gms | German Medical Science

73. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC)
Joint Meeting mit der Griechischen Gesellschaft für Neurochirurgie

Deutsche Gesellschaft für Neurochirurgie (DGNC) e. V.

29.05. - 01.06.2022, Köln

Determining language function lateralisation using clustered-sparse acquisition fMRI

Bestimmung der Lateralisierung von Sprachfunktionen durch clustered-sparse fMRT

Meeting Abstract

  • presenting/speaker Phillip Keil - Universitätsklinikum Köln, Zentrum für Neurochirurgie, Köln, Deutschland
  • Charlotte Nettekoven - Universitätsklinikum Köln, Zentrum für Neurochirurgie, Köln, Deutschland
  • Kristina Jonas - Universität zu Köln, Humanwissenschaftliche Fakultät, Department Heilpädagogik und Rehabilitation, Köln, Deutschland
  • Thorsten Lichtenstein - Universitätsklinikum Köln, Institut für Diagnostische und Interventionelle Radiologie, Köln, Deutschland
  • Roland Goldbrunner - Universitätsklinikum Köln, Zentrum für Neurochirurgie, Köln, Deutschland
  • Carolin Weiß-Lucas - Universitätsklinikum Köln, Zentrum für Neurochirurgie, Köln, Deutschland

Deutsche Gesellschaft für Neurochirurgie. 73. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Griechischen Gesellschaft für Neurochirurgie. Köln, 29.05.-01.06.2022. Düsseldorf: German Medical Science GMS Publishing House; 2022. DocP162

doi: 10.3205/22dgnc475, urn:nbn:de:0183-22dgnc4753

Veröffentlicht: 25. Mai 2022

© 2022 Keil et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.


Gliederung

Text

Objective: Detecting the individual hemispheric language lateralization is of great interest, e.g., for planning tumor surgery. Functional MRI (fMRI) offers a non-invasive alternative to the WADA-test. However, conventional fMRI acquisition methods (i.e., continuous sampling) suffer from the acoustic contamination by scanner noise. In this study, we set out to compare the utility of two different fMRI tasks to determine language lateralization, using a clustered-sparse acquisition method. This novel acquisition method provides silence in the scanner during task execution, thus minimizing acoustic contamination and movement artifacts, whilst preserving a reasonable scanning session length.

Methods: 15 healthy subjects (m=4, mean age=30 yrs) underwent fMRI (Philips Ingenia 3T) consisting of (1 – PN) a picture naming task and (2 – SD) a semantic decision task (i.e., selecting a semantically related picture out of three options by button-press after auditory sentence presentation). Full brain volumes were acquired in a clustered-sparse scheme leaving a silent epoch for task conduction between groupings of three scans (TR: 1.2s, TE: 30ms, FA: 64°, 36 slices, voxel size: 3mm isotropic), lasting for ~7.5 min. Data were analyzed using SPM12 and Matlab. JuBrain Anatomy Toolbox was used to delineate regions of interest (ROI): angular gyrus (AG), superior temporal gyrus (STG) and inferior frontal gyrus (IFG). The SPM script “AveLI” was used to compute laterality indices (LI). LI values determined lateralization, using a cut-off of +/- 20%.

Results: Overall, left lateralization was higher for the SD task compared to PN (p<0.01). Using the IFG and AG ROIs from the SD task, eight subjects were categorized as left dominant (LD; mean LI: 45% ±14%), five as ambiguous (mean LI: 2% ± 10%) and two as right dominant (RD; mean LI: -34% ± 16%). PN in contrast showed five subjects as LD (mean LI: 41% ± 20%), five as ambiguous (mean LI: 8% ± 8%), and six as RD (mean LI: -48% ± 18%). Limiting the analysis to the STG ROI, only a minority of subjects were categorized as LD (SD: n=6; PN: n=2).

Conclusion: Clustered-sparse fMRI using a SD task with focus on the IFG and AG ROIs performed closest to literature with regard to detecting hemispheric language dominance. It might therefore offer a valuable non-invasive tool for determining language lateralization, well suited for brain tumour patients due to the velocity of scan acquisition and the relative simplicity of the task.