Insights Into the Spatiotemporal Patterns of Complexity of Ventricular Fibrillation by Multilead Analysis of Body Surface Potential Maps

Marianna Meo; Arnaud Denis; Frédéric Sacher; Josselin Duchâteau; Ghassen Cheniti; Stéphane Puyo; Laura Bear; Pierre Jaïs; Mélèze Hocini; Michel Haïssaguerre; Olivier Bernus; Rémi Dubois

doi:10.3389/fphys.2020.554838

Insights Into the Spatiotemporal Patterns of Complexity of Ventricular Fibrillation by Multilead Analysis of Body Surface Potential Maps

Front Physiol. 2020 Sep 23:11:554838. doi: 10.3389/fphys.2020.554838. eCollection 2020.

Authors

Marianna Meo^{1

2

3}, Arnaud Denis^{1

4}, Frédéric Sacher^{1

4}, Josselin Duchâteau^{1

2

3

4}, Ghassen Cheniti^{1

4}, Stéphane Puyo^{1

4}, Laura Bear^{1

2

3}, Pierre Jaïs^{1

2

3

4}, Mélèze Hocini^{1

2

3

4}, Michel Haïssaguerre^{1

2

3

4}, Olivier Bernus^{1

2

3}, Rémi Dubois^{1

2

3}

Affiliations

¹ Institute of Electrophysiology and Heart Modeling (IHU Liryc), Foundation Bordeaux University, Bordeaux, France.
² Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, University of Bordeaux, Bordeaux, France.
³ Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, Institut National de la Santé et de la Recherche Médicale, Bordeaux, France.
⁴ Electrophysiology and Ablation Unit, Bordeaux University Hospital, Bordeaux, France.

Abstract

Background: Ventricular fibrillation (VF) is the main cause of sudden cardiac death, but its mechanisms are still unclear. We propose a noninvasive approach to describe the progression of VF complexity from body surface potential maps (BSPMs).

Methods: We mapped 252 VF episodes (16 ± 10 s) with a 252-electrode vest in 110 patients (89 male, 47 ± 18 years): 50 terminated spontaneously, otherwise by electrical cardioversion (DCC). Changes in complexity were assessed between the onset ("VF start") and the end ("VF end") of VF by the nondipolar component index (N D I _{B S P M} ), measuring the fraction of energy nonpreserved by an equivalent 3D dipole from BSPMs. Higher NDI reflected lower VF organization. We also examined other standard body surface markers of VF dynamics, including fibrillatory wave amplitude (A _BSPM ), surface cycle length (BsCL _BSPM ) and Shannon entropy (S h E n _{B S P M} ). Differences between patients with and without structural heart diseases (SHD, 32 vs. NSHD, 78) were also tested at those stages. Electrocardiographic features were validated with simultaneous endocardium cycle length (CL) in a subset of 30 patients.

Results: All BSPM markers measure an increase in electrical complexity during VF (p < 0.0001), and more significantly in NSHD patients. Complexity is significantly higher at the end of sustained VF episodes requiring DCC. Intraepisode intracardiac CL shortening (VF start 197 ± 24 vs. VF end 169 ± 20 ms; p < 0.0001) correlates with an increase in NDI, and decline in surface CL, f-wave amplitude, and entropy (p < 0.0001). In SHD patients VF is initially more complex than in NSHD patients (N D I _{B S P M} , p = 0.0007; S h E n _{B S P M} , p < 0.0001), with moderately slower (BsCL _BSPM , p = 0.06), low-amplitude f-waves (A _BSPM , p < 0.0001). In this population, lower NDI (p = 0.004) and slower surface CL (p = 0.008) at early stage of VF predict self-termination. In the NSHD group, a more abrupt increase in VF complexity is quantified by all BSPM parameters during sustained VF (p < 0.0001), whereas arrhythmia evolution is stable during self-terminating episodes, hinting at additional mechanisms driving VF dynamics.

Conclusion: Multilead BSPM analysis underlines distinct degrees of VF complexity based on substrate characteristics.

Keywords: body surface potential maps; complexity; electrocardiology; singular value decomposition; structural diseases; sudden cardiac death; ventricular fibrillation; ventricular fibrillation mechanisms.