Vector Quantization of T Wave Abnormalities Associated with a Predisposition to Ventricular Arrhythmias and Sudden Death

Background Previous studies have suggested that irregular T wave morphologies are associated with an increased risk of sudden death. However, automated characterization of T wave abnormalities has been hampered by the lack of suitable analysis techniques. In this study, we tested a new method of T wave analysis in German shepherd dogs with inherited ventricular arrhythmias and sudden death. Methods Sets of 24‐hour ambulatory ECG recordings obtained from unaffected (n = 6) and affected (n = 5) dogs were digitized, automatically annotated to label each R wave, and placed into a matrix with the R waves aligned. A vector quantization algorithm separated the QRS‐T complexes into classes according to T wave morphology. The existence of notched T waves was determined by assessing the number of zero crossings of the first derivative during the T wave. Results The duration of the QT interval was similar in affected and unaffected dogs (182 ± 14 ms vs 176 ± 16 ms, respectively). However, T wave morphology differed between the two groups. Specifically, affected dogs had a higher percentage of notched T waves than unaffected dogs (41.6%± 10.8% vs 5.0%± 1.2%, respectively). Notched T waves did not appear at all times of day, nor were they present in all leads. Conclusion Vector quantization and first derivative analyses were feasible and effective methods for detecting T wave abnormalities associated with the development of ventricular arrhythmias These methods ultimately may be useful for risk stratification of patients susceptible to ventricular arrhythmias and sudden death.