exploring connectivity of the brain’s white matter with dynamic queries
DESCRIPTION
Exploring Connectivity of the Brain’s White Matter with Dynamic Queries. Anthony Sherbondy, David Akers, Rachel Mackenzie, Robert Dougherty, and Brian Wandell. IEEE Transactions on Visualization and Computer Graphics, V11, No 4, July/August 2005. Presented by: Eugene (Austin) Stoudenmire - PowerPoint PPT PresentationTRANSCRIPT
Exploring Connectivity of the Brain’s White Matter with Dynamic Queries
Presented by:Eugene (Austin) Stoudenmire
14 Feb 2007
Anthony Sherbondy, David Akers, Rachel Mackenzie, Robert Dougherty, and Brian Wandell
IEEE Transactions on Visualization and Computer Graphics, V11, No 4, July/August 2005
Problem• New technology emerged
–Diffusion Tensor Imaging (DTI)–White matter connections, i.e. fiber
tracts, can now be measured• Need to take advantage of it• Requires better visualization
Approach• Combine types of data
–Anatomical – White – DTI–Functional – Gray – fMRI
• Functional Magnetic Resonance Imaging• Precompute• Query Interface
–Pictoral–Labeled–Ranges
DTI• Diffusion Tensor Imaging• New Technology• Measures white matter pathways• Estimates water molecule diffusion
–Water diffuses lengthwise along axons–Diffusion direction nerve fiber
orientation
One Method of DTI Visualization
• MR Tractography• Traces principle direction of diffusion• Connects points into fiber tracts• Fiber tracts = pathways• Anatomical connections between
endpoints of the pathways are implied• Therefore, implied white matter structure
These Pathways• Not individual nerves• Not Bundles• But something• Abstract, white matter route
“possibilities”
The Combination• Take the MR Tractography data• Precompute paths, statistical properties• Interactive manipulation
– Regions of interest – Box / Ellipsoid– Path properties – Length / Curvature
• Combine with fMRI– Search for anatomical paths that might
connect functionally-defined regions• Saves time over existing approaches
DTI• Eight 3-minute whole brain scans
–Averaged–38 axial slices–2 x 2 x 3 mm voxels
• 8-minute high res anat images–1 x 1 x 1 mm voxel
• Coregistered• DTI resampled to 2 mm
fMRI• 21-30 obliquely oriented slices• 2 x 2 x 3 mm voxel• Registered with anatomy• Mapped to cortical surface mesh
Fractional Anisotropy (FA)• Diffusion orientation ratio
0 = spherical = gray matter0.5 = linear or planar ellipsoid1 = very linear
• Uses–Algorithm termination criteria–Queries–Navigational aid
Approaches• Typical
–Interactively trace pathways• Authors’
–Precompute pathways–Over entire white matter–Then let software “prune”
Cortical Surface• Classified white matter • Semi-manually – neuroscientist• Marching-Cubes -> t-mesh• Smoothed• Kept both• 230,000 vertices
Path Rendering• Lines vs streamtubes (for speed)• Pathways – luminance offset• Groups of pathways – hue
–User defined hue–Virtual staining
• Queries modified – stains remain
Hardware/Software• Visualization C++• ToolKit (VTK)• RAPID
–Fast VOI / Path Intersection Comp–80K-120K paths/sec (w/SGI RE)–Allowed 3-8
• 510MB for 26K paths @ 20KB/path• 160MB for cortical meshes
Evaluation• Types of functions
–Validation of known pathways–Hypothesis generation
• Time to explore – 10 minutes for significant exploration
• Speed – Interactive rates• Interface – Interactive queries
White Matter Algorithms
• Streamlines Tracking Techniques• Fiber Assg thru Cont Tracking• Tensor-deflection
Conclusion• Multiple data types (DTI & fMRI)• New visualization interface• Interactive queries• Hypothesis generation & testing
Next Steps
• Real work• Multiple subjects• Normal to abnormal• Acquisition technology• Path tracing algorithms