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  Investigation of time-dependency of intracranial brain shift and its relation to the extent of tumor removal using intra-operative MRI

Trantakis, C., Tittgemeyer, M., Schneider, J. P., Lindner, D., Strauß, G., & Meixensberger, J. (2003). Investigation of time-dependency of intracranial brain shift and its relation to the extent of tumor removal using intra-operative MRI. Neurological Research, 25(1), 9-12. doi:10.1179/016164103101200923.

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 Creators:
Trantakis, C., Author
Tittgemeyer, Marc1, Author           
Schneider, J. P., Author
Lindner, Dirk, Author
Strauß, Gero, Author
Meixensberger, Jürgen, Author
Affiliations:
1MPI of Cognitive Neuroscience (Leipzig, -2003), The Prior Institutes, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634574              

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Free keywords: Brain shift, Iintra-operative imaging, Biomechanical head model, Vector field
 Abstract: The object of the paper is to investigate intra-operative brainshift and its relation to the extent of tumor removal. Repeated T1w 3D datasets were acquired at different time points intra-operatively (T0; T1; T2...Tx) using a vertical open 0.5T MR scanner in six patients with intracranial tumor. An offline analysis with initial linear registration, intensity adjustment and finally nonlinear registration of the first versus subsequent time points (T0/T1; T0/T2...To/Tx) was performed, yielding a 3D displacement vector field that describes the brainshift. Brainshift was analysed qualitatively and quantitatively. A semi-automatic segmentation technique was used for calculation of the tumor size and the size of tumor remnants. Semi-automatic segmentation was reliable in all but two cases. Segmentation was difficult and unreliable in astrocytomas grade II. The shift basically followed gravity. The major shift reached levels up to 25 mm. Significant shift was observed at the first time point (T0). Intra-operative brainshift can be analysed qualitatively and also captured quantitatively. Neuronavigation that is based on pre-operatively acquired datasets is associated with a significant risk of surgical morbidity at a very early time point. Parallelisation on a workstation cluster may reduce computation time so that information about the displacement can facilitate updated navigation.

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Language(s): eng - English
 Dates: 2003
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 239428
Other: P6883
DOI: 10.1179/016164103101200923
 Degree: -

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Title: Neurological Research
  Other : Neurol. Res.
Source Genre: Journal
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Publ. Info: Guilford, Surry [etc.] : Butterworths [etc.]
Pages: - Volume / Issue: 25 (1) Sequence Number: - Start / End Page: 9 - 12 Identifier: ISSN: 0161-6412
CoNE: https://pure.mpg.de/cone/journals/resource/954925478523