OBJECTIVE: Modern 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. METHODS: For 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. RESULTS: The 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. CONCLUSION: Without 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.
OBJECTIVE: Modern 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. METHODS: For 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. RESULTS: The 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. CONCLUSION: Without 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.
Authors: Michael I Miga; Tuhin K Sinha; David M Cash; Robert L Galloway; Robert J Weil Journal: IEEE Trans Med Imaging Date: 2003-08 Impact factor: 10.048
Authors: David M Cash; Tuhin K Sinha; William C Chapman; Hiromi Terawaki; Benoit M Dawant; Robert L Galloway; Michael I Miga Journal: Med Phys Date: 2003-07 Impact factor: 4.071
Authors: Alex Hartov; Keith Paulsen; Songbai Ji; Kathryn Fontaine; Marie-Laure Furon; Andrea Borsic; David Roberts Journal: Med Phys Date: 2010-05 Impact factor: 4.071
Authors: Kay Sun; Thomas S Pheiffer; Amber L Simpson; Jared A Weis; Reid C Thompson; Michael I Miga Journal: IEEE J Transl Eng Health Med Date: 2014-04-30 Impact factor: 3.316