Interpreting Activation Mapping of Atrial Fibrillation: A Hybrid Computational/Physiological Study

Abstract

Atrial fibrillation is the most common rhythm disorder of the heart associated with a rapid and irregular beating of the upper chambers. Activation mapping remains the gold standard to diagnose and interpret atrial fibrillation. However, fibrillatory activation maps are highly sensitive to far-field effects, and often disagree with other optical mapping modalities. Here we show that computational modeling can identify spurious non-local components of atrial fibrillation electrograms and improve activation mapping. We motivate our approach with a cohort of patients with potential drivers of persistent atrial fibrillation. In a computational study using a monodomain Maleckar model, we demonstrate that in organized rhythms, electrograms successfully track local activation, whereas in atrial fibrillation, electrograms are sensitive to spiral wave distance and number, spiral tip trajectories, and effects of fibrosis. In a clinical study, we analyzed n = 15 patients with persistent atrial fibrillation that was terminated by limited ablation. In five cases, traditional activation maps revealed a spiral wave at sites of termination; in ten cases, electrogram timings were ambiguous and activation maps showed incomplete reentry. By adjusting electrogram timing through computational modeling, we found rotational activation, which was undetectable with conventional methods. Our results demonstrate that computational modeling can identify non-local deflections to improve activation mapping and explain how and where ablation can terminate persistent atrial fibrillation. Our hybrid computational/physiological approach has the potential to optimize map-guided ablation and improve ablation therapy in atrial fibrillation.

Keywords: Atrial fibrillation; Electrogram; Electrophysiology; Rotors; Simulation; Spiral waves.

Conflict of interest statement

Conflict of Interest

Sanjiv Narayan is co-author of intellectual property owned by the University of California Regents and licensed to Topera Inc. He held equity in Topera and received honoraria from Medtronic and St. Jude Medical. The other authors declare no conflict of interest.

Figures

Figure 1

Mapped mechanisms at the site of atrial fibrillation termination by ablation depend on which electrogram deflection is selected. A) Four atrial fibrillation cycles are shown with annotations of voltages (black trace) in the selected cycle based on minimum negative dV/dt (green trace). D3 has 3 similar deflections. B) Localized ablation at this site terminated atrial fibrillation. Mechanisms at the site of termination vary for selection of i) first or ii) second deflections, which reveal a focal impulse or partial rotational circuits; iii) third deflection, which reveals a complete rotation.

Figure 2

Precessing spiral wave trajectory causes variable atrial fibrillation electrograms; with similar local and far-field components on clinically sized electrodes. A) Isopotential snapshots of the spiral wave. Insets 1–6 show zoomed views with black lines representing spiral tip trajectory, at times referenced to electrograms. B) Electrograms for electrodes of diameters marked by concentric circles in panel A. Recorded activity depends on electrode size independent of spacing. C) Transmembrane action potentials. Time 1 indicates non-local activity from a passing wave, especially on larger electrodes. At time 2, low amplitude signals reflect tight turn of the spiral tip. At times 3 and 4, electrograms represent activation. Time 5 represents non-local activation from the nearby passing wave, which is difficult to separate from the next true activation at time 6. Vertical black lines mark onset (minimum dV/dt) in each electrogram.

Figure 3

Atrial fibrillation electrograms poorly represents timing of local activity in the presence of substantial fibrotic remodeling and for larger electrodes. A) Spiral wave propagates through fibrotic tissue, with electrodes of varying diameters marked by concentric circles. Panels 1–3 are isopotential snapshots at marked times; Panel D indicates fibrotic region. B) Atrial fibrillation electrograms generated by different electrodes sizes, with black lines marking minimum dV/dt. Large electrodes (3, 5mm) record a non-local deflection of the wave front that is passing nearby at time 1, whereas small electrodes (0, 1mm) record a deflection that is not a complete activation at time 2 (Panel A, time 2, light blue). C) Action potential at the electrode site is complex due to the interaction of fibrotic and remodeled tissue.

Figure 4

Errors in atrial fibrillation timing, number of electrogram deflections, and electrogram upstroke velocity varying with electrode size. For all simulations (panels A–C), electrograms with 2 deflections present increased error with respect to the local activation times, were further from the spiral tip and decreased dV/dt of the deflection. Significant differences are marked with (*).

Figure 5

Estimation of distance to spiral tip based on time difference between electrogram deflections in atrial fibrillation. A linear trend (p 83 for all electrodes) was observed for each electrode size, with a positive correlation between the time interval between deflections and distance to the spiral tip at the time of the maximum negative dV/dt. 95% prediction intervals are shown in gray and have a range of 3mm for any given time difference.

Figure 6

Improved prediction of activation times in low dv/dt electrograms. By always selecting the second deflection as local activation time in cases of low dV/dt magnitude, we reduced the error to that seen in single deflection electrograms using clinically sized electrodes (independent t-test: p

Figure 7

Applying a second deflection criterion changes the detection of atrial fibrillation mechanisms. A) In this 67 years old man marking the channels by maximum negative dV/dt (red lines), gives a map with a focal pattern of atrial fibrillation B). However, in those channels with low dV/dt (C4, C5, C6), applying the proposed rule of taking the second plausible negative dV/dt reveals a rotational circuit C), where earliest activation (red) meets latest activation (blue). Ablation at this site terminated atrial fibrillation.