• Neurosurgery · Nov 2000

    Quantification of, visualization of, and compensation for brain shift using intraoperative magnetic resonance imaging.

    • C Nimsky, O Ganslandt, S Cerny, P Hastreiter, G Greiner, and R Fahlbusch.
    • Department of Neurosurgery, University Erlangen-Nürnberg, Erlangen, Germany. nimsky@nch.imed.uni-erlangen.de
    • Neurosurgery. 2000 Nov 1;47(5):1070-9; discussion 1079-80.

    ObjectiveModern neuronavigation systems lack spatial accuracy during ongoing surgical procedures because of increasing brain deformation, known as brain shift. Intraoperative magnetic resonance imaging was used for quantitative analysis and visualization of this phenomenon.MethodsFor a total of 64 patients, we used a 0.2-T, open-configuration, magnetic resonance imaging scanner, located in an operating theater, for pre- and intraoperative imaging. The three-dimensional imaging data were aligned using rigid registration methods. The maximal displacements of the brain surface, deep tumor margin, and midline structures were measured. Brain shift was observed in two-dimensional image planes using split-screen or overlay techniques, and three-dimensional, color-coded, deformable surface-based data were computed. In selected cases, intraoperative images were transferred to the neuronavigation system to compensate for the effects of brain shift.ResultsThe results demonstrated that there was great variability in brain shift, ranging up to 24 mm for cortical displacement and exceeding 3 mm for the deep tumor margin in 66% of all cases. Brain shift was influenced by tissue characteristics, intraoperative patient positioning, opening of the ventricular system, craniotomy size, and resected volume. Intraoperative neuronavigation updating (n = 14) compensated for brain shift, resulting in reliable navigation with high accuracy.ConclusionWithout brain shift compensation, neuronavigation systems cannot be trusted at critical steps of the surgical procedure, e.g., identification of the deep tumor margin. Intraoperative imaging allows not only evaluation of and compensation for brain shift but also assessment of the quality of mathematical models that attempt to describe and compensate for brain shift.

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