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.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Special Emphasis Panel (ZRG1-SBIB-U (50))
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Tandon, Pushpa
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Brigham and Women's Hospital
United States
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