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Simulation of Corticospinal Tract Displacement in Patients with Brain Tumors

Institution:
Surgical Planning Laboratory, Departments of Radiology and Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Publisher:
Med Image Comput Comput Assist Interv. MICCAI 2000
Publication Date:
Oct-2000
Volume Number:
3
Pages:
9-18
Citation:
Int Conf Med Image Comput Comput Assist Interv. 2000 Oct;3:9-18.
Appears in Collections:
SPL, SLICER
Sponsors:
R01 CA4662708
P01 CA067165/CA/NCI NIH HHS/United States
P01 AG004953/AG/NIA NIH HHS/United States
NSF BES 9631710
Darpa F41624-96-2-0001
Whittaker Foundation RG-96-0440
DFG NA 359/1-1
Generated Citation:
Kaus M.R., Nabavi A., Mamisch C.T., Wells III W.M., Jolesz F.A., Kikinis R. Simulation of Corticospinal Tract Displacement in Patients with Brain Tumors. Int Conf Med Image Comput Comput Assist Interv. 2000 Oct;3:9-18.
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The spatial relationship between the corticospinal tracts and a brain tumor is important for planning the surgical strategy. Although the white matter tracts can be manually outlined from structural MRI this is time consuming and impractical. To enhance the spatial understanding of the distorted pathology we have established a method to retrieve this structural information automatically by registration of a standardized normal brain atlas to the individual pathologic anatomy of brain tumor patients. The skin and the brain were segmented in the patient MRI volume. Subsequently a deformable volumetric atlas of a single normal subject was registered to the patient brain using affine and non-linear registration techniques. The estimated spatial correspondence between atlas and patient brain was used to warp the corticospinal tracts from the atlas onto the patient. The accuracy of the method was evaluated in 5 patients with extrinsic tumors of different histopathology and location by comparing selected anatomical landmark structures from the projected atlas to their manually segmented counterpart in the patient. Our method enables the visualization of complex anatomical information with minimal user interaction for routine surgical planning that would otherwise demand the acquisition of additional imaging modalities.

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