Automated detection and characterization of complex fractionated atrial electrograms in human left atrium during atrial fibrillation

Scherr, Douglas S.; Dalal, Darshan; Cheema, Aamir; Cheng, Alan; Henrikson, Charles A.; Spragg, David D.; Marine, Joseph E.; Berger, Ronald D.; Calkins, Hugh; Dong, Jun

doi:10.1016/j.hrthm.2007.04.021

Cited by 114 publications

(128 citation statements)

References 18 publications

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“…The SAVP model leads to more easily induced and more frequently sustained AF episodes than the RVP model. The observation that SAVP dogs had a greater degree of LA systolic dysfunction and longer episodes of AF is consistent with prior observations that a decrease in LA fractional area shortening is correlated with AF duration in dogs (29) and suggests that structural changes associated with decreases in LA function are an important determinant of the propensity to AF. In addition, whereas none of the RVP dogs developed AF induced by a single premature extrastimulus, half of the SAVP dogs did.…”

Section: Chronic Consequences Of Savp Versus Rvpsupporting

confidence: 90%

“…Second, the only true conduction velocity calculated (taking into account the interelectrode distance) was at the posterior wall of the LA. In humans, this area is of interest for its AF vulnerability, because of the muscular fiber disarray responsible for complex fractionated atrial electrograms, which have been reported as ablative targets for the treatment of AF (29). Mapping the LA with the clock-face electrode (only 16 unipolar electrodes) is also a limitation.…”

Section: Limitationsmentioning

confidence: 99%

See 1 more Smart Citation

Experimental studies of atrial fibrillation: a comparison of two pacing models

Laurent¹,

Moe²,

Hu³

et al. 2008

American Journal of Physiology-Heart and Circulatory Physiology

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is a well-established animal model of atrial fibrillation (AF). However, this model is limited by a high mortality rate and severe heart failure. The purpose of our study was to assess a new canine model of inducible AF. We performed acute, short-term, simultaneous atrioventricular pacing (SAVP) and RVP (in random order) in 14 dogs for 30 s. SAVP produced more echocardiographic pulmonary venous flow reversal, a greater increase in mean pulmonary capillary wedge pressure, and a significantly greater decrease in left atrial emptying function (Ϫ84.4 Ϯ 38.6% vs. Ϫ23.7 Ϯ 27.1%, P Ͻ 0.05) than RVP. Thirty dogs were randomized to three, longer-term, study groups: eight dogs in the control group (no pacing), eight dogs in the RVP group (2 wk at 240 beats/min followed by 3 wk at 220 beats/min), and fourteen dogs in the SAVP group (2 wk at 220 beats/min). SAVP induced less left ventricular dysfunction but more left atrial dysfunction than RVP. SAVP dogs had similar atrial effective refractory periods as RVP dogs but more heterogeneity in conduction and more AF inducibility (83% vs. 40%, P Ͻ 0.05) and maintenance (median 1,660 vs. 710 s, P Ͻ 0.05) than RVP dogs. SAVP induced more collagen turnover and was associated with a significantly greater increase in type III collagen in the atria compared with RVP dogs (6.9 Ϯ 1.5 vs. 4.8 Ϯ 1.6, respectively, P Ͻ 0.05 vs. 1.1 Ϯ 0.7 in unpaced control dogs). In conclusion, the SAVP model induced profound mechanical and substrate atrial remodeling and reproducible sustained AF. This new model is clinically relevant and may be useful for testing AF interventions. experimental atrial arrhythmia; extracellular matrix; remodeling ATRIAL FIBRILLATION (AF) is the most common sustained cardiac arrhythmia and frequently causes cardiovascular morbidity and mortality. Although AF can occur in patients with normal hearts (lone AF), the majority of patients with AF have coexisting structural heart disease, most commonly hypertension or heart failure (1). To better understand the relationship between the atrial substrate and AF vulnerability and to evaluate therapies for AF, multiple animal models of AF have been developed. They include sterile pericarditis, acute atrial ischemia, atrial volume overload, mitral regurgitation, pacemakerinduced atrial tachycardia, and ventricular pacing-induced heart failure (25).One of the most commonly used models employs rapid atrial pacing (RAP) at 400 beats/min with control of the ventricular response (atrioventricular node ablation) (24). This model helps to understand the mechanisms underlying the tendency of paroxysmal AF to become persistent but does not relate closely to the most frequent clinical conditions associated with AF, in which the left atrium (LA) dilates and is fibrosed, exhibiting conduction slowing (14, 21). The other commonly used model is rapid ventricular pacing (RVP) to induce heart failure (240 -280 beats/min for 3-8 wk), sometimes combined with RAP (RVP at 240 beats/min for 2 wk combined with additional RAP at 400 beats/min during the sec...

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Section: Chronic Consequences Of Savp Versus Rvpsupporting

confidence: 90%

Section: Limitationsmentioning

confidence: 99%

Experimental studies of atrial fibrillation: a comparison of two pacing models

Laurent¹,

Moe²,

Hu³

et al. 2008

American Journal of Physiology-Heart and Circulatory Physiology

View full text Add to dashboard Cite

show abstract

“…66 Automatic computer algorithms have been developed to remove some of the subjectivity in distinguishing important areas of fractionation, but in one study using such a method, 86 % of LA sites were classified as having CFAEs. 75 Despite the initial excitement surrounding the relation of CFAEs to AF, CFAEs are non-specific electrophysiological manifestations which are unlikely to be drivers of AF, and coincidental ablation of reentrant circuits and AF drivers likely explains the occasional success when CFAEs are targeted with ablation. CFAE ablation has minimal effect on patient outcomes, and can result in increased procedure times and an increased potential for complications.…”

Section: Complex Fractionated Electrograms Are Passive Bystanders In Afmentioning

confidence: 99%

Mechanisms of Atrial Fibrillation – Reentry, Rotors and Reality

Waks

Josephson²

2014

Arrhythmia &Amp; Electrophysiology Review

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Atrial fibrillation (AF), the most common sustained arrhythmia, is a leading cause of stroke, and is associated with significant morbidity and mortality worldwide. Despite its frequency, clinical importance, and advances in technology and our knowledge of the molecular, ionic and physiological fundamentals of cardiac electrophysiology, our limited understanding of the mechanisms that initiate and sustain AF has prevented us from being able to truly cure this arrhythmia with antiarrhythmic drugs and/or ablation. This contrasts with other arrhythmias, such as AV nodal tachycardia or circus movement tachycardia using an accessory pathway, which have well-defined mechanisms and circuits that can be safely targeted with high rates of cure. The observations that AF may have different mechanisms in different patients, and that paroxysmal, persistent and permanent forms of AF may differ in how they are initiated and sustained, only serves to reinforce our lack of understanding of this ubiquitous arrhythmia. Historical Mechanisms of Atrial Fibrillation and the Multiple Wavelet HypothesisInterest and understanding of the mechanism of AF began to take form in the early 1900s. Given the chaotic and irregular nature of AF on the surface electrocardiogram, rapid firing of automatic atrial foci was considered a potential mechanism. However, after the seminal work of Mayer 1 , Mines 2 and Garrey 3 in laying the foundation for describing and understanding reentrant arrhythmias, atrial reentrant circuits emerged as the likely drivers of AF.4-7 Although these theories were conceptually sound, it was impossible to prove a specific mechanism with the technology of the time. Moe et al. demonstrated that it was probabilistically unlikely that a large number of simultaneous wavefronts would all die out simultaneously, and AF would therefore perpetuate. However, if the number of simultaneous wavelets were small and/or below a critical value (between 15 and 30 in Moe's computer model), 9 at some point all reentrant wavefronts would be simultaneously extinguished, and AF would therefore terminate. 8,9 Allessie et al. provided experimental evidence supporting this mechanism in a canine heart model of AF where four to six simultaneous reentrant wavelets were needed to sustain arrhythmia. 10 Further evidence supporting multiple wavelets in AF was demonstrated in a separate model, which evaluated the effect of various antiarrhythmic drugs on canine myocardium. This model demonstrated that termination of AF was associated with a reduction AbstractAtrial fibrillation (AF) is the most common sustained arrhythmia encountered in clinical practice, yet our understanding of the mechanisms that initiate and sustain this arrhythmia remains quite poor. Over the last 50 years, various mechanisms of AF have been proposed, yet none has been consistently observed in both experimental studies and in humans. Recently, there has been increasing interest in understanding how spiral waves or rotors -which are specific, organised forms of functional reentry -su...

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“…Other works that showed new quantification measures of A-EGM during AF used morphological features of the atrial waves in contrast to previously proposed measures to describe A-EGMs. In a recent study Scherr et al (Scherr et al, 2007) showed the first use of an algorithm for automatic search of CFAEs and A-EGM complexity description in A-EGMs recorded during AF mapping procedures. Nademanee et al (Nademanee et al, 2004) sought to investigate the electrophysiological substrate and referred in their publication introduction to the work of Allessie's group.…”

Section: Introductionmentioning

confidence: 99%

“…However, currently used algorithms still have some settings that need to be set up manually, so that execution of the algorithms are not fully automatic and it needs to be tested under a range of conditions. New stable algorithms for automatic evaluation of fibrillation electrograms are thus not only of scientific interest but can also provide a proper basis for selecting the most appropriate AF treatment (Kottkamp & Hindricks, 2007;Scherr et al, 2007). In 2007 and 2008 we developed a background methodology and techniques to extract more A-EGM features that are based on several possible information dimensions (degree of freedom) of the A-EGM signal, for example entropy, DF and CFAEs based features, as well as time and frequency domain analysis features.…”

Section: Introductionmentioning

confidence: 99%