[en] Abstract Deep brain stimulation (DBS) is a neurosurgical intervention where electrodes are permanently implanted into the brain in order to modulate pathologic neural activity. The post-operative reconstruction of the DBS electrodes is important for an efficient stimulation parameter tuning. A major limitation of existing approaches for electrode reconstruction from post-operative imaging that prevents the clinical routine use is that they are manual or semi-automatic, and thus both time-consuming and subjective. Moreover, the existing methods rely on a simplified model of a straight line electrode trajectory, rather than the more realistic curved trajectory. The main contribution of this paper is that for the first time we present a highly accurate and fully automated method for electrode reconstruction that considers curved trajectories. The robustness of our proposed method is demonstrated using a multi-center clinical dataset consisting of N=44 electrodes. In all cases the electrode trajectories were successfully identified and reconstructed. In addition, the accuracy is demonstrated quantitatively using a high-accuracy phantom with known ground truth. In the phantom experiment, the method could detect individual electrode contacts with high accuracy and the trajectory reconstruction reached an error level below 100 μm (0.046 ± 0.025 mm). An implementation of the method is made publicly available such that it can directly be used by researchers or clinicians. This constitutes an important step towards future integration of lead reconstruction into standard clinical care.
Research center :
- Luxembourg Centre for Systems Biomedicine (LCSB): Systems Control (Goncalves Group)
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Husch, Andreas ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC)
Petersen, Mikkel V.; Aarhus University, Aarhus, Denmark > Department of Clinical Medicine > Center of Functionally Integrative Neuroscience
Gemmar, Peter
Goncalves, Jorge ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Hertel, Frank ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
External co-authors :
yes
Language :
English
Title :
PaCER - A fully automated method for electrode trajectory and contact reconstruction in deep brain stimulation