gms | German Medical Science

63rd Annual Meeting of the German Society of Neurosurgery (DGNC)
Joint Meeting with the Japanese Neurosurgical Society (JNS)

German Society of Neurosurgery (DGNC)

13 - 16 June 2012, Leipzig

Investigation of an image-based tool for planning safe trajectories in deep-brain-stimulation

Meeting Abstract

  • C. Kappus - Klinik für Neurochirurgie, Universitätsklinikum Marburg, Marburg
  • J. Egger - Klinik für Neurochirurgie, Universitätsklinikum Marburg, Marburg; FB Mathematik & Informatik, Universität Marburg, Marburg
  • B. Carl - Klinik für Neurochirurgie, Universitätsklinikum Marburg, Marburg
  • M. Bauer - Klinik für Neurochirurgie, Universitätsklinikum Marburg, Marburg; FB Mathematik & Informatik, Universität Marburg, Marburg
  • C. Nimsky - Klinik für Neurochirurgie, Universitätsklinikum Marburg, Marburg

Deutsche Gesellschaft für Neurochirurgie. Japanische Gesellschaft für Neurochirurgie. 63. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Japanischen Gesellschaft für Neurochirurgie (JNS). Leipzig, 13.-16.06.2012. Düsseldorf: German Medical Science GMS Publishing House; 2012. DocP 048

doi: 10.3205/12dgnc435, urn:nbn:de:0183-12dgnc4351

Published: June 4, 2012

© 2012 Kappus et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



Objective: Planning of trajectories for deep brain stimulation (DBS) is nowadays based on MRI-data and adapted to the individual anatomy. In some cases planning is very easy to perform, while in others it can be very complicated and time-consuming. The surgeon has to identify a safe trajectory, never knowing whether there is a better one, which he was not able to identify. While MRI data consists of gray-values, risk-structers are identified by aberrations differing from the gray-matter. Aim of this study is to fasten the procedure of planning by giving the surgeon computer-generated coordinates for potential safe trajectories.

Methods: MRI-datasets of 10 DBS-Implantations were exported from Framelink5®. An algorithm was implemented using C++ on MeVisLab® platform for creating multiple possible trajectories for electrode-placement as vectors in a 3D dataset of a T1-weighted MRI acquired for DBS-procedure. A safety-region of 5 mm was set around each trajectory. For that the algorithm was supplied with the target-point and the entry-point of the clinical DBS-procedure, based on AC-PC coordinates. Multiple trajectories were virtually created and evaluated by the algorithm, by analyzing the grayscale-values along each trajectory. Values excessing or underrunning a specified range were defined as unsafe, a ranking was generated containing all tested coordinates. The five trajectories determined as safest in each dataset were reimported to Framelink5® and a blinded evaluation was performed by a neurosurgeon experienced in DBS, comparing them with the surgical-trajectory.

Results: The automatic calculation and ranking of trajectories in our implementation took less then 3 seconds (measured on an Intel Core i5-750 CPU) Ranking of the trajectories showed that in all evaluated datasets the clinical trajectory was among the first ten software-generated trajectories in ranking. Blinded evaluation of the safest trajectories generated by software led to a different “optimal” trajectory in 9 of 10 cases compared with former surgery. All of the best 5 potential trajectories generated and evaluated by the algorithm were identified as safe alternative by the surgeon.

Conclusions: We present a tool for helping surgeons planning trajectories for DBS. Computer-generated trajectories created by our algorithm seem to be safe and planning time can be impressingly decreased.