Clinical Evaluation of Endocardial ECGI Mapping Accuracy in the Septal Area Using Different Equivalent Single Layer Algorithms

Mikhail Chmelevsky1, Danila Potyagaylo2, Margarita Budanova1, Stepan Zubarev3, Tatjana Treshkur3, Dmitry Lebedev3
1Almazov National Medical Research Centre, 2EP Solutions, 3Almazov National Medical Research Center


Background. Noninvasive ECGI mapping has recently become one of the primary focus of active and ongoing researches in electrocardiology. However, endocardial ECGI accuracy of ventricular septal area has not been investigated. Aim. To evaluate endocardial ECGI mapping accuracy with focal septal pacing in patients with previously implanted pacemakers using different single layer source algorithms. Methods. 11 patients (median age 62 years; min-max 27-78 years, 5 male) with previously implanted pacemakers underwent epi-endocardial ECGI mapping using “Amycard 01C EP Lab” system (EP Solutions SA, Switzerland). 240-channell ECG were recorded during right endocardial septal pacing followed by torso and ECG-gated cardiac computed tomography. The data obtained from CT was imported into “Amycard 01C EP lab” software in DICOM-format to reconstruct 3D polygonal models of the torso and heart. In this study we consider only epi-endocardial 3D models of the heart. Afterwards endocardial unipolar electrograms as well as isopotential maps were reconstructed using four different equivalent single layer (ESL) algorithms. Early activation zone was determined on the isopotential map of endocardial models. Euclidean as well as geodesic distances between real pacing point and detected early activation zone were calculated for different algorithms. A p-value < 0.01 was considered as statistically significant. Statistical analysis was performed using Statistica v.12 (Statsoft Inc, USA). Results. The mean (SD) geodesic distance between noninvasively reconstructed and the reference pacing sites was 22 (15) mm for the best ESL algorithm. There was no significant difference in accuracy for all four ESL-based algorithms used in this study. Conclusions. The study showed insufficient accuracy to use this technology in routine clinical practice for identification of focal arrhythmia sources in the septal region. At the same time, the lack of significant difference between algorithms accuracy shows that another approach should be investigated for septal area.