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Correlation between conduction velocity and frequency analysis in patients with atrial fibrillation using high-density charge mapping

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Abstract

Spectral analysis of atrial signals has been used to identify regions of interest in atrial fibrillation (AF). However, the relationship to the atrial substrate is unclear. In this study, we compare regions with dominant frequency (DF), simultaneously determined in the left atrium (LA) by a novel noncontact mapping system using unipolar charge density signals, to the zones of slow conduction (SZ) during AF.

In 19 AF patients the conduction during AF was assessed by a validated algorithm and SZ compared to the DF and the DF ratio between the DF peak and the area under the total spectrum (DFR). The results were compared in five different regions of the LA. The reproducibility of SZ location at different time measurements was higher than for DF or DFR. The SZs are mainly confined at the anterior and posterior wall of the LA. There was no statistically significant correlation between SZ and DF or DFR across the atrium.

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Abbreviations

AF:

Atrial fibrillation

CAFE:

Complex fractionated electrogram

CD:

Charge density (C·cm−2)

CV:

Conduction velocity (m·s−1)

SZ:

Slow zone

LAT:

Local activation time (ms)

FFT:

Fast Fourrier transform

DF:

Dominant frequency (Hz)

DFR:

Dominant frequency ratio, the ratio between the DF peak and the area under the total spectrum

LA:

Left atrium

MV:

Mitral valve

LSPV:

Left pulmonary vein

LIPV:

Left inferior pulmonary vein

RSPV:

Right superior pulmonary vein

RIPV:

Right inferior pulmonary vein

LAA:

Left atrial appendage

References

  1. Sanders P, Berenfeld O, Hocini M, Jaïs P, Vaidyanathan R, Hsu L-F, Garrigue S, Takahashi Y, Rotter M, Sacher F, Scavée C, Ploutz-Snyder R, Jalife J, Haïssaguerre M (2005) Spectral analysis identifies sites of high-frequency activity maintaining atrial fibrillation in humans. Circulation 112(6):789–797

    Article  Google Scholar 

  2. Jarman JWE, Wong T, Kojodjojo P, Spohr H, Davies JE, Roughton M, Francis DP, Kanagaratnam P, Markides V, Davies DW, Peters NS (2012) Spatiotemporal behavior of high dominant frequency during paroxysmal and persistent atrial fibrillation in the human left atrium. Circ Arrhythmia electrophysiol 5(4):650–658

    Article  Google Scholar 

  3. Schuessler RB, Kay MW, Melby SJ, Branham BH, Boineau JP, Damiano RJ (2006) Spatial and temporal stability of the dominant frequency of activation in human atrial fibrillation. J Electrocardiol 39:S7–S12

    Article  Google Scholar 

  4. Grace A, Willems S, Meyer C, Verma A, Heck P, Zhu M, Shi X, Chou D, Dang L, Scharf C, Scharf G, Beatty G (2019) High-resolution noncontact charge-density mapping of endocardial activation. JCI insight 4(6)

  5. Shi R, Parikh P, Chen Z, Angel N, Norman M, Hussain W, Butcher C, Haldar S, Jones DG, Riad O, Markides V, Wong T (2020) Validation of dipole density mapping during atrial fibrillation and sinus rhythm in human left atriumJACC. Clinical electrophysiology 6(2):171–181

    Article  Google Scholar 

  6. Gagyi RB, Noten AME, Lesina K, Mahmoodi BK, Yap S-C, Hoogendijk MG, Wijchers S, Bhagwandien RE, Szili-Torok T (2021) New possibilities in the treatment of brief episodes of highly symptomatic atrial Tachycardia: the usefulness of single-position single-beat charge density mapping. Circ Arrhythmia and electrophysiol 14(11):e010340

    Article  Google Scholar 

  7. Pope MTB, Kuklik P, Gala ABE, Leo M, Mahmoudi M, Paisey J, Betts TR (2021) Spatial and temporal variability of rotational, focal, and irregular activity: practical implications for mapping of atrial fibrillation. J Cardiovasc Electrophysiol 32:2393–2403

    Article  Google Scholar 

  8. Pope MTB, Kuklik P, Gala ABE, Leo M, Mahmoudi M, Paisey J, Betts TR (2022) Impact of adenosine on wavefront propagation in persistent atrial fibrillation: insights from global noncontact charge density mapping of the left atrium. J Am Heart Assoc: Cardiovasc Cerebrovasc Dis 11

  9. Shi R, Chen Z, Butcher C, Zaman JA, Boyalla V, Wang YK, Riad O, Sathishkumar A, Norman M, Haldar S, Jones DG, Hussain W, Markides V, Wong T (2020) Diverse activation patterns during persistent atrial fibrillation by noncontact charge-density mapping of human atrium. J arrhythmia 36(4):692–702

    Article  Google Scholar 

  10. Mickelsen SR, Angel N, Shah P, Shi X, Chou D (2021) B-PO05-085 Regional conduction velocity measurements: comparing contact and non-contact activation techniques. Heart Rhythm 18:S406

    Article  Google Scholar 

  11. Pytkowski M, Jankowska A, Maciag A, Kowalik I, Sterlinski M, Szwed H, Saumarez RC (2008) Paroxysmal atrial fibrillation is associated with increased intra-atrial conduction delay. Europace 10:1415–1420

    Article  Google Scholar 

  12. Zheng Y, Xia Y, Carlson J, Kongstad O, Yuan S (2017) Atrial average conduction velocity in patients with and without paroxysmal atrial fibrillation. Clin Physiol Funct Imaging 37:596–601

    Article  Google Scholar 

  13. Grossi S, Grassi F, Galleani L, Bianchi F, SibonaMasi A, Conte MR (2016) Atrial conduction velocity correlates with frequency content of bipolar signal. Pacing clin electrophysiol : PACE 39(8):814–821

    Article  Google Scholar 

  14. Grace A, Verma A, Willems S (2017) Dipole density mapping of atrial fibrillation. Eur heart j 38(1):5–9

    Article  Google Scholar 

  15. Willems S, Verma A, Betts TR, Murray S, Neuzil P, Ince H, Steven D, Sultan A, Heck PM, Hall MC, Tondo C, Pison L, Wong T, Boersma LV, Meyer C, Grace A (2019) Targeting nonpulmonary vein sources in persistent atrial fibrillation identified by noncontact charge density mapping: UNCOVER AF Trial. Circulation. Arrhythmia electrophysiol 12(7):e007233

    Article  Google Scholar 

  16. Bayly PV, KenKnight BH, Rogers JM, Hillsley RE, Ideker RE, Smith WM (1998) Estimation of conduction velocity vector fields from epicardial mapping data. IEEE trans bio-med eng 45(5):563–571

    Article  CAS  Google Scholar 

  17. Barnette AR, Bayly PV, Zhang S, Walcott GP, Ideker RE, Smith WM (2000) Estimation of 3-D conduction velocity vector fields from cardiac mapping data. IEEE Trans Biomed Eng 47(8):1027–1035

    Article  CAS  Google Scholar 

  18. Good WW, Gillette KK, Zenger B, Bergquist JA, Rupp LC, Tate J, Anderson D, Gsell MAF, Plank G, MacLeod RS (2021) Estimation and validation of cardiac conduction velocity and wavefront reconstruction using epicardial and volumetric data. IEEE Trans Biomed Eng 68(11):3290–3300

    Article  Google Scholar 

  19. Wong GR, Nalliah CJ, Lee G, Voskoboinik A, Prabhu S, Parameswaran R, Sugumar H, Anderson RD, McLellan A, Ling L-H, Morton JB, Sanders P, Kistler PM, Kalman JM (2019) Dynamic atrial substrate during high-density mapping of paroxysmal and persistent AF. JACC: Clin Electrophysiol 5:1265–1277

    Google Scholar 

  20. Honarbakhsh S, Schilling RJ, Orini M, Providencia R, Keating E, Finlay M, Sporton S, Chow A, Earley MJ, Lambiase PD, Hunter RJ (2019) Structural remodeling and conduction velocity dynamics in the human left atrium: relationship with reentrant mechanisms sustaining atrial fibrillation. Heart Rhythm 16:18–25

    Article  Google Scholar 

  21. Konings KTS, Kirchhof CJHJ, Smeets JRLM, Wellens HJJ, Penn OC, Allessie MA (2000) High-density mapping of electrically induced atrial fibrillation in humans. Springer, Netherlands, pp 549–567

    Google Scholar 

  22. Ng J, Kadish AH, Goldberger JJ (2007) Technical considerations for dominant frequency analysis. J cardiovasc electrophysiol 18(7):757–764

    Article  Google Scholar 

  23. Li X, Chu GS, Almeida TP, Vanheusden FJ, Salinet J, Dastagir N, Mistry AR, Vali Z, Sidhu B, Stafford PJ, Schlindwein FS, Ng GA (2021) Automatic extraction of recurrent patterns of high dominant frequency mapping during human persistent atrial fibrillation. Front physiol 12:649486

    Article  Google Scholar 

  24. Everett TH, Kok LC, Vaughn RH, Moorman JR, Haines DE (2001) Frequency domain algorithm for quantifying atrial fibrillation organization to increase defibrillation efficacy. IEEE trans bio-med eng 48(9):969–978

    Article  Google Scholar 

  25. Everett TH, Moorman JR, Kok LC, Akar JG, Haines DE (2001) Assessment of global atrial fibrillation organization to optimize timing of atrial defibrillation. Circulation 103(23):2857–2861

    Article  Google Scholar 

  26. Kogawa R, Okumura Y, Watanabe I, Kofune M, Nagashima K, Mano H, Sonoda K, Sasaki N, Ohkubo K, Nakai T, Hirayama A (2015) Spatial and temporal variability of the complex fractionated atrial electrogram activity and dominant frequency in human atrial fibrillation. J Arrhythmia 31:101–107

    Article  Google Scholar 

  27. Li X, Chu GS, de Almeida TP, Salinet J, Mistry AR, Vali Z, Stafford PJ, Schlindwein FS, Ng GA (2018) Dominant frequency variability mapping for identifying stable drivers during persistent atrial fibrillation using noncontact mapping, Comput Cardiol

  28. Zheng Y, Xia Y, Carlson J, Kongstad O, Yuan S (2017) Atrial average conduction velocity in patients with and without paroxysmal atrial fibrillation. Clin physiol funct imaging 37(6):596–601

    Article  Google Scholar 

  29. Heida A, van Schie MS, van der Does WFB, Taverne YJHJ, Bogers AJJC, de Groot NMS (2021) Reduction of conduction velocity in patients with atrial fibrillation. J Clin Med 10:2614

    Article  CAS  Google Scholar 

  30. Kurata N, Masuda M, Kanda T, Asai M, Iida O, Okamoto S, Ishihara T, Nanto K, Tsujimura T, Matsuda Y, Hata Y, Mano T (2020) Slow whole left atrial conduction velocity after pulmonary vein isolation predicts atrial fibrillation recurrence. J Cardiovasc Electrophysiol 31:1942–1949

    Article  Google Scholar 

  31. Frontera A, Pagani S, Limite LR, Peirone A, Fioravanti F, Enache B, Cuellar Silva J, Vlachos K, Meyer C, Montesano G, Manzoni A, Dedé L, Quarteroni A, Lațcu DG, Rossi P, Della Bella P (2022) Slow conduction corridors and pivot sites characterize the electrical remodeling in atrial fibrillation. JACC Clin electrophysiol 8(5):561–577

    Article  Google Scholar 

  32. Verma A, Lakkireddy D, Wulffhart Z, Pillarisetti J, Farina D, Beardsall M, Whaley B, Giewercer D, Tsang B, Khaykin Y (2011) Relationship between complex fractionated electrograms (CFE) and dominant frequency (DF) sites and prospective assessment of adding DF-guided ablation to pulmonary vein isolation in persistent atrial fibrillation (AF). J Cardiovasc Electrophysiol 22(12):1309–1316

    Article  Google Scholar 

  33. Habel N, Znojkiewicz P, Thompson N, Müller JG, Mason B, Calame J, Calame S, Sharma S, Mirchandani G, Janks D, Bates J, Noori A, Karnbach A, Lustgarten DL, Sobel BE, Spector P (2010) The temporal variability of dominant frequency and complex fractionated atrial electrograms constrains the validity of sequential mapping in human atrial fibrillation. Heart Rhythm 7:586–593

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. HerzGefässStiftung, Klinik im Park, Zurich, Switzerland

    Lam Dang

  2. Acutus Medical, Inc, CA, 92008, Carlsbad, USA

    Nathan Angel & Min Zhu

  3. Applied Signal Processing Group, Swiss Federal Institute of Technology, Lausanne, Switzerland

    Jean-Marc Vesin

  4. Rhythmologie-Zürich AG, Zurich, Switzerland

    Christoph Scharf

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  1. Lam Dang
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Correspondence to Lam Dang.

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Drs Dang and Scharf are co-founder and shareholders of Acutus Meical Inc.

Drs Angel and Zhu were previously employees and shareholders of Acutus Medical Inc.

Dr Vesin has no disclosure.

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Dang, L., Angel, N., Zhu, M. et al. Correlation between conduction velocity and frequency analysis in patients with atrial fibrillation using high-density charge mapping. Med Biol Eng Comput 60, 3081–3090 (2022). https://doi.org/10.1007/s11517-022-02659-0

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  • DOI: https://doi.org/10.1007/s11517-022-02659-0

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