gms | German Medical Science

65th Annual Meeting of the German Society of Neurosurgery (DGNC)

German Society of Neurosurgery (DGNC)

11 - 14 May 2014, Dresden

Article

Send article

Improved localization of implanted subdural electrode contacts on MRI using an elastic image fusion algorithm in invasive EEG recording

Meeting Abstract

Search Medline for

  • Lennart Henning Stieglitz - Universitätsklinik für Neurochirurgie, Universitätsspital Zürich
  • Christian Ayer - Masterstudent, Universität Bern
  • Kaspar Schindler - Universitätsklinik für Neurologie, Inselspital Bern
  • Markus Florian Oertel - Universitätsklinik für Neurochirurgie, Inselspital Bern
  • Roland Wiest - Diagnostische und interventionelle Neuroradiologie, Inselspital Bern
  • Claudio Pollo - Universitätsklinik für Neurochirurgie, Inselspital Bern

Deutsche Gesellschaft für Neurochirurgie. 65. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC). Dresden, 11.-14.05.2014. Düsseldorf: German Medical Science GMS Publishing House; 2014. DocMI.16.09

doi: 10.3205/14dgnc368, urn:nbn:de:0183-14dgnc3687

Published: May 13, 2014

© 2014 Stieglitz et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.

Outline

Text

Objective: Accurate projection of implanted subdural electrode contacts in the invasive recording phase in pharmacoresistant epilepsy cases is highly relevant. Rigid fusion of CT and MRI may display the contacts in the wrong position due to brain shift effects.

Method: To evaluate the ability of an elastic image fusion algorithm to provide a more accurate projection of the electrode contacts on the pre-implantation MRI we performed a retrospective study in five patients. An automated elastic image fusion algorithm (AEF), a guided elastic image fusion algorithm (GEF) and a standard rigid fusion algorithm (RF) were used on preoperative MRI and post-implantation CT scans. Vertical correction of virtual contact positions, total virtual contact shift, correction of midline shift and brain shift due to pneumencephalus were measured.

Results: Both AEF and GEF worked well with all 5 cases. An average midline shift of 1.7mm (SD 1.25) was corrected to 0.4 mm (SD .8) after AEF and to 0mm (SD 0) after GEF. Median virtual distances between contacts and cortical surface were significantly corrected from 2.3mm after RF to 0mm after AEF and GEF (p<.001). A mean total relative correction of 3.11mm (SD 1.85) after AEF and 3.0mm (SD 1.77) after GEF was achieved. The tested version of GEF did not achieve a satisfying virtual correction of pneumencephalus.

Conclusions: The technique provides a clear improvement in fusion of pre- and post-implantation scans, though the accuracy is difficult to evaluate.