Intraoperative imaging has several advantages over conventional images guidance methods which utilize pre-operative acquired images. Using frequent image updates, one can compensate for changes in position of the brain. The ability to visualize surgical and lesion margins permits resections to be more complete with less damage to adjacent normal. Interactive intra-operative MRI guidance allows to accurately localize and target during neurosurgery, to optimize surgical approaches that avoid critical structures and to decrease vulnerability of surrounding normal tissues. Consequently, image-guided therapy could improve critical outcomes and reduce complication rages while being more cost-effective. In addition intra-operative MRI may result in new procedures that cannot be conceived outside of this operating environment. The overall goal of this Project is to develop an integrated system of pre and intraoperative image acquisition, on-line image processing and intraoperative display which allows the utilization of all the accessible and preoperative information for image-guided neurosurgery. The subject of this Project is the integration of the software and hardware components of intraoperative MRI, navigational tools, multi-modality imaging and intraoperative display into a single powerful image guidance system. The goal is to provide all the accessible image based information to assure to assure that intraoperative trajectory optimization and navigation can be performed in a user friendly environment.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
3P01CA067165-05S1
Application #
6500737
Study Section
Project Start
2001-05-01
Project End
2002-04-30
Budget Start
Budget End
Support Year
5
Fiscal Year
2001
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
071723621
City
Boston
State
MA
Country
United States
Zip Code
02115
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Penzkofer, Tobias; Tempany-Afdhal, Clare M (2014) Prostate cancer detection and diagnosis: the role of MR and its comparison with other diagnostic modalities--a radiologist's perspective. NMR Biomed 27:3-15
Jayender, Jagadaeesan; Chikarmane, Sona; Jolesz, Ferenc A et al. (2014) Automatic segmentation of invasive breast carcinomas from dynamic contrast-enhanced MRI using time series analysis. J Magn Reson Imaging 40:467-75

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