The shocking truth.
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American Heart Association↗
Biomedical subjects
E J Berbari
Publications and source records attributed to E J Berbari.
Differences in organization between acute and chronic atrial fibrillation in dogs.
OBJECTIVES: The purpose of this study was to determine differences in acute and chronic atrial fibrillation (AF) "organization" in canine models. BACKGROUND: Electrophysiologic changes occur during atrial remodeling, but little is known about how remodeling affects AF organization. We hypothesized that atrial remodeling induced by long-term rapid atrial rates heterogeneously decreases AF organization. METHODS: In seven dogs, acute AF was induced by atrial burst pacing, and in eight dogs chronic AF was created by six weeks of continuous rapid atrial pacing. Atrial fibrillation was epicardially mapped from the right atria (RA) and left atria (LA). Atrial cycle length (CL), spatial organization and activation maps were compared. Spatial organization was quantified by an objective signal processing measure between multiple electrograms. RESULTS In acute AF, mean CL was slightly shorter in the LA (124 +/- 16 ms) than it was in the RA (131 +/- 14 ms) (p < 0.0001). In chronic AF, LA CL (96 +/- 14 ms) averaged 24 ms shorter than RA CL (121 +/- 18 ms) (p < 0.0001). Right atria and LA in acute AF had similar levels of organization. In chronic AF, the LA became approximately 25% more disorganized (p < 0.0001) while the RA did not change. In acute AF, a single broad wave front originating from the posterior and medial atrium dominated LA activation. In chronic AF, LA activation was more complex, sustaining multiple reentrant wavelets in the free wall and lateral appendage. CONCLUSIONS: Acute and chronic AF exhibit heterogeneous differences in CL, organization and activation patterns. The LA in chronic AF is faster and more disorganized than it is in acute AF. Differences in the models may be due to heterogeneous electrophysiologic remodeling and anatomic constraints. The design of future AF therapies may benefit by addressing the patient specific degree of atrial remodeling.
Acute Disease↗
A high-temporal resolution algorithm for quantifying organization during atrial fibrillation.
Atrial fibrillation (AF) has been described as a "random" or "chaotic" rhythm. Evidence suggests that AF may have transient episodes of temporal and spatial organization. We introduce a new algorithm that quantifies AF organization by the mean-squared error (MSE) in the linear prediction between two cardiac electrograms. This algorithm calculates organization at a finer temporal resolution. (approximately 300 ms) than previously published algorithms. Using canine atrial epicardial mapping data, we verified that the MSE algorithm showed nonfibrillatory rhythms to be significantly more organized than fibrillatory rhythms (p < .00001). Further, we compared the sensitivity of MSE to that of two previously published algorithms by analyzing AF with simulated noise and AF manipulated with vagal stimulation or by adenosine administration to alter the character of the AF. MSE performed favorably in the presence of noise. While all three algorithms distinguished between low and high vagal AF, MSE was the most sensitive in its discrimination. Only MSE could distinguish baseline AF from AF with adenosine. We conclude that our algorithm can distinguish different levels of organization during AF with a greater temporal resolution and sensitivity than previously described algorithms. This algorithm could lead to new ways of analyzing and understanding AF as well as improved techniques in AF therapy.
Algorithms↗
Analysis of abnormal intra-QRS potentials. Improved predictive value for arrhythmic events with the signal-averaged electrocardiogram.
BACKGROUND: Using the signal-averaged ECG (SAECG), this study developed a new electrical index for predicting arrhythmic events: abnormal intra-QRS potentials (AIQP). METHODS AND RESULTS: We studied 173 patients followed after myocardial infarction for a mean duration of 14 +/- 7 months. Sixteen arrhythmic events occurred, defined as sudden cardiac death, documented sustained ventricular tachycardia, or non-fatal cardiac arrest. Noninvasive indices of arrhythmia risk were measured, including AIQP, conventional SAECG, Holter, and left ventricular ejection fraction (LVEF). Abnormal intra-QRS potentials were defined as abnormal signals occurring anywhere within the QRS period. They were estimated with a lead-specific, parametric modeling method that removed the smooth, predictable part of the QRS. AIQPs are characterized by the remaining transient, unpredictable component of the QRS and manifest as low-amplitude notches and slurs. A combined XYZ-lead AIQP index exhibited higher specificity (95%) and predictive value (PV) (+PV, 47%; -PV, 94%) than the conventional SAECG in combination with Holter and LVEF (specificity, 89%; +PV, 25%; -PV, 93%). CONCLUSIONS: AIQP improved specificity and predictive value, compared with conventional tests, for prediction of arrhythmic events. AIQP emerged as the best noninvasive univariate predictor of arrhythmic events after myocardial infarction in this study. A review of several other reports shows that AIQP in the present study outperformed the conventional predictive indices reported in those other data sets.
Arrhythmias, Cardiac↗
Time-frequency plane Wiener filtering of the high-resolution ECG: background and time-frequency representations.
This paper introduces the concept of a posteriori Wiener filtering (APWF), performed in the time-frequency plane. The objective is to improve the signal-to-noise ratio (SNR) of the ensemble-averaged high-resolution electrocardiogram (HRECG). APWF was developed to address the problem of a limited ensemble size for estimating ensemble-averaged evoked potentials. For the HRECG, we identify the major challenge as adapting the time-frequency structure of the filter to that of low-level cardiac signals. Technical limitations and the characteristics of HRECG signals make time-frequency analysis of the ensemble average problematic. Normal and abnormal signal components are difficult to distinguish due to low time-frequency energy concentration and limited spectrotemporal resolution. However, considering the entire ensemble of repetitive ECG records, signal and noise components are separable in the time-frequency plane. This forms the basis of the new time-frequency plane Wiener (TFPW) filter, applicable to any ensemble averaging problem involving repetitive deterministic signals mixed with uncorrelated noise.
Electrocardiography↗
Time-frequency plane Wiener filtering of the high-resolution ECG: development and application.
The time-frequency plane Wiener (TFPW) filter is a new method, based on a posteriori Wiener filtering principles, to enhance the performance of ensemble averaging. This paper develops the mathematical aspects of the TFPW filter, and assesses its performance with elementary signals, such as sine waves and chirps, and authentic high-resolution electrocardiogram (HRECG) ensembles. The principal feature of the TFPW filter is its use of the time-frequency plane to accommodate signal nonstationarity. Using a posteriori computed statistics of the ensemble, the filter matches itself to the time-frequency structure of the signals to be estimated. The method is sufficiently general to be applicable to any class of repetitive signal with a deterministic time-frequency structure and additive noise in the ensemble. It is concluded that significant improvements in both estimated signal fidelity and noise reduction are possible with the TFPW filter, compared to conventional ensemble averaging.
Electrocardiography↗
Analysis of abnormal signals within the QRS complex of the high-resolution electrocardiogram.
This paper presents a new, quantitative approach to measuring abnormal intra-QRS signals, using the high-resolution electrocardiogram (HRECG). These signals are conventionally known as QRS "notches and slurs." They are measured qualitatively and form the basis for the ECG identification of myocardial infarction. The HRECG is used for detection of ventricular late potentials (LP), which are linked with the presence of a reentry substrate for ventricular tachycardia (VT) after a myocardial infarction. LP's are defined as signals from areas of delayed conduction which outlast the normal QRS period. Our objective is to quantify very low-level abnormal signals that may not outlast the normal QRS period. In this work, abnormal intra-QRS potentials (AIQP) were characterized by removing the predictable, smooth part of the QRS from the original waveform. This was represented as the impulse response of an ARX parametric model, with model order selected empirically from a training data set. AIQP were estimated using the residual of the modeling procedure. Critical AIQP parameters to separate VT and non-VT subjects were obtained using discriminant functions. Results suggest that AIQP indexes are a new predictive index of the HRECG for VT. The concept of abnormal intra-QRS potentials permits the characterization of pathophysiological signals contained wholly within the normal QRS period, but related to arrhythmogenesis. The new method may have other applications, such as detection of myocardial ischemia and improved ECG identification of the site of myocardial infarction, particularly in the absence of Q waves.
Electrocardiography↗
Epicardial maps of atrial fibrillation after linear ablation lesions.
INTRODUCTION: The purpose of this study was to investigate the mechanisms by which atrial linear ablation lesions eliminate atrial fibrillation (AF). METHODS AND RESULTS: With an array of 112 unipole, epicardial maps of electrically induced AF in 6 dogs (acute group), self-sustained AF in 6 dogs (chronic group), and sinus rhythm and atrial pacing in 3 dogs (control group) were analyzed before and after creating linear radiofrequency ablation lesions in both atria that eliminated the AF. In the acute and chronic groups, activation maps showed multiple wavelets with complex patterns of activation and reentry during AF. Conduction velocity and the number, size, and complexity of wavelets did not change, whereas median fibrillatory cycle length increased with the number of linear lesions. In the control group, refractoriness and conduction velocity were unaffected by the number of lesions. CONCLUSIONS: In these models of AF, linear lesions that eliminate AF increase the cycle length of AF without changing conduction velocity, number of size of wavelets, or complexity of activation patterns.
Animals↗
The signal-averaged electrocardiogram: update on clinical applications.
The signal-averaged electrocardiogram (SAECG) facilitates noninvasive recording of low-amplitude cardiac signals such as ventricular late potentials. The SAECG has been used to accurately predict life-threatening ventricular tachyarrhythmias in patients after acute myocardial infarction and with nonischemic dilated cardiomyopathy, and to screen for inducible ventricular tachycardia in patients with unexplained syncope and with nonsustained ventricular tachycardia. This review focuses on currently accepted methodology and clinical and research applications of the SAECG.
Arrhythmias, Cardiac↗
Optimal filtering and quality control of the signal-averaged ECG. High-fidelity 1-minute recordings.
BACKGROUND: The clinical performance of the signal-averaged ECG (SAECG) for prediction of ventricular tachycardia (VT) depends on its quality, or final noise level. However, signal averaging is a statistical estimation procedure that is time-consuming and vulnerable to noise-induced error. The optimally filtered SAECG is proposed as a simple, quality-assured procedure requiring only 1 minute of data. METHODS AND RESULTS: The optimally filtered SAECG is based on measures of signal variance and time-frequency representations. Forty subjects were studied to compare a 0.3-microV root-mean-square (RMS) noise endpoint SAECG with an optimally filtered 64-beat ensemble. Eight SAECGs were computed with noise endpoints of 1.0-through 0.3-microV RMS. Noise measurements were also made directly from the filtered SAECG. From these and previously published data, sensitivity was predicted as a function of noise endpoint. Measured QRS parameters and final noise were highly similar between the optimally filtered SAECG and the 0.3-microV RMS noise endpoint SAECG. CONCLUSIONS: The optimally filtered 64-beat SAECG achieves a performance (equivalent noise reduction, signal definition, and mathematically predicted sensitivity for VT) similar to a 0.3-microV RMS noise endpoint average. Testing in a large clinical database is required to validate the method for routine clinical use. SAECGs terminated by use of different noise measurement techniques are not directly comparable because of measurement technique dependence. However, a formula is presented for comparison of statistics between studies that have used the most popular noise measurement techniques.
Electrocardiography↗
Differences in the effect of acute ischemia on late potentials in susceptible and resistant dogs for sudden cardiac death.
The low predictive value of the signal averaged ECG (SAECG) at rest may be due to the absence of any physiological perturbation. This study assessed changes of late potentials (LP) in the SAECG due to acute ischemia in five susceptible (S) and five resistant (R) dogs for sudden cardiac death. SAECGs were measured at rest prior to and during the last 3 min of 4 min transient occlusion of the left circumflex artery (CAO). At rest no significant differences were seen in the QRS duration (QRSD), the low amplitude signal duration (LAS40) and the root mean square voltage (RMS20) between S and R dogs. However, acute ischemia caused significant increases in QRSD and LAS40, but only in the S dogs. These results indicate differences in the ischemic modulation of the arrhythmogenic substrate in S and R group. Analysis of LP during acute ischemia may provide an important increase in the positive predictive value of the SAECG.
Animals↗
Analysis of alternans in late potentials. Correlations between epicardial and body surface recordings.
The methodical performance of the signal-averaged electrocardiogram is strongly influenced by the beat-to-beat reproducibility of late potentials (LPs). Especially at higher heart rates, epicardial recordings from infarct regions show progressive beat-to-beat prolongations with alternating conduction block. To analyze the influence of beat-to-beat-alternans of LPs on the signal-averaging process, epicardial and body surface recordings were studied at different heart rates and extrastimulation. Epicardial and body surface recordings were obtained from dogs with 4-day postligation of the left anterior descending coronary artery (Harris model). Body surface potentials were averaged in different modes to a final noise level of 0.3 microV (rms) and digitally bandpass filtered (40-250 Hz). Modulation of the heart rate was performed by atrial or His-bundle pacing and by atrial premature extrastimulation. Pacing up to heart rates close to 180 beats/min produced no significant changes in the duration of LPs in epicardial and averaged body surface recordings; however, at higher pacing rates, considerable prolongation of LPs with different patterns in the epicardial leads was observed. In these cases, averaging of all beats revealed only a slight prolongation of LPs, as seen from the body surface. Selective averaging of beats with prolonged epicardial LPs showed the prolongation or absence of LPs, as seen in the epicardial recordings. Similar observations were made using an atrial extrastimulation technique, whereby the average of the premature beats was compared to the average of all normal sinus beats. Selective beat averaging of body surface potentials can unmask the prolongation of LPs due to atrial pacing or extrastimulation, as seen in recordings from the infarcted epicardium. The evidence of this modulation of LPs may improve the positive predictive value of the signal-averaged electrocardiogram.
Action Potentials↗
Changes in high-frequency QRS components during prolonged coronary artery occlusion in humans.
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Adult↗
Simulation of intracardiac electrograms with a moving dipole source. Role of electrode geometry and high-pass filtering.
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Electrocardiography↗
Time-frequency structure of the high-resolution ECG.
This study considers the problem of representing high-resolution ECG (HRECG) signals in the time-frequency plane using spectrotemporal mapping (STM). High-resolution ECG signal components overlap in both time and frequency. The central issue with STM techniques is whether sufficient time-frequency resolution exists to discriminate normal and abnormal QRS signals. The trade-off between signal resolution in time and in frequency must be made without a priori knowledge of the HRECG's time-frequency structure. A simulation experiment was performed to examine the time-frequency distribution of normal, abnormal low-level (late potentials), and bundle branch block components of the QRS. Results suggest that discrimination of these signals with STM is problematic. Signals and noise within the HRECG ensemble can, however, be easily distinguished. This observation forms the basis of a new optimally filtered ensemble averaging technique for signal-to-noise ratio enhancement.
Electrocardiography↗
Late potentials are unaffected by radiofrequency catheter ablation in patients with ventricular tachycardia.
Reentrant ventricular tachycardia is dependent on an area of myofibers, embedded in scar tissue, which exhibit slow conduction. Late potentials recorded by signal-averaged electrocardiography appear to correspond to these zones of slow conduction and frequently are present in patients with VT. We hypothesized that elimination of inducible VT by catheter-mediated ablation of critical areas of slow conduction would alter late potentials. Four patients underwent catheter ablation in which radiofrequency current was delivered to zones of slow conduction exhibiting isolated mid-diastolic potentials that could not be dissociated from the tachycardia. The four patients had developed VT (cycle length 382 +/- 50 msec; mean +/- SEM) 13-180 months after inferior myocardial infarction. Late potentials were present in each patient before catheter ablation was attempted. Although VT was not inducible in any patient immediately after ablation, late potentials were still present in all four patients and there was no significant difference in the QRS duration (136.5 +/- 4.0 msec postablation; 135.7 +/- 4.5 msec preablation), root mean square voltage in the terminal 40 msec of the QRS (10.0 +/- 1.0 microV postablation; 5.9 +/- 0.4 microV preablation), or in the duration of the low amplitude signal (69.2 +/- 2.0 msec postablation; 62.7 +/- 3.4 msec preablation). At follow-up electrophysiology study performed 14 +/- 7 days after ablation, one of the four patients had inducible VT. In conclusion, late potentials persist even after successful radiofrequency catheter ablation and do not appear to be useful for predicting results of follow-up electrophysiology study.
Action Potentials↗
Identifying the end of ventricular activation: body surface late potentials versus electrogram measurements in a canine infarction model.
INTRODUCTION: Identification of the end of the QRS is perhaps the single most important feature obtained from the high resolution signal-averaged electrocardiogram (SAECG). This point relies on computer algorithms to select a point above the noise levels. Prior studies to substantiate this approach using electrograms for comparison have demonstrated many examples of the body surface recordings failing to detect the full extent of the late potentials. METHODS AND RESULTS: An animal model that generates late potentials was used in conjunction with epicardial cardiac mapping system to systematically examine the reasons for these failures. In 11 of 13 dogs we found a concordance between the signal-averaged recordings and the epicardial recordings within 5 msec. The two discordant studies were attributed to a failure of epicardial mapping to record all late potential sources. Also, a means of accurately comparing measurements from the two recording technologies was required in this study as well as a new definition for identifying the end of activation currents in epicardial electrograms. CONCLUSION: To achieve these results required approaches different from those used in the clinical setting to record the SAECG. These include: (1) the analysis of individual XYZ leads as opposed to the vector magnitude derived from these leads; (2) visual identification of very low level signals, as automatic algorithms often fail to detect low level signals; and (3) the use of finite impulse response digital filters instead of the bidirectional Butterworth filter.
Action Potentials↗
Critical analysis of the signal-averaged electrocardiogram. Improved identification of late potentials.
BACKGROUND: This study performed a critical analysis of signal-averaging methods. The objective was to optimize detection of late potentials. METHODS AND RESULTS: We studied two patient populations: a low-arrhythmia-risk group with no evidence of heart disease and a group with clinically documented ventricular tachycardia (VT). Filtered QRS duration (QRSD) and terminal QRS amplitude (RMS40) were measured from the vector magnitude. A QRS duration based on the latest detectable ventricular activity in any of the three individual XYZ leads was also measured. Because of improved signal-to-noise ratio, both individual lead analysis and extended (600-versus 200-beat) averaging yielded significant changes in signal-averaged ECG parameters. Both approaches gave an increased sensitivity for VT identification. Sensitivity, specificity, and accuracy were evaluated as functions of critical values of QRSD and RMS40. RMS measurements in the terminal QRS, ranging from 20 to 100 msec and including RMS40, did not contribute to maximizing sensitivity and were highly correlated with QRSD. Our results from the low-arrhythmia-risk group suggest that age and sex should be considered in the definition of late potentials. CONCLUSIONS: We propose a VT risk stratification scheme using signal-averaged ECG parameters obtained from both individual lead and vector magnitude analysis. This allows definition of four categories of VT risk derived statistically from the study data. This definition is based on combined measures of sensitivity, specificity, and negative and positive predictive value.
Aged↗