Intraoperatively updated neuroimaging using brain modeling and sparse data

Image-guided neurosurgery incorporating preoperatively obtained imaging information is subject to spatial error resulting from intraoperative brain displacement and deformation. A strategy to update preoperative imaging using readily available intraoperative information has been developed and implem...

Full description

Saved in:
Bibliographic Details
Published inNeurosurgery Vol. 45; no. 5; p. 1199
Main Authors Roberts, D W, Miga, M I, Hartov, A, Eisner, S, Lemery, J M, Kennedy, F E, Paulsen, K D
Format Journal Article
LanguageEnglish
Published United States 01.11.1999
Subjects
Online AccessGet more information
ISSN0148-396X
DOI10.1097/00006123-199911000-00037

Cover

Loading…
More Information
Summary:Image-guided neurosurgery incorporating preoperatively obtained imaging information is subject to spatial error resulting from intraoperative brain displacement and deformation. A strategy to update preoperative imaging using readily available intraoperative information has been developed and implemented. Preoperative magnetic resonance imaging is used to generate a patient-specific three-dimensional finite element model of the brain by which deformation resulting from multiple surgical processes may be simulated. Sparse imaging data obtained subsequently, such as from digital cameras or ultrasound, are then used to prescribe the displacement of selected points within the model. Based on the model, interpolation to the resolution of preoperative imaging may then be performed. The algorithms for generation of the finite element model and for its subsequent deformation were successfully validated using a pig brain model. In these experiments, the method recovered 84% of the intraoperative shift resulting from surgically induced tissue motion. Preliminary clinical application in the operating room has demonstrated feasibility. A strategy by which intraoperative brain deformation may be accounted for has been developed, validated in an animal model, and demonstrated clinically.
ISSN:0148-396X
DOI:10.1097/00006123-199911000-00037