gms | German Medical Science

65. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC)

Deutsche Gesellschaft für Neurochirurgie (DGNC) e. V.

11. - 14. Mai 2014, Dresden

Use of microelectrode recordings to detect different tumor tissues

Meeting Abstract

  • Falko Wahnschaff - Klinik für Neurochirurgie, Universitätsklinikum Jena, Jena
  • Jan Walter - Klinik für Neurochirurgie, Universitätsklinikum Jena, Jena
  • Susanne Kuhn - Klinik für Neurochirurgie, Ernst-von-Bergmann Klinikum, Potsdam
  • Rupert Reichart - Klinik für Neurochirurgie, Universitätsklinikum Jena, Jena
  • Rolf Kalff - Klinik für Neurochirurgie, Universitätsklinikum Jena, Jena

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. DocP 188

doi: 10.3205/14dgnc582, urn:nbn:de:0183-14dgnc5822

Veröffentlicht: 13. Mai 2014

© 2014 Wahnschaff et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen ( Er darf vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.



Objective: Using microelectrodes for neurophysiological mapping is an essential tool in functional neurosurgery. The purpose of this study is to use the technique of microelectrode recording (MER) in patients, who are diagnosed with brain cancers, to distinguish neuronal field activities between healthy and tumor tissue. Furthermore a classification of various signals, elicited by tumors and the surrounding brain parenchyma should be developed.

Method: Data from 14 patients diagnosed with brain malignancies and undergoing stereotactic biopsy were collected. MER data was acquired using single microelectrode recording stepwise every 0.5mm in a range of 5mm ahead and beyond the tumor with a recording time of 10sec per step. After data recording, stereotactic biopsy was taken exactly at the same points of MER. Biopsies were histological examined and the MER data were analyzed according to spike-dependent and non-spike-dependent features.

Results: MER data analysis showed considerable artifacts. Therefore, only 3 data sets could be used for further analysis. All these records showed similarities between spike activity (ACT) and other non-spike-dependent characteristics. ACT showed a noteworthy segregation between different tissue types with a significant ACT reduction in the tumor area compared to the non-tumor area in one data set. Even the attempt to find a classification algorithm of feature Length Curve (LC) was disappointing due to very variable results. Two other data sets did not show barely any noticeable field activity at all measurement points. Other features like non-dependent spikes were measured only seldom.

Conclusions: To distinguish healthy tissue and tumor tissue the method of microelectrode recording can be seen as a possible diagnostic tool. To minimize confounders in further studies, we promote the use of more microelectrodes; in order to obtain better differentiation and possibly more conclusive end results.