Rupin Dalvi

Localized rotational activation in the left atrium during human atrial fibrillation: Relationship to complex fractionated atrial electrograms and low-voltage zones

BACKGROUND In humans, the existence of rotors or reentrant sources maintaining atrial fibrillation (AF) and the underlying electroanatomic substrate has not been well defined. OBJECTIVE Our aim was to determine the prevalence of localized rotational activation (RotA) in the left atrium (LA) during human AF and whether complex fractionated atrial electrograms (CFAEs) or low-voltage areas colocalize with RotA sites. METHODS We prospectively studied 32 patients (mean age 57 ± 8 years; 88% with persistent AF) undergoing AF catheter ablation. Bipolar electrograms were recorded for 2.5 seconds during AF using a roving 20-pole circular catheter in the LA. RotA was defined as sequential temporal activation of bipoles around the circular catheter. Bipolar electrogram fractionation index and bipolar voltage were used to define CFAEs and low-voltage areas, respectively. RESULTS In 21 (66%) patients, 47 RotA sites were identified. Few (9%) lasted 2.5 seconds (cycle length 183 ± 6 ms), while the majority (91%) were nonsustained (duration 610 ± 288 ms; cycle length 149 ± 11 ms). RotA was most common in the pulmonary vein antrum (71%) and posterior LA (25%). CFAEs were recorded from 18% ± 12% of LA area, and most (92% ± 7%) were not associated with RotA sites. However, 85% of RotA sites contained CFAEs. Very low voltage (<0.1 mV) areas comprised 12% ± 10% of LA area and were present in 23% of RotA sites. CONCLUSIONS In patients with predominantly persistent AF, localized RotA is commonly present but tends to be transient (<1 second). Although most CFAEs do not colocalize with RotA sites, the high prevalence of CFAEs and very low voltages within RotA sites may indicate slow conduction in diseased myocardium necessary for their maintenance.

Relationship of bipolar and unipolar electrogram voltage to scar transmurality and composition derived by magnetic resonance imaging in patients with nonischemic cardiomyopathy undergoing VT ablation

BACKGROUND Bipolar voltage mapping has a role in defining endocardial-based scar in postinfarct patients undergoing ventricular tachycardia catheter ablation. The utility of bipolar and unipolar voltages in characterizing scar has not been evaluated in patients with nonischemic cardiomyopathy. OBJECTIVE To relate left ventricular (LV) endocardial bipolar and unipolar voltages in these patients to scar transmurality (endocardial vs nonendocardial) and composition (homogeneous core vs heterogeneous gray). METHODS Ten consecutive cardiomyopathy patients undergoing endocardial LV tachycardia ablation were included (age 48 ± 14 years; left ventricular ejection fraction 43% ± 15%). Preablation late gadolinium-enhanced magnetic resonance imaging was used to quantify core and gray scar by using signal-intensity thresholding. Electroanatomic LV endocardial mapping provided bipolar and unipolar voltages. Electroanatomic maps and late gadolinium-enhanced magnetic resonance imaging were rigidly registered in order to relate voltage to scar (registration error 3.6 ± 2.9 mm). RESULTS Bipolar voltage was lower in endocardial core than in no scar (P <.001). Unipolar voltage was lower in endocardial core and nonendocardial core than in no scar (P <.001). Endocardial and nonendocardial gray scar had an effect similar to that of core in reducing bipolar and unipolar voltages (P <.001). The mass of healthy myocardium and endocardial core scar independently predicted bipolar and unipolar voltages using general estimating equation modeling. With receiver operating characteristic curve analysis, bipolar voltage >1.9 mV and unipolar voltage <6.7 mV had a high negative predictive value (91%) for detecting nonendocardial scar from either endocardial scar or no scar. CONCLUSIONS In patients with nonischemic cardiomyopathy, LV endocardial bipolar voltage is dependent on endocardial core and gray scar, while the unipolar voltage is influenced by core and gray scar across the LV wall as defined by late gadolinium-enhanced magnetic resonance imaging.

Quantifying abnormal QRS peaks using a novel time-domain peak detection algorithm: Application in patients with cardiomyopathy at risk of sudden death

Abnormal components in the QRS complex on the surface electrocardiogram have been used to predict sudden cardiac death in patients with heart disease. We propose a novel method to automate detection of abnormal peaks within the QRS complex. The approach involves identification of such peaks from consecutive unfiltered 10-beat QRS averages. A simulation using synthetic QRS peaks is conducted to assess the methods robustness to noise. The performance of the method is tested using high-resolution precordial lead electrocardiograms recorded from normal subjects and patients with cardiomyopathy. The 10-beat average performance is compared to a 100-beat average, as is commonly used in other state-of-the-art QRS component algorithms, and shown to be more sensitive in detecting abnormal QRS peaks. The clinical performance is tested amongst the cardiomyopathy patients and the method is shown to discriminate those at risk of sudden cardiac death with high sensitivity and specificity.

Graph search based detection of periodic activations in complex periodic signals: Application in atrial fibrillation electrograms

A novel method for automatic detection of peaks corresponding to the periodic activations in complex periodic signals is proposed. The approach involves dominant frequency-based periodicity detection combined with a graph search algorithm to identify periodic activations or peaks of interest. The performance of the proposed method is demonstrated in human atrial fibrillation electrograms with simulated periodic activations corrupted by complex aperiodic signal features. The proposed method is compared to two state-of-the-art peak detection algorithms and is shown to be more accurate in detecting periodic peaks.

Reviving the maximum likelihood method for detecting dominant periodicities from near-periodic signals

Many naturally occurring signals exhibit near, rather than perfect, periodicity, as a result of variation in cycle length (CL). The accuracy of methods to detect near-periodic signals is typically not evaluated against known CL variations which may compromise their performance. The maximum likelihood method (ML) proposed by Noll to evaluate periodicity involves block averaging which, with smoothing may make it robust to CL variations. In this paper, we revive the ML method and present it as a robust candidate for detecting near-periodicity. We propose to compare the performance of ML to conventional periodicity detection methods by testing against synthetic periodic data with varying CL and noise. Our results indicate that the ML method is significantly more accurate than conventional methods. We also demonstrate a substantial influence of periodic CL fluctuations on the accuracy of all methods.

Robust approach for evaluating periodicity in human atrial fibrillation bipolar electrograms

Atrial fibrillation (AF) is a common arrhythmia which can arise from periodic electrical sources. Bipolar electrograms (EGMs) recorded in the atrium are used to localize these sources. However, currently used signal processing approaches, including Fourier transform, do not accurately detect periodicity in bipolar EGMs owing to their complex morphology. This study introduces a novel variant of the periodicity transform (PT) which incorporates a correlation-based signal projection in order to improve detection of periodicities during AF. For validation, synthetic periodic signals added to bipolar atrial EGMs from patients without periodicity were used. The effect of noise and quasi-periodicity was further evaluated. When compared to PT, the proposed methods accuracy in detecting periodicity, at an average signal-to-noise ratio of 0 dB, improved by up to 36%.

Reduced T wave alternans in heart failure responders to cardiac resynchronization therapy: Evidence of electrical remodeling

Background T-wave alternans (TWA), a marker of electrical instability, can be modulated by cardiac resynchronization therapy (CRT). The relationship between TWA and heart failure response to CRT has not been clearly defined. Methods and results In 40-patients (age 65±11 years, left ventricular ejection-fraction [LVEF] 23±7%), TWA was evaluated prospectively at median of 2 months (baseline) and 8 months (follow-up) post-CRT implant. TWA-magnitude (Valt >0μV, k≥3), its duration (d), and burden (Valt ·d) were quantified in moving 128-beat segments during incremental atrial (AAI, native-TWA) and atrio-biventricular (DDD-CRT) pacing. The immediate and long-term effect of CRT on TWA was examined. Clinical response to CRT was defined as an increase in LVEF of ≥5%. Native-TWA was clinically significant (Valt ≥1.9μV, k≥3) in 68% of subjects at baseline. Compared to native-TWA at baseline, DDD-CRT pacing at baseline and follow-up reduced the number of positive TWA segments, peak-magnitude, longest-duration and peak-burden of TWA (44±5 to 33±5 to 28±4%, p = 0.02 and 0.002; 5.9±0.8 to 4.1±0.7 to 3.8±0.7μV, p = 0.01 and 0.01; 97±9 to 76±8 to 67±8sec, p = 0.004 and <0.001; and 334±65 to 178±58 to 146±54μV.sec, p = 0.01 and 0.004). In addition, the number of positive segments and longest-duration of native-TWA diminished during follow-up (44±5 to 35±6%, p = 0.044; and 97±9 to 81±9sec, p = 0.02). Clinical response to CRT was observed in 71% of patients; the reduction in DDD-CRT paced TWA both at baseline and follow-up was present only in responders (interaction p-values <0.1). Conclusion Long-term CRT reduces the prevalence and magnitude of TWA. This CRT induced beneficial electrical remodeling is a marker of clinical response after CRT.

Hierarchical analysis of electrograms to guide termination of persistent atrial fibrillation

The mechanism(s) perpetuating atrial fibrillation (AF) is poorly understood, and long-term success with catheter ablation remains suboptimal, especially in persistent AF. Ablation strategies beyond pulmonary vein (PV) isolation (PVI) have not been shown to provide incremental benefit in terms of maintaining sinus rhythm. However, there are data suggesting that acute termination of AF during ablation of extra-PV sources could lead to improved freedom from AF recurrence. As such, there is intense interest to better characterize and identify such potential “drivers” of AF, which may be amenable to ablation and improve outcomes. We recently described a hierarchical schema using stepwise analysis of bipolar electrogram (EGM) periodicity and unipolar QS morphology to identify focal sources (FS) that may be of significance in maintaining AF. In this report, we describe our experience in using this algorithm to identify and ablate extra-PV FS, which led to arrhythmia termination in a patient with persistent AF.

Automated Quantification of Low-Amplitude Abnormal QRS Peaks From High-Resolution ECG Recordings Predicts Arrhythmic Events in Patients With Cardiomyopathy

Background— Cardiomyopathy patients are at risk of sudden death, typically from scar-related abnormalities of electrical activation that promote ventricular tachyarrhythmias. Abnormal intra-QRS peaks may provide a measure of altered activation. We hypothesized that quantification of such QRS peaks (QRSp) in high-resolution ECGs would predict arrhythmic events in implantable cardioverter–defibrillator (ICD)–eligible cardiomyopathy patients. Methods and Results— Ninety-nine patients with ischemic or non-ischemic dilated cardiomyopathy undergoing prophylactic ICD implantation were prospectively enrolled (age 62±11 years, left ventricular ejection fraction 27±7%). High-resolution (1024 Hz) digital 12-lead ECGs were recorded during intrinsic rhythm. QRSp was quantified for each precordial lead as the total number of low-amplitude deflections that deviated from their respective naive QRS template. The primary end point of arrhythmic events was defined as appropriate ICD therapy or sustained ventricular tachyarrhythmias. After a median follow-up of 24 (15–43) months, 20 (20%) patients had arrhythmic events. Both QRSp and QRS duration were greater in those with arrhythmic events (both P<0.001) and this was consistent for QRSp for both cardiomyopathy types. In a multivariable Cox regression model that included age, left ventricular ejection fraction, QRS duration, and QRSp, only QRSp was an independent predictor of arrhythmic events (hazard ratio, 2.1; P<0.001). Receiver operating characteristic analysis revealed that a QRSp ≥2.25 identified arrhythmic events with greater sensitivity (100% versus 70%, P<0.05) and negative predictive value (100% versus 89%, P<0.05) than QRS duration ≥120 ms. Conclusions— QRSp measured from high-resolution digital 12-lead ECGs independently predicts ventricular tachyarrhythmias in ICD-eligible cardiomyopathy patients. This novel QRS morphology index has the potential to improve sudden death risk stratification and patient selection for prophylactic ICD therapy.

An algorithm for rotor tracking in atrial fibrillation using graph search-based periodic peak detection

Rotors are rotating electrical waves that may sustain atrial fibrillation (AF); thereby providing therapeutic targets for catheter ablation. We propose a method for identifying rotors from circular catheter recordings of bipolar intracardiac electrograms (EGM) during AF. We use dominant frequency-based periodicity detection along with a graph search algorithm to identify the most dominant periodic activations or peaks of interest in each bipolar EGM recorded by a multipolar circular catheter. We then track the activations across catheter bipoles to determine whether they conform to the rotational pattern of a rotor. The performance of the proposed method is tested on simulated bipolar EGM arrays containing rotor activation corrupted by noise and complex aperiodic signal features. The method is shown to perform with high accuracy (up to 98% sensitivity and 100% specificity) in detecting simulated rotors and may serve to guide rotor ablation in patients with AF.