Pranav Bhagirath

167 A priori model independent inverse potential mapping: the impact of electrode positioning INTRODUCTION Inverse potential mapping (IPM) is a promising technique that may complement conventional invasive electrophysiological (EP) studies [1-2]. In IPM, local epicardial potentials are inversely computed from recorded body surface potentials (BSP) [3]. Typically, 252 electrodes surrounding the thorax are used to record BSP [4-5]. When a smaller number of recording electrodes is used, optimal electrode positioning is important. In the past, several studies have addressed this topic. Early studies focused on the detection and elimination of redundant information in the recorded BSP [6– 10]. Later, biophysical a priori models, i.e., computer models that enable the in silico mimicking of in vivo conditions by using pre-programmed settings relating to physical properties, e.g., conduction velocity, fiber orientation, anisotropy, activation pathways, were introduced to compensate for the limited BSP data actually recorded [11]. In general, inverse procedures involving 64 or fewer electrodes always apply an a priori activation model. The purpose of this study was to investigate the feasibility of IPM using only 62 torso electrodes in the absence of an a priori model. A simulation using 252 electrodes served as a reference for desired image quality. Simulations were performed using various electrode configurations. Three different electrode positions using 62 electrodes were subsequently applied on healthy volunteers to record BSP. From the recorded BSP, epicardial potentials were reconstructed. The amount of detail and the correlation with the original source model were assessed. To evaluate the localisation error and size of the smallest visible detail, this mapping technique was applied in four patients with an implanted MRI-conditional DDD pacemaker system. METHODS Computer simulations 3Dmodel Simulations were performed using a 3D thorax model. This model was constructed after manual segmentation of different structures and organs on anatomic magnetic resonance imaging (MRI) images using customwritten software.Themodel incorporated the whole-heart (including atria, ventricles, septum), liver, lungs, spleen, and torso surface. To each of these tissue elements conductivities were assigned as reported in