DTI-based Virtual Reality System for Neurosurgery

The relationship between tumor mass and peritumoral structures including peritumoral edema is important for planning surgical trajectory and crucial for diagnosis, tumor excision, and post-surgical outcome. The recent development of diffusion tensor MRI has shown its feasibility in grading tumor, monitoring therapeutic effects, and post-surgery outcome. To visualize the tumor mass and the peritumoral structure, a 3D virtual reality environment was developed. Neural tractography and peritumoral anatomy were integrated in this interaction VR system. Using a 3D controller, suitable surgical trajectory can be defined by manipulating the tumor mass, peritumoral microstructure, and brain tissues before neurosurgery. Post-surgery evaluation showed that this system was useful to design pre-surgerical plan and optimize therapeutic outcome.

[1]  Benjamin D. Greenberg,et al.  An immersive virtual environment for DT-MRI volume visualization applications: a case study , 2001, Proceedings Visualization, 2001. VIS '01..

[2]  P. V. van Zijl,et al.  Three‐dimensional tracking of axonal projections in the brain by magnetic resonance imaging , 1999, Annals of neurology.

[3]  C. Meyer,et al.  Evaluation of the functional diffusion map as an early biomarker of time-to-progression and overall survival in high-grade glioma. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Glyn Johnson,et al.  Diffusion-tensor MR imaging of intracranial neoplasia and associated peritumoral edema: introduction of the tumor infiltration index. , 2004, Radiology.

[5]  M E Bastin,et al.  The use of diffusion tensor imaging in quantifying the effect of dexamethasone on brain tumours. , 1999, Neuroreport.

[6]  M. Horsfield,et al.  Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging , 1999, Magnetic resonance in medicine.

[7]  M. Tarr,et al.  Virtual reality in behavioral neuroscience and beyond , 2002, Nature Neuroscience.

[8]  Yuriko Suzuki,et al.  Air jet driven force feedback in virtual reality , 2005, IEEE Computer Graphics and Applications.

[9]  Michal Neeman,et al.  A simple method for obtaining cross‐term‐free images for diffusion anisotropy studies in NMR microimaging , 1991, Magnetic resonance in medicine.

[10]  Susumu Mori,et al.  Fiber tracking: principles and strategies – a technical review , 2002, NMR in biomedicine.