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Background: T-wave alternans (TWA) increases acutely prior to ventricular tachycardia (VT) or fibrillation (VF) in animal studies, suggesting that it may provide a warning for VT/VF in implantable cardioverter defibrillator (ICD) patients. Clinically, measurement of surface ECG TWA requires preprocessing the input signal to reduce noise and/or analyzing more sinus beats than are recorded in ICDs as pre-onset, stored intracardiac electrograms (EGMs) before VT/VF. Our objective was to measure TWA from the few sinus EGMs stored in ICDs before spontaneous VT/VF in humans., Objective: The purpose of this study was to evaluate the technical feasibility of measuring TWA from pre-onset ICD EGMs and to measure EGM TWA before spontaneous VT/VF in humans., Methods: We developed a method to measure EGM TWA as a simple average (AVE) of peak-to-peak alternans. Using simulation, we determined the effect of ICD signal processing on EGM TWA for durations comparable to those in pre-onset EGMs. We then applied this method to pre-onset ICD EGMs that preceded 101 episodes of sustained VT/VF in 10 patients. In 6 of these patients, EGM recordings in atrial pacing and sinus rhythm provided control data., Results: In simulation, the AVE method discriminated input TWA differences > or = 15 microV. In patients, EGM TWA was 78 +/- 62 microV prior to VT/VF vs. 13 +/- 10 microV in control recordings (p< .0001). Eighty percent of pre-onset measurements exceeded 30 microV, while 95% of control measurements were less than 30 microV., Conclusions: A simple averaging method can measure TWA preceding VT/VF in stored ICD EGMs. Pilot data indicate that high-amplitude EGM TWA usually precedes spontaneous VT/VF and is infrequent in control recordings. They provide a rationale for developing ICD technology to measure EGM TWA continuously, both to warn patients and to initiate pacing algorithms to prevent VT/VF.

Implantable devices such as pacemakers and implantable cardioverter/defibrillators (ICDs) use algorithms to sense cardiac depolarizations and to detect tachyarrhythmias by analysis of timing and morphology of sensed events. The purpose of tachyarrhythmia detection in these devices is to guide electrical therapies delivered by the pacemaker or ICD and/or to provide clinical diagnostics for medical management of patients. Unlike electrocardiographic analysis methods that rely on postanalysis of recorded signals using desktop computers, implantable devices must make detection decisions on a beat-by-beat basis with algorithms that can be implemented in battery-powered devices with longevities of up to several years. Cardiac sensing in implantable devices is achieved using amplifiers, bandpass filters, and adaptive thresholds to avoid oversensing of cardiac and noncardiac activity, while avoiding undersensing of low-amplitude cardiac activations during fibrillation. The tachyarrhythmia detection algorithms are formed by combining different building blocks of rhythm information extracted from timing of cardiac activations and from electrogram morphology information. Tachyarrhythmia detection algorithms in ICDs were originally designed to achieve high sensitivity for detection of life-threatening tachyarrhythmias such as ventricular tachycardia and ventricular fibrillation. Much of the progress in ICD detection algorithms in the past 15 years has been in the development of supraventricular tachycardia discrimination algorithms to reduce the number of inappropriate therapies delivered by ICDs. This article provides an overview of current tachyarrhythmia detection approaches, describe challenges facing tachyarrhythmia detection algorithm performance in ICD patients with primary prevention indications, and presents future directions in cardiac tachyarrhythmia detection for implantable devices.