Evaluation of ECGI Localization Accuracy for Single Pacings in CRT Patients

Abstract

ECG imaging (ECGI) is a noninvasive tool for estimating cardiac electrical activity from body surface potentials. Recently, there have been significant methodological improvements as well as a tremendous progress in the validation of ECGI reflected by an increasing number of published studies. Notwithstanding this progress, ECGI has neither been integrated into the clinical workflow concept nor achieved a clear positioning regarding its practical benefits involving cost and procedural time reduction. One of the main hurdles lies in the scarcity of high quality validation data. With this respect, the goal of the present study is to evaluate performance of three well-established inverse methods for ten cardiac resynchronization therapy (CRT) patients: the model-based fastest route algorithm (FRA), data-driven Tikhonov regularization, and a FRA-based maximum a posteriori methods were analyzed. Locations of the implanted pacing leads were exactly known from CT images, making them perfectly suited for ECGI accuracy assessment of focal activation sequences.