Literature DB >> 17959699

Quantifying fractionation and rate in human atrial fibrillation using monophasic action potentials: implications for substrate mapping.

Sanjiv M Narayan1, Michael R Franz.   

Abstract

AIMS: To use monophasic action potentials (MAPs) to better assess the rate and the presence of fractionated electrograms during the mapping of atrial fibrillation (AF). Substrate mapping is increasingly central to AF ablation. However, traditional bipolar signals poorly represent waveform shape, making it unclear whether fractionation reflects local waveform variations, true electrogram fragmentation, or noise, and raising issues on whether their spectral dominant frequencies (DFs) accurately estimate AF rate. METHODS AND
RESULTS: In 28 patients with paroxysmal or persistent AF (left atrial diameters 44 +/- 8 mm), we studied 49 epochs of right atrial MAPs during AF. We compared fractionation, spectral and time-domain AF rate estimates using MAPs and bipolar electrograms obtained by filtering the MAPs. Fractionation was overestimated in bipolar rather than MAP electrograms (P = 0.005) and often reflected artefacts on the MAPs. Conversely, local waveform variability in the MAPs, including alternans or fractionation, was often uniform in the bipolar electrograms. The measured AF cycle length (CL) was accurately represented by the DF of the MAPs (r = 0.73, P < 0.001) but, due to double counting, not by the DF of bipolar signals (r = 0.29, P = 0.07). Spectral CL estimates were therefore accurate (< or = 20 ms from measured CL) for 77% of MAPs but for 45% of bipolar signals only. A novel autocorrelation method better estimated CL in MAPs (r = 0.92; P < 0.001) and bipoles (r = 0.82; P < 0.001), with 89 and 77% accuracy, respectively (P < 0.01).
CONCLUSION: Atrial fibrillation organization and rate are better represented by MAPs, which portray fibrillatory waveform shape, than by bipolar recordings. This approach may more reliably portray electrogram variability, fragmentation, and rate for the mapping of AF substrates.

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Year:  2007        PMID: 17959699     DOI: 10.1093/europace/eum212

Source DB:  PubMed          Journal:  Europace        ISSN: 1099-5129            Impact factor:   5.214


  14 in total

1.  Clinical mapping approach to diagnose electrical rotors and focal impulse sources for human atrial fibrillation.

Authors:  Sanjiv M Narayan; David E Krummen; Wouter-Jan Rappel
Journal:  J Cardiovasc Electrophysiol       Date:  2012-04-26

2.  Functional nature of electrogram fractionation demonstrated by left atrial high-density mapping.

Authors:  Amir S Jadidi; Edward Duncan; Shinsuke Miyazaki; Nicolas Lellouche; Ashok J Shah; Andrei Forclaz; Isabelle Nault; Matthew Wright; Lena Rivard; Xingpeng Liu; Daniel Scherr; Stephen B Wilton; Frédéric Sacher; Nicolas Derval; Sebastien Knecht; Steven J Kim; Mélèze Hocini; Sanjiv Narayan; Michel Haïssaguerre; Pierre Jaïs
Journal:  Circ Arrhythm Electrophysiol       Date:  2012-01-03

3.  Acute ivabradine treatment reduces heart rate without increasing atrial fibrillation inducibility irrespective of underlying vagal activity in dogs.

Authors:  Kazunori Uemura; Masashi Inagaki; Can Zheng; Toru Kawada; Meihua Li; Masafumi Fukumitsu; Masaru Sugimachi
Journal:  Heart Vessels       Date:  2016-11-14       Impact factor: 2.037

Review 4.  Thinking outside the Box: Rotor Modulation in the Treatment of Atrial Fibrillation.

Authors:  Ruchir Sehra; Sanjiv M Narayan; John Hummel
Journal:  J Atr Fibrillation       Date:  2013-06-30

5.  Comparison of spectral estimators for characterizing fractionated atrial electrograms.

Authors:  Edward J Ciaccio; Angelo B Biviano; Hasan Garan
Journal:  Biomed Eng Online       Date:  2013-07-16       Impact factor: 2.819

6.  Classifying fractionated electrograms in human atrial fibrillation using monophasic action potentials and activation mapping: evidence for localized drivers, rate acceleration, and nonlocal signal etiologies.

Authors:  Sanjiv M Narayan; Matthew Wright; Nicolas Derval; Amir Jadidi; Andrei Forclaz; Isabelle Nault; Shinsuke Miyazaki; Frédéric Sacher; Pierre Bordachar; Jacques Clémenty; Pierre Jaïs; Michel Haïssaguerre; Mélèze Hocini
Journal:  Heart Rhythm       Date:  2010-10-16       Impact factor: 6.343

7.  Pathogenesis of AF: impact on intracardiac signals.

Authors:  Ashok J Shah; Rémi Dubois; Shinsuke Miyazaki; Amir S Jadidi; Daniel Scherr; Stephen B Wilton; Laurent Roten; Patrizio Pascale; Michala Pedersen; Nicolas Derval; Sebastien Knecht; Frederic Sacher; Pierre Jais; Sanjiv Narayan; Meleze Hocini; Michel Haïssaguerre
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

8.  Panoramic electrophysiological mapping but not electrogram morphology identifies stable sources for human atrial fibrillation: stable atrial fibrillation rotors and focal sources relate poorly to fractionated electrograms.

Authors:  Sanjiv M Narayan; Kalyanam Shivkumar; David E Krummen; John M Miller; Wouter-Jan Rappel
Journal:  Circ Arrhythm Electrophysiol       Date:  2013-02-07

9.  Targeting Stable Rotors to Treat Atrial Fibrillation.

Authors:  Sanjiv M Narayan; David E Krummen
Journal:  Arrhythm Electrophysiol Rev       Date:  2012-09

Review 10.  Temporal and Spatial Indices of AF Regularization Predict Intraprocedural AF Termination and Outcome.

Authors:  Tina Baykaner; David E Krummen; Sanjiv M Narayan
Journal:  J Atr Fibrillation       Date:  2012-04-14
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