Evaluation of five algorithms in predicting the sublocalisation of right ventricular outflow tract arrhythmia (RVOTA) when compared to 3D electroanatomical mapping origin

Abstract

Abstract Introduction The majority of idiopathic ventricular arrythmias arise from the right ventricular outflow tract (RVOT) and they represent nearly 10% of all ventricular tachycardia (VT) admissions. It is paramount to precisely predict the origin of RVOT arrhythmias to define the appropriate approach before the ablation procedure. Conventional 12-lead electrocardiogram (ECG) is a useful tool for analysing cardiac arrhythmias, and numerous ECG algorithms for predicting the origin of RVOT arrhythmias have been reported. Purpose To compare the predictive accuracy of five different algorithms as verified by successful ablation site using 3D electroanatomical non-contact mapping in patients with symptomatic and asymptomatic but high ventricular burden right ventricular outflow tract (RVOT) tachycardias. Methods 28 consecutive patients admitted for radiofrequency catheter ablation for symptomatic and asymptomatic, but high ventricular burden idiopathic premature ventricular contractions (PVC) were recruited for this study. All patients had previous failed or intolerant to beta-blocker and/or at least one class IC anti-arrhythmic agents, and they had normal left ventricular ejection fraction. All patients had documented monomorphic PVC with left bundle branch block morphology and an inferior axis. Concordance of the arrhythmia origin based on ECG algorithm and 3D mapping system site were further evaluated. Of the five algorithms, two algorithms with easy-applicability and having a memorable design (Dixit and Joshi) and three algorithms with more complex and detailed design (Ito, Zhang, Pytkowski) were selected for comparisons. Results Assessment of the diagnostic accuracy showed that each of the five algorithms had only moderate accuracy, and the greatest accuracy was observed in the algorithm proposed by Pytkowski algorithm when assessed by a general cardiologist and Dixit and Pytkowski algorithms when evaluated by the electrophysiologist. However, when the algorithms were compared for their accuracy, specificity, sensitivity, no significant differences were found (p=0.99). Conclusions All the five published 12-lead ECG algorithms for RVOT location were similar in terms of the diagnostic accuracy, specificity, and sensitivity. In our study, Pytkowski algorithm exhibits the best accuracy and sensitivity among the algorithms, while predicting a precise location and when evaluation is performed by electrophysiologists and/or cardiologists. Funding Acknowledgement Type of funding sources: None.