Systematic differences of non-invasive dominant frequency estimation compared to invasive dominant frequency estimation in atrial fibrillation

Frederique J Vanheusden,Gavin S Chu,Xin Li,João Salinet,Tiago P Almeida,Nawshin Dastagir,Peter J Stafford,G André Ng,Fernando S Schlindwein

doi:10.1016/j.compbiomed.2018.11.017

Abstract

Non-invasive analysis of atrial fibrillation (AF) using body surface mapping (BSM) has gained significant interest, with attempts at interpreting atrial spectro-temporal parameters from body surface signals. As these body surface signals could be affected by properties of the torso volume conductor, this interpretation is not always straightforward. This paper highlights the volume conductor effects and influences of the algorithm parameters for identifying the dominant frequency (DF) from cardiac signals collected simultaneously on the torso and atrial surface. Bi-atrial virtual electrograms (VEGMs) and BSMs were recorded simultaneously for 5 min from 10 patients undergoing ablation for persistent AF. Frequency analysis was performed on 4 s segments. DF was defined as the frequency with highest power between 4 and 10 Hz with and without applying organization index (OI) thresholds. The volume conductor effect was assessed by analyzing the highest DF (HDF) difference of each VEGM HDF against its BSM counterpart. Significant differences in HDF values between intra-cardiac and torso signals could be observed, independent of OI threshold. This difference increases with increasing endocardial HDF (BSM-VEGM median difference from −0.13 Hz for VEGM HDF at 6.25 ± 0.25 Hz to −4.24 Hz at 9.75 ± 0.25 Hz), thereby confirming the theory of the volume conductor effect in real-life situations. Applying an OI threshold strongly affected the BSM HDF area size and location and atrial HDF area location. These results suggest that volume conductor and measurement algorithm effects must be considered for appropriate clinical interpretation.

Highlights

Non-invasive analysis of atrial fibrillation (AF) using body surface maps (BSMs) to locate AF drivers has become increasingly popular in recent years [1,2,3,4], motivated by the reduced costs and risks compared to electrophysiological (EP) studies, and the development of accurate systems for inverse problem analysis of atrial activity [5,6]
A total of 1322 windows were available for highest dominant frequency (HDF) analysis on both virtual electrograms (VEGMs) and BSM data
After removing windows in which either VEGM or BSM data showed the potential of having detected a harmonic as the HDF, 1002 windows (75.80%) remained for further analysis

Summary

Introduction

Non-invasive analysis of atrial fibrillation (AF) using body surface maps (BSMs) to locate AF drivers has become increasingly popular in recent years [1,2,3,4], motivated by the reduced costs and risks compared to electrophysiological (EP) studies, and the development of accurate systems for inverse problem analysis of atrial activity [5,6]. With the advent of new metrics for identifying drivers of AF [7,8,9], establishing methods for directly correlating these metrics as measured on the body surface to AF sources has gained significant interest [10,11]. This area of research can be seen as a step between direct (invasive) measurement of AF behavior and the non-invasive estimation of AF sources using inverse problem analysis. BSMs can, be considered blurred images of cardiac signals, with body surface signals being weighted contributions of activity over the entire atrium [18]

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Discussion

Conclusion