gms | German Medical Science

68th Annual Meeting of the German Society of Neurosurgery (DGNC)
7th Joint Meeting with the British Neurosurgical Society (SBNS)

German Society of Neurosurgery (DGNC)

14 - 17 May 2017, Magdeburg

Using templates for the identification of language related areas in tumor patients based on resting state fMRI

Meeting Abstract

  • Christian Ott - Regensburg, Deutschland
  • Markus Goldhacker - Regensburg, Deutschland
  • Katharina Rosengarth - Regensburg, Deutschland
  • Julius Höhne - Regensburg, Deutschland
  • Elmar Lang - Regensburg, Deutschland
  • Mark Greenlee - Regensburg, Deutschland
  • Alexander Brawanski - Regensburg, Deutschland

Deutsche Gesellschaft für Neurochirurgie. Society of British Neurological Surgeons. 68. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), 7. Joint Meeting mit der Society of British Neurological Surgeons (SBNS). Magdeburg, 14.-17.05.2017. Düsseldorf: German Medical Science GMS Publishing House; 2017. DocMi.23.02

doi: 10.3205/17dgnc522, urn:nbn:de:0183-17dgnc5222

Published: June 9, 2017

© 2017 Ott et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at



Objective: In contrast to the task-based-fMRI there is no need for an active participation of the patient in resting-state fMRI (rs-fMRI). The major question of our study is, whether it is possible to identify language related areas in patients suffering from a lesion close to those areas using rs-fMRI and a predefined template of the language related resting state network in the entirely absence of any patient participation

Methods: 15 patients suffering from lesions close to language related areas were included. All of the patients underwent rs-fMRI, which was analyzed by independent component analysis (ICA). ICA was performed in multiple runs for each patient. Correlation analyses between the predefined template of the language related resting state network and resting state components were conducted. For each patient the component - out of all ICA runs - highest correlating with the predefined template was selected as a candidate for representing language related areas.

Results: Preliminary results showed that the maximally correlating component of the ICAs of the rs-fMRI with the template was promising concerning the activation surrounding tumor areas and their appearance as being language related.

Conclusion: In patients who are not able to actively participate due to neurological impairment or sedation rs-fMRI could be an alternative tool for the identification of eloquent cortex. The major challenge is the identification of the correct component and thereby the correct network. In this study we could show that it is possible to identify language related areas in tumor patients using rs-fMRI solely.