gms | German Medical Science

59. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC)
3. Joint Meeting mit der Italienischen Gesellschaft für Neurochirurgie (SINch)

Deutsche Gesellschaft für Neurochirurgie (DGNC) e. V.

01. - 04.06.2008, Würzburg

Integration of functional biosignals of the facial nerve into a navigation concept of the lateral skull base

Integration von funktionellen Biosignalen des Nervus facialis in ein Navigationskonzept der Laterobasis

Meeting Abstract

  • corresponding author C. Trantakis - Klinik und Poliklinik für Neurochirurgie, Universität leipzig
  • G. Strauss - Klinik und Poliklinik für HNO-Heilkunde/Plastische Operationen, Universität Leipzig
  • T. Lüth - Lehrstuhl für Mikrotechnik und Medizingerätetechnik, Technische Universität München
  • J. Meixensberger - Klinik und Poliklinik für Neurochirurgie, Universität leipzig

Deutsche Gesellschaft für Neurochirurgie. Società Italiana di Neurochirurgia. 59. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie e.V. (DGNC), 3. Joint Meeting mit der Italienischen Gesellschaft für Neurochirurgie (SINch). Würzburg, 01.-04.06.2008. Düsseldorf: German Medical Science GMS Publishing House; 2008. DocMI.02.06

Die elektronische Version dieses Artikels ist vollständig und ist verfügbar unter: http://www.egms.de/de/meetings/dgnc2008/08dgnc225.shtml

Veröffentlicht: 30. Mai 2008

© 2008 Trantakis et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.de). Er darf vervielf&aauml;ltigt, verbreitet und &oauml;ffentlich zug&aauml;nglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.


Gliederung

Text

Objective: EMG signals of the facial nerve were integrated into a navigation model of the lateral skull base. A 3D-model of the facial nerve course was created using position-controlled nerve stimulation. The data were registered with a 3D x-ray dataset of a digital volume tomography (DVT). The accuracy of the x-ray based model and the EMG-derived model was investigated.

Methods: EMG signals were derived from a facial nerve phantom. The signals were arranged in realtime. The position of the nerve was visualized as a sphere representing the probable space in which the facial nerve takes course. A phantom of the facial nerve was built using an electro conductive silver wire mounted on a trackable raster plate and a DVT dataset was obtained. A navigation system (TUM Panel ENT, MiMed) captured both the position of the plate and the position of the tracked tip of the probe. And a 3D course of the simulated facial nerve was generated. This 3-D model was integrated into DVT- based planning data. The deviation between the real wire position and the spheres was measured.

Results:

Tracking of the stimulation probe: The position of the tip of the probe could be tracked with high precision and a 3D course of the facial nerve was generated.

Tracking algorithm: Stimulation occurred at 12 points along the course of the wire. Every point was stimulated 12 times resulting in data consisting of 144 measurements.

Convergence of the real wire course and the resulting 3D model: At 12 points the deviation between the course of the wire and the 3D-model was measured. The mean deviation was 1.585 mm.

Conclusions: The phantom allows the simulation of a facial nerve and the conduction of EMG-like signals. Under the assumption that the tip of the probe represents the possible area of localisation of the simulated facial nerve, a 3D model could be made. The amount of the volume obtained depends on the amperage of stimulation. The 3D dataset and the DVT based model were visualized on a common coordinate system. 3D integration of EMG signals in facial nerve surgery may enhance navigation concepts in the future. The study could show a reliable concept of creating a 3D model of a phantom of a facial nerve based on stimulation and derived EMG like signals.