Correlation waveform analysis to discriminate monomorphic ventricular tachycardia from sinus rhythm using stored electrograms from implantable defibrillators

An Adaptive Seismocardiography (SCG)-ECG Multimodal Framework for Cardiac Gating Using Artificial Neural Networks

To more accurately trigger data acquisition and reduce radiation exposure of coronary computed tomography angiography (CCTA), a multimodal framework utilizing both electrocardiography (ECG) and seismocardiography (SCG) for CCTA prospective gating is presented. Relying upon a three-layer artificial neural network that adaptively fuses individual ECG- and SCG-based quiescence predictions on a beat-by-beat basis, this framework yields a personalized quiescence prediction for each cardiac cycle. This framework was tested on seven healthy subjects (age: 22-48; m/f: 4/3) and eleven cardiac patients (age: 31-78; m/f: 6/5). Seventeen out of 18 benefited from the fusion-based prediction as compared to the ECG-only-based prediction, the traditional prospective gating method. Only one patient whose SCG was compromised by noise was more suitable for ECG-only-based prediction. On average, our fused ECG-SCG-based method improves cardiac quiescence prediction by 47% over ECG-only-based method; with both compared against the gold standard, B-mode echocardiography. Fusion-based prediction is also more resistant to heart rate variability than ECG-only- or SCG-only-based prediction. To assess the clinical value, the diagnostic quality of the CCTA reconstructed volumes from the quiescence derived from ECG-, SCG- and fusion-based predictions were graded by a board-certified radiologist using a Likert response format. Grading results indicated the fusion-based prediction improved diagnostic quality. ECG may be a sub-optimal modality for quiescence prediction and can be enhanced by the multimodal framework. The combination of ECG and SCG signals for quiescence prediction bears promise for a more personalized and reliable approach than ECG-only-based method to predict cardiac quiescence for prospective CCTA gating.

Rhythm Classification by Correlation-Waveform Morphology Analysis of Atrial and Ventricular Electrogram Signals

We tested the use of correlation-waveform analysis (CWA) of atrial and ventricular electrograms (EGMs) to distinguish ventricular tachycardia (VT) from supraventricular tachycardia (SVT). Patients undergoing electrophysiologic testing were enrolled. EGMs recorded during induced tachycardias were compared with EGMs recorded during sinus and paced rhythms, taken as templates, by assigning a CWA percent-match (CPM) score. Twenty-two patients were studied: 15 men and 7 women (mean age 48 years); 16 with SVT and 6 with VT. Using a sinus-rhythm template, the atrial CPM scores for SVT and VT were 66%+/- 20% and 93%+/- 5%, respectively (P = 0.0034). With a CPM-score cutoff of 85%, the sensitivity for correctly identifying VT was 100% and the specificity for rejection of SVT was 80%. The corresponding ventricular-CPM scores for SVT and VT were 81%+/- 12% and 72%+/- 24%, respectively (P = 0.13, cutoff = 65%, sensitivity = 50%, and specificity = 90%). Using a ventricular template with atrial pacing, the ventricular-CPM scores for SVT and VT were 87%+/- 9% and 76%+/- 14%, respectively (P = 0.028, cutoff = 70%, sensitivity = 50%, and specificity = 93%). Atrial CWA matching is superior to ventricular CWA matching in discriminating between SVT and VT. CWA matching in both chambers could potentially achieve better discrimination.

Testing of a new T-wave subtraction algorithm as an aid to localizing ectopic atrial beats

BACKGROUND

Identifying the timing and morphology of an ectopic P wave from the surface electrogram can aid in the diagnosis and localization of atrial arrhythmias. Given the relatively short coupling interval of atrial ectopic beats, the P wave is often obscured by the larger amplitude QRS-T wave complex. A method to uncover such "buried" P waves using a standard 12-lead surface ECG would be clinically useful and could potentially be a noninvasive guide to catheter ablation of focal atrial tachycardia.

METHODS

We developed an automated computerized program (BARD DUO LAB SYSTEM trade mark ) designed to subtract the QRS-T wave complex from the surface electrogram and uncover a previously obscured P wave. The purpose of the present study was to validate this program. The surface ECG from 21 patients undergoing atrial pacing during electrophysiologic study (group I) and 10 patients with atrial tachycardia (group II) were analyzed and the derived P-wave morphology assessed using correlation waveform analysis (CWA) and visual grading by three reviewers.

RESULTS

The algorithm successfully uncovered the P wave in each surface ECG. For the 21 patients in group I, average CWA comparing the derived P wave with the previous paced P wave was 83%. Average CWA for group II was 82%. Visual grading of the match between derived P waves and paced P waves revealed a 21/21 match in group I patients and a 12/12 match in 9/10 of group II patients.

CONCLUSIONS

An ectopic atrial P wave obscured by a coincident QRS-T wave complex can be accurately uncovered using this new algorithm. Addition of this technique to existing methods may improve the diagnosis of atrial arrhythmias and aid in the localization and ablation of ectopic atrial foci.

The clinician's approach to evaluating patients with dysrhythmias

As cardiac arrhythmia services and the ability to perform electrophysiologic testing become more prevalent in the hospital setting, advanced practice nurses (APNs) are continually challenged to keep their skills in evaluating patients with dysrhythmias sharp and current. The experienced APN evaluates the patient's history, recognizes physical findings, and uses noninvasive data to help diagnose, anticipate, and even prevent dysrhythmias. This article reviews the essential components of a systematic evaluation of patients with a known or potential rhythm disturbance.

Past and future technologic developments for rhythm and conduction disturbances

Since the first cardiac pacemaker was implanted in 1958, continuing technologic innovations have steadily improved the therapeutic power of implantable cardiac device therapy. This evolution has benefited both patients and their physicians, expanding the conditions manageable through pacing and implantable defibrillation while streamlining implant and follow-up procedures. This progress is likely to continue unabated because (1) devices will continue to grow smaller; (2) more advanced features will be introduced, with an increased level of automaticity; and (3) the quality and quantity of telemetered diagnostic information about both patient and device will continue to expand, and device sophistication will soon reach the point at which prediction and prevention of specific events will be a reality. This article reviews historical developments and presents concepts that are guiding future technologic innovations.