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

OBJECTIVE: Modern neuronavigation systems lack spatial accuracy during ongo ing surgical procedures because of increasing brain deformation, known as b rain shift. Intraoperative magnetic resonance imaging was used for quantita tive analysis and visualization of this phenomenon. METHODS: For a total of 64 patients, we used a 0.2-T, open-configuration, m agnetic resonance imaging scanner, located in an operating theater, for pre - and intraoperative imaging. The three-dimensional imaging data were align ed using rigid registration methods. The maximal displacements of the brain surface, deep tumor margin, and midline structures were measured. Brain sh ift was observed in two-dimensional image planes using split-screen or over lay techniques, and three-dimensional, color-coded, deformable surface-base d data were computed. In selected cases, intraoperative images were transfe rred to the neuronavigation system to compensate for the effects of brain s hift. RESULTS: The results demonstrated that there was great variability in brain shift, ranging up to 24 mm for cortical displacement and exceeding 3 mm fo r 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 ne uronavigation updating (n = 14) compensated for brain shift, resulting in r eliable navigation with high accuracy. CONCLUSION: Without brain shift compensation, neuronavigation systems canno t be trusted at critical steps of the surgical procedure, e.g., identificat ion of the deep tumor margin. Intraoperative imaging allows not only evalua tion of and compensation for brain shift but also assessment of the quality of mathematical models that attempt to describe and compensate for brain s hift.