Neurosurgical navigation systems have reduced the risk of complications from surgery and have allowed surgeons to remove tumors that were once considered inoperable. However, many techniques used by neurosurgical navigation systems to align pre- and intra-operative images are inaccurate when tissue deformations occur. Deformations commonly arise from tumor resection, gravitational effects on the organ, and the use of hyperosmotic drugs. Deformable intra-operative image registration remains a significant challenge for neurosurgical guidance. We proposed two new methods for registering pre-operative MRI with intra-operative 3D ultrasound data, during craniotomies for brain tumor resection. These methods will be delivered as part of an extensible """"""""'NeuralNav""""""""'toolkit that provides a common API for fetching tracker data and intra-operative images from commercial (VectorVision by BrainLAB) and research (Image-Guided Surgical Toolkit, IGSTK by Georgetown Univ) surgical guidance systems. Development and validation of methods and efforts will be conducted in collaboration with top neurosurgeons, the developers of IGSTK, and BrainLAB.

Public Health Relevance

This project aims to construct registration algorithms for neurosurgical navigation and deliver them to the re- search and commercial community in an open source toolkit. These capabilities may eventually lead to improved outcomes in tumor resection.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA138419-04
Application #
8311809
Study Section
Special Emphasis Panel (ZRG1-SBIB-U (50))
Program Officer
Tandon, Pushpa
Project Start
2009-09-29
Project End
2014-07-31
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
4
Fiscal Year
2012
Total Cost
$359,959
Indirect Cost
$91,204
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Toews, Matthew; Wells, William M (2018) Phantomless Auto-Calibration and Online Calibration Assessment for a Tracked Freehand 2-D Ultrasound Probe. IEEE Trans Med Imaging 37:262-272
Sastry, Rahul; Bi, Wenya Linda; Pieper, Steve et al. (2017) Applications of Ultrasound in the Resection of Brain Tumors. J Neuroimaging 27:5-15
Niethammer, Marc; Pohl, Kilian M; Janoos, Firdaus et al. (2017) ACTIVE MEAN FIELDS FOR PROBABILISTIC IMAGE SEGMENTATION: CONNECTIONS WITH CHAN-VESE AND RUDIN-OSHER-FATEMI MODELS. SIAM J Imaging Sci 10:1069-1103
Bersvendsen, Jørn; Toews, Matthew; Danudibroto, Adriyana et al. (2016) Robust Spatio-Temporal Registration of 4D Cardiac Ultrasound Sequences. Proc SPIE Int Soc Opt Eng 9790:
Pace, Danielle F; Aylward, Stephen R; Niethammer, Marc (2013) A locally adaptive regularization based on anisotropic diffusion for deformable image registration of sliding organs. IEEE Trans Med Imaging 32:2114-26
Risholm, Petter; Janoos, Firdaus; Norton, Isaiah et al. (2013) Bayesian characterization of uncertainty in intra-subject non-rigid registration. Med Image Anal 17:538-55
Kwitt, R; Vasconcelos, N; Razzaque, S et al. (2013) Localizing target structures in ultrasound video - a phantom study. Med Image Anal 17:712-22
Kwitt, Roland; Pace, Danielle; Niethammer, Marc et al. (2013) Studying cerebral vasculature using structure proximity and graph kernels. Med Image Comput Comput Assist Interv 16:534-41
Gessner, Ryan C; Aylward, Stephen R; Dayton, Paul A (2012) Mapping microvasculature with acoustic angiography yields quantifiable differences between healthy and tumor-bearing tissue volumes in a rodent model. Radiology 264:733-40
Kwitt, Roland; Vasconcelos, Nuno; Razzaque, Sharif et al. (2012) Recognition in ultrasound videos: where am I? Med Image Comput Comput Assist Interv 15:83-90

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