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

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 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

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 TechniquesVs

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?