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 14 Feb 2007 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 We Care • Better visualization would –Assist research –Interactive 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” fMRI • Functional Magnetic Res Imaging • Correlate activity • Suggests gray matter connections 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 Query Interface Query Interface – Partial Blowup Query Interface – Partial Blowup Query Interface – Partial Blowup Query Interface – Partial Blowup Acqusition DTI & fMRI Subject • Neurologically Normal • Male • Human • 35 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 Precomputation Fractional Anisotropy (FA) • Diffusion orientation ratio 0 = spherical = gray matter 0.5 = linear or planar ellipsoid 1 = 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 Precomputation • Statistical properties • Length • Avg FA • Avg Curvature • Tractography Algorithm Implementation 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 Sequential Dynamic Queries All 13,000 Pathways Length > 4 cm Through VOI 1 Through VOI 1 AND (2 or 3) Volumes of Interest Surface-constrained VOI on Cortical Surface Same VOI, Smoothed Surface Validation of Known Pathways Occipital Lobe Occipital to Right Frontal Lobe Occipital to Left Frontal Lobe Occipital to R & L, w/Context Forming Hypotheses Known and Unknown Paths Algorithm Comparison STT – Streamlines Tracking Techniques Vs TEND – Tensor Deflection STT (blue) vs TEND (yellow) Exploration of Connections Between Functional Areas fMRI Areas Colormapped VOI Placement Surface Removed Paths Visible VOI Adjusted Different Paths Evaluation • Types of functions –Validation of known pathways –Hypothesis generation • Time to explore – 10 minutes for significant exploration • Speed – Interactive rates • Interface – Interactive queries Alternative Methods Alternative Methods • Diffusion tensor visualization White Matter Algorithms • Streamlines Tracking Techniques • Fiber Assg thru Cont Tracking • Tensor-deflection Filters • Length • Average linear anisotropy • Regions of interest 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 Question • Is there any reason for tools such as this to be validated? Question • If validated this early on, wouldn’t every change pretty much negate the validation? Question • Should there be some kind of benchmark to use to measure these applications against?
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