Angelo B. Biviano

Arrhythmias in pulmonary arterial hypertension.

Cardiac arrhythmias are important contributors to morbidity and mortality in patients with pulmonary arterial hypertension (PAH). Such patients manifest a substrate resulting from altered autonomics, repolarization abnormalities, and ischemia. Supraventricular arrhythmias such as atrial fibrillation and flutter are associated with worsened outcomes, and maintenance of sinus rhythm is a goal. Sudden death is a relatively common issue, though the contribution of malignant ventricular arrhythmias versus bradyarrhythmias differs from non-PAH patients. Congenital heart disease patients with PAH benefit from catheter ablation of medically refractory arrhythmias. Clinical studies of defibrillator/pacemaker therapy for primary prevention against sudden death in PAH patients are lacking.

Differences in Repeating Patterns of Complex Fractionated Left Atrial Electrograms in Longstanding Persistent Atrial Fibrillation as Compared With Paroxysmal Atrial Fibrillation

Background— Complex fractionated atrial electrograms (CFAE) are morphologically more uniform in persistent longstanding as compared with paroxysmal atrial fibrillation (AF). It was hypothesized that this may result from a greater degree of repetitiveness in CFAE patterns at disparate left atrial (LA) sites in longstanding AF. Methods and Results— CFAEs were obtained from recording sites outside the 4 pulmonary vein (PV) ostia and at a posterior and an anterior LA site during paroxysmal and longstanding persistent AF (10 patients each, 120 sequences total). To quantify repetitiveness in CFAE, the dominant frequency was measured from ensemble spectra using 8.4-second sequences, and repetitiveness was calculated by 2 novel techniques: linear prediction and Fourier reconstruction methods. Lower prediction and reconstruction errors were considered indicative of increasing repetitiveness and decreasing randomness. In patients with paroxysmal AF, CFAE pattern repetitiveness was significantly lower (randomness higher) at antral sites outside PV ostia as compared with LA free wall sites (P<0.001). In longstanding AF, repetitiveness increased outside the PV ostia, especially outside the left superior PV ostium, and diminished at the LA free wall sites. The result was that in persistent AF, there were no significant site-specific differences in CFAE repetitiveness at the selected LA locations used in this study. Average dominant frequency magnitude was 5.32±0.29 Hz in paroxysmal AF and higher in longstanding AF, at 6.27±0.13 Hz (P<0.001), with the frequency of local activation approaching a common upper bound for all sites. Conclusions— In paroxysmal AF, CFAE repetitiveness is low and randomness high outside the PVs, particularly the left superior PV. As evolution to persistent longstanding AF occurs, CFAE repetitiveness becomes more uniformly distributed at disparate sites, possibly signifying an increasing number of drivers from remote PVs.

Why is intracardiac echocardiography helpful? Benefits, costs, and how to learn

Current interventional procedures in structural heart disease and cardiac arrhythmias require peri-interventional echocardiographic monitoring and guidance to become as safe, expedient, and well-tolerated for patients as possible. Intracardiac echocardiography (ICE) complements and has in part replaced transoesophageal echocardiography (TEE), including real-time three-dimensional (RT-3D) imaging. The latter is still widely accepted as a method to prepare for and to guide interventional treatments. In contrast to TEE, ICE represents a purely intraprocedural guiding and imaging tool unsuitable for diagnostic purposes. Patients tolerate ICE much better, and the method does not require general anaesthesia. Accurate imaging of the particular pathology, its anatomic features, and spatial relation to the surrounding structures is critical for catheter and wire positioning, device deployment, evaluation of the result, and for ruling out complications. This review describes the peri-interventional role of ICE, outlines current limitations, and points out future implications. Two-dimensional ICE has become a suitable guiding tool for a variety of percutaneous treatments in patients who are conscious or under monitored anaesthesia care, whereas RT-3DICE is still undergoing clinical testing. Continuous TEE monitoring under general anaesthesia remains a widely accepted alternative.

Different characteristics of complex fractionated atrial electrograms in acute paroxysmal versus long-standing persistent atrial fibrillation

BACKGROUND Complex fractionated atrial electrograms (CFAEs) may represent a phenomenon associated with sources of atrial fibrillation (AF) and are being used increasingly as targets of catheter ablation. However, current methods have limited efficacy for characterizing CFAEs important to substrate arrhythmogenicity and do not measure electrogram morphology. OBJECTIVE The purpose of this study was to develop a methodology for quantifying the degree of morphologic heterogeneity in CFAE deflections, and to determine whether there are differences in this measurement between paroxysmal and persistent AF patients. METHODS Two successive bipolar CFAEs of length 8.4 seconds each were acquired during AF from two sites each at the ostia of the four pulmonary veins (PVs) and from the anterior and posterior left atrial free wall in patients with paroxysmal AF (N = 10) and long-standing persistent AF (N = 10). Extrinsic and intrinsic features of electrogram shape were used to characterize fractionation in CFAE sequences. The extrinsic parameters were the amplitude, upslope, downslope, and width of each deflection. The intrinsic parameter was the voltage profile as characterized by the sum of absolute values. These measurements were compared to the mean interval between CFAE deflections, a standard fractionation indicator. RESULTS The variability of intrinsic/extrinsic morphologic parameters was higher in paroxysmal than persistent AF at the left superior PV (P < or =.003), the posterior left atrial free wall, anterior left atrial free wall, left inferior PV, and right superior PV (P <.05 for most parameters), and the right inferior PV (not significant). Mean CFAE deflection intervals were longer at all locations in paroxysmal AF but were significant only at the left superior PV and posterior left atrial free wall (P <.05). Quantitative morphologic parameters were not well correlated with dominant frequency (r(2) <0.32); thus, our new measures are robust to changes in activation rate. CONCLUSION A novel method for quantifying CFAEs, independent of activation rate, has been developed. The method demonstrates greater significance in the difference between CFAE morphology in paroxysmal and long-standing AF compared with mean interval between CFAE deflections. The differences identified suggest that CFAE morphology may evolve as AF persists.

Identification of recurring patterns in fractionated atrial electrograms using new transform coefficients.

BackgroundIdentification of recurrent patterns in complex fractionated atrial electrograms (CFAE) has been used to differentiate paroxysmal from persistent atrial fibrillation (AF). Detection of the atrial CFAE patterns might therefore be assistive in guiding radiofrequency catheter ablation to drivers of the arrhythmia. In this study a technique for robust detection and classification of recurrent CFAE patterns is described.MethodCFAE were obtained from the four pulmonary vein ostia, and from the anterior and posterior left atrium, in 10 patients with paroxysmal AF and 10 patients with longstanding persistent AF (216 recordings in total). Sequences 8.4 s in length were analyzed (8,192 sample points, 977 Hz sampling). Among the 216 sequences, two recurrent patterns A and B were substituted for 4 and 5 of the sequences, respectively. To this data, random interference, and random interference + noise were separately added. Basis vectors were constructed using a new transform that is derived from ensemble averaging. Patterns A and B were then detected and classified using a threshold level of Euclidean distance between spectral signatures as constructed with transform coefficients.ResultsIn the presence of interference, sensitivity to detect and distinguish two patterns A and B was 96.2%, while specificity to exclude nonpatterns was 98.0%. In the presence of interference + noise, sensitivity was 89.1% while specificity was 97.0%.ConclusionsTransform coefficients computed from ensemble averages can be used to succinctly quantify synchronized patterns present in AF data. The technique is useful to automatically detect recurrent patterns in CFAE that are embedded in interference without user bias. This quantitation can be implemented in real-time to map the AF substrate prior to and during catheter ablation.

Improved frequency resolution for characterization of complex fractionated atrial electrograms

BackgroundThe dominant frequency of the Fourier power spectrum is useful to analyze complex fractionated atrial electrograms (CFAE), but spectral resolution is limited and uniform from DC to the Nyquist frequency. Herein the spectral resolution of a recently described and relatively new spectral estimation technique is compared to the Fourier radix-2 implementation.MethodsIn 10 paroxysmal and 10 persistent atrial fibrillation patients, 216 CFAE were acquired from the pulmonary vein ostia and left atrial free wall (977 Hz sampling rate, 8192 sample points, 8.4 s duration). With these parameter values, in the physiologic range of 3–10 Hz, two frequency components can theoretically be resolved at 0.24 Hz using Fourier analysis and at 0.10 Hz on average using the new technique. For testing, two closely-spaced periodic components were synthesized from two different CFAE recordings, and combined with two other CFAE recordings magnified 2×, that served as interference signals. The ability to resolve synthesized frequency components in the range 3–4 Hz, 4–5 Hz, …, 9–10 Hz was determined for 15 trials each (105 total).ResultsWith the added interference, frequency resolution averaged 0.29 ± 0.22 Hz for Fourier versus 0.16 ± 0.10 Hz for the new method (p < 0.001). The misalignment error of spectral peaks versus actual values was ±0.023 Hz for Fourier and ±0.009 Hz for the new method (p < 0.001). One or both synthesized peaks were lost in the noise floor 13/105 times using Fourier versus 4/105 times using the new method.ConclusionsWithin the physiologically relevant frequency range for characterization of CFAE, the new method has approximately twice the spectral resolution of Fourier analysis, there is less error in estimating frequencies, and peaks appear more readily above the noise floor. Theoretically, when interference is not present, to resolve frequency components separated by 0.10 Hz using Fourier analysis would require an 18.2 s sequence duration, versus 8.4 s with the new method.

Computational method for high resolution spectral analysis of fractionated atrial electrograms

BACKGROUND The discrete Fourier transform (DFT) is often used as a spectral estimator for analysis of complex fractionated atrial electrograms (CFAE) acquired during atrial fibrillation (AF). However, time resolution can be unsatisfactory, as the frequency resolution is proportional to rate/time interval. In this study we compared the DFT to a new spectral estimator with improved time-frequency resolution. METHOD Recently, a novel spectral estimator (NSE) based upon signal averaging was derived and implemented computationally. The NSE is similar to the DFT in that both estimators model the autocorrelation function to form the power spectrum. However, as derived in this study, NSE frequency resolution is proportional to rate/period(2) and thus unlike the DFT, is not directly dependent on the window length. We hypothesized that the NSE would provide improved time resolution while maintaining satisfactory frequency resolution for computation of CFAE spectral parameters. Window lengths of 8s, 4s, 2s, 1s, and 0.5s were used for analysis. Two criteria gauged estimator performance. Firstly, a periodic electrogram pattern with phase jitter was embedded in interference. The error in detecting the frequency of the periodic pattern was determined. Secondly, significant differences in spectral parameters for paroxysmal versus persistent AF data, which have known dissimilarities, were determined using the DFT versus NSE methods. The parameters measured were the dominant amplitude, dominant frequency, and mean spectral profile. RESULTS At all time resolutions, the error in detecting the frequency of the repeating electrogram pattern was less for NSE than for DFT (p<0.001). The DFT was accurate to 2s time resolution/0.5 Hz frequency resolution, while the NSE was accurate to 0.5s time resolution/0.05 Hz frequency resolution. At all time resolutions, significant differences in the dominant amplitude spectral parameter for paroxysmal versus persistent CFAE were greater using NSE than DFT (p<0.0001). For three of five time resolutions, the NSE had greater significant differences than DFT for discriminating the dominant frequency and mean spectral profile parameters between AF types. CONCLUSIONS The results suggest that the NSE has improved performance versus DFT for measurement of CFAE spectral properties.

Applications of computed tomography and magnetic resonance imaging in percutaneous ablation therapy for atrial fibrillation

Percutaneous catheter ablation is an established therapy for symptomatic drug-refractory atrial fibrillation (AF). Accurate delineation of relevant anatomy is critical but often challenging and limited in traditional technologies such as intra-procedural fluoroscopy. There has been an increased interest in non-invasive three-dimensional imaging technologies, especially computed tomography (CT) and magnetic resonance imaging (MRI), as useful tools for patients undergoing AF ablation. Here, we review applications of CT and MRI before, during, and after AF ablation and highlight areas for future research.

A new LMS algorithm for analysis of atrial fibrillation signals

BackgroundA biomedical signal can be defined by its extrinsic features (x-axis and y-axis shift and scale) and intrinsic features (shape after normalization of extrinsic features). In this study, an LMS algorithm utilizing the method of differential steepest descent is developed, and is tested by normalization of extrinsic features in complex fractionated atrial electrograms (CFAE).MethodEquations for normalization of x-axis and y-axis shift and scale are first derived. The algorithm is implemented for real-time analysis of CFAE acquired during atrial fibrillation (AF). Data was acquired at a 977 Hz sampling rate from 10 paroxysmal and 10 persistent AF patients undergoing clinical electrophysiologic study and catheter ablation therapy. Over 24 trials, normalization characteristics using the new algorithm with four weights were compared to the Widrow-Hoff LMS algorithm with four tapped delays. The time for convergence, and the mean squared error (MSE) after convergence, were compared. The new LMS algorithm was also applied to lead aVF of the electrocardiogram in one patient with longstanding persistent AF, to enhance the F wave and to monitor extrinsic changes in signal shape. The average waveform over a 25 s interval was used as a prototypical reference signal for matching with the aVF lead.ResultsBased on the derivation equations, the y-shift and y-scale adjustments of the new LMS algorithm were shown to be equivalent to the scalar form of the Widrow-Hoff LMS algorithm. For x-shift and x-scale adjustments, rather than implementing a long tapped delay as in Widrow-Hoff LMS, the new method uses only two weights. After convergence, the MSE for matching paroxysmal CFAE averaged 0.46 ± 0.49μV2/sample for the new LMS algorithm versus 0.72 ± 0.35μV2/sample for Widrow-Hoff LMS. The MSE for matching persistent CFAE averaged 0.55 ± 0.95μV2/sample for the new LMS algorithm versus 0.62 ± 0.55μV2/sample for Widrow-Hoff LMS. There were no significant differences in estimation error for paroxysmal versus persistent data. From all trials, the mean convergence time was approximately 1 second for both algorithms. The new LMS algorithm was useful to enhance the electrocardiogram F wave by subtraction of an adaptively weighted prototypical reference signal from the aVF lead. The extrinsic weighting over 25 s demonstrated that time-varying functions such as patient respiration could be identified and monitored.ConclusionsA new LMS algorithm was derived and used for normalization of the extrinsic features in CFAE and for electrocardiogram monitoring. The weighting at convergence provides an estimate of the degree of similarity between two signals in terms of x-axis and y-axis shift and scale. The algorithm is computationally efficient with low estimation error. Based on the results, proposed applications include monitoring of extrinsic and intrinsic features of repetitive patterns in CFAE, enhancement of the electrocardiogram F wave and monitoring of time-varying signal properties, and to quantitatively characterize mechanistic differences in paroxysmal versus persistent AF.

The dominant morphology of fractionated atrial electrograms has greater temporal stability in persistent as compared with paroxysmal atrial fibrillation

BACKGROUND Measurements of both the dominant frequency (DF) and the time series morphology of complex fractionated atrial electrograms (CFAE) are useful to distinguish persistent from paroxysmal atrial fibrillation (AF). In this study, an algorithm was devised to extract morphologic components according to frequency, and its usefulness for distinguishing CFAE was shown. METHOD CFAE of length 16s were obtained at two sites each from the four pulmonary vein ostia (PV), and from anterior and posterior left atrial free wall (FW), in nine paroxysmal and 10 longstanding persistent AF patients. The DF was computed for each of two 8s CFAE segments in each 16s recording. Each CFAE segment was then transformed into a set of basis vectors, which represent electrogram morphology at each frequency. The dominant morphology (DM) is defined as the ensemble average of sequential signal segments, with the segment length equal to the period at the DF. The DMs of the two 8s pairs were correlated. Normalized correlation coefficients were tabulated for all data, and separately for PV and FW. The means and coefficients of variation of the DM correlation coefficients were then plotted, and a linear discriminant function was used to classify persistent versus paroxysmal AF data. For comparison with DM results, CFE-mean and interval confidence level (ICL) were also calculated for persistent versus paroxysmal AF data. RESULTS Mean correlation of the DM, 1st 8s versus 2nd 8s data, was 0.62+0.22 for persistent versus 0.50+0.19 for paroxysmal CFAE for all recording sites (p<0.001). At single anatomical locations, correlation was greater in persistents than paroxysmals at all sites, but achieved significance only at the left superior (p<0.001) and right superior (p<0.05) PV. Spatial variation in correlation coefficient was greater in paroxysmal than persistent AF (not significant). Using the means of DF correlation coefficients, 17/19 patients were classified correctly. The CFE-mean parameter averaged 89.01±20.99 ms in persistents versus 93.96±33.81 ms in paroxysmals (p<0.05), while ICL averaged 94.54±18.52 deflections/8s for persistents versus 90.70±19.28 deflections/8s for paroxysmals (p<0.05). CONCLUSIONS In CFAE recordings, the DM parameter was found to have greater temporal morphologic variation in paroxysmal as compared with persistent AF data (p<0.001). In contrast, only moderate significance between paroxysmal versus persistent AF data was found when using the of CFE-mean and ICL parameters (p<0.05). The DM parameter may thus be useful as a new measure to discern both temporal and spatial variations in CFAE in paroxysmal versus persistent AF recordings.