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  2. Medical Image Computing and Computer-Assisted Intervention — MICCAI’98
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Measurement of intraoperative brain surface deformation under a craniotomy

  • Conference paper
  • First Online: 01 January 2006
  • pp 51–62
  • Cite this conference paper
Medical Image Computing and Computer-Assisted Intervention — MICCAI’98 (MICCAI 1998)
Measurement of intraoperative brain surface deformation under a craniotomy
  • Calvin R. Maurer Jr.1,
  • Derek L. G. Hill1,
  • Robert J. Maciunas2,
  • John A. Barwise3,
  • J. Michael Fitzpatrick4 &
  • …
  • Matthew Y. Wang4 

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1496))

Included in the following conference series:

  • International Conference on Medical Image Computing and Computer-Assisted Intervention
  • 6524 Accesses

  • 23 Citations

Abstract

We measured the deformation of the dura and brain surfaces between the time of imaging and the start of surgical resection for 21 patients. All patients underwent intraoperative functional mapping, allowing us to measure brain surface motion at two times that were separated by nearly an hour after opening the dura but before resection. The positions of the dura and brain surfaces were recorded and transformed to the coordinate space of a preoperative MR image using the Acustar neurosurgical navigation system. The mean displacements of the dura and the first and second brain surfaces were 1.2, 4.4, and 5.6 mm, respectively, with corresponding mean volume reductions under the craniotomy of 6, 22, and 29 ml. The maximum displacement was greater than 10 mm in approximately one-third of the patients for the first brain surface measurement and one-half of the patients for the second. In all cases the direction of brain shift corresponds to a “sinking” of the brain intraoperatively, compared with its preoperative position. We observed two patterns of the brain surface deformation field depending on the inclination of the craniotomy with respect to gravity. Separate measurements of brain deformation within the closed cranium caused by changes in patient head orientation with respect to gravity suggested that less than 1 mm of the brain shift recorded intraoperatively could have resulted from the change in patient orientation between the time of imaging and the time of surgery. These results suggest that intraoperative brain deformation is an important source of error that needs to be considered when using neurosurgical navigation systems.

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Author information

Authors and Affiliations

  1. Division of Radiological Sciences and Medical Engineering, King’s College, London, UK

    Calvin R. Maurer Jr. & Derek L. G. Hill

  2. Department of Neurological Surgery, Vanderbilt University, Nashville, Tennessee

    Robert J. Maciunas

  3. Department of Anesthesiology, Vanderbilt University, Nashville, Tennessee

    John A. Barwise

  4. Department of Computer Science, Vanderbilt University, Nashville, Tennessee

    J. Michael Fitzpatrick & Matthew Y. Wang

Authors
  1. Calvin R. Maurer Jr.
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  2. Derek L. G. Hill
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  3. Robert J. Maciunas
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  4. John A. Barwise
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  5. J. Michael Fitzpatrick
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  6. Matthew Y. Wang
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Editor information

William M. Wells Alan Colchester Scott Delp

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© 1998 Springer-Verlag Berlin Heidelberg

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Maurer, C.R., Hill, D.L.G., Maciunas, R.J., Barwise, J.A., Fitzpatrick, J.M., Wang, M.Y. (1998). Measurement of intraoperative brain surface deformation under a craniotomy. In: Wells, W.M., Colchester, A., Delp, S. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI’98. MICCAI 1998. Lecture Notes in Computer Science, vol 1496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056187

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  • DOI: https://doi.org/10.1007/BFb0056187

  • Published: 01 June 2006

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65136-9

  • Online ISBN: 978-3-540-49563-5

  • eBook Packages: Springer Book Archive

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Keywords

  • Surface Point
  • Brain Surface
  • Brain Shift
  • Surgical Navigation System
  • Supine Image

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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