Ihor Varha, MSc.

Identification of subcortical structures is an essential step in surgical planning for interventions such as the deep brain stimulation (DBS), in which permanent electrode is implanted in a precisely defined location. For refinement of the target localisation and compensation of brain shift occurring during the surgery, intra-operative electrophysiological recording using microelectrodes is usually undertaken. In this paper, we present a multimodal method that consists of a) subthalamic nucleus (STN) segmentation from magnetic resonance T2 images using 3D active contour fitting and b) a subsequent brain shift compensation step, increasing the accuracy of microelectrode placement localisation by the probabilistic electrophysiology-based fitting. The method is evaluated on a data set of 39 multi-electrode trajectories from 20 patients undergoing DBS surgery for Parkinson’s disease in a leave-one-subject-out scenario. The performance comparison shows increased sensitivity and slightly decreased specificity of STN identification using the individually-segmented 3D contours, compared to electrophysiology-based refinement of a standard 3D atlas. To achieve accurate segmentation from the low-resolution clinical T2 images, a more sophisticated approach, including shape priors and intensity model, needs to be implemented. However, the presented approach is a step towards automatic identification of microelectrode recording sites and possibly also an assistive system for the DBS surgery.