for estimating conduction anisotropy and fibre direction.

• To estimate anisotropy, we fit elliptical wavefront propagation to a single activation map.

• Using three activation maps provided accurate estimation of conduction anisotropy.

• We demonstrated heterogeneous conduction anisotropy in clinical recordings.

• Anisotropy affected predicted arrhythmia dynamics in computational simulation.

Abstract

Background

Cardiac conduction properties exhibit large variability, and affect patient-specific arrhythmia mechanisms. However, it is challenging to clinically measure conduction velocity (CV), anisotropy and fibre direction. Our aim is to develop a technique to estimate conduction anisotropy and fibre direction from clinically available electrical recordings.

Methods

We developed and validated automated algorithms for estimating cardiac CV anisotropy, from any distribution of recording locations on the atrial surface. The first algorithm is for elliptical wavefront fitting to a single activation map (method 1), which works well close to the pacing location, but decreases in accuracy further from the pacing location (due to spatial heterogeneity in the conductivity and fibre fields). As such, we developed a second methodology for measuring local conduction anisotropy, using data from two or three activation maps (method 2: ellipse fitting to wavefront propagation velocity vectors from multiple activation maps).

Results

Ellipse fitting to CV vectors from two activation maps (method 2) leads to an improved estimation of longitudinal and transverse CV compared to method 1, but fibre direction estimation is still relatively poor. Using three activation maps with method 2 provides accurate estimation, with approximately $70\text{\%}$ of atrial fibres estimated within ${20}^{\circ }$. We applied the technique to clinical activation maps to demonstrate the presence of heterogeneous conduction anisotropy, and then tested the effects of this conduction anisotropy on predicted arrhythmia dynamics using computational simulation.

Conclusions

We have developed novel algorithms for calculating CV and measuring the direction dependency of atrial activation to estimate atrial fibre direction, without the need for specialised pacing protocols, using clinically available electrical recordings.