DTI-Based White Matter Fiber Analysis and Visualization

Jun Zhang, Ph.D.Laboratory for Computational Medical Imaging & Data Analysis

Laboratory for High Performance Scientific Computing and Computer SimulationComputer Science Department

University Of KentuckyLexington, KY 40506

Outline

• Introduction - DTI and AD• Methods• Experimental results• Discussion and Conclusion

Isotropic/Anisotropic Diffusion

Diffusion Tensor Imaging (DTI)

1: (0.707, 0.707, 0.000)2: (-0.707, 0.707, 0.000)3: (0.000, 0.707, 0.707)4: (0.000, -0.707, 0.707)5: (0.707, 0.000, 0.707)6: (-0.707, 0.000, 0.707)

b0 and the six gradient applied images

The six gradients in the image acquisition may be:

b0 means the gradient:

(0.000, 0.000, 0.000)

Diffusion Tensor – Mathematical Model and Derived Diffusivity Measures

zzzyzx

yzyyyx

xzxyxx

ttttttttt

T

23

22

21

23

22

21 )()()(

23

FA

3)( 321

MD

Measures of the diffusivity:

T V = T V = λλVV

Det(T – Det(T – λλI) = 0I) = 0

(T – (T – λλI) V = 0I) V = 0

Aging and Diffusions in the White Matter

Linear (Linear (λλ1 » 1 » λλ2 ≈2 ≈ λ λ3)3) Planar (Planar (λλ1 ≈1 ≈ λ λ2 »2 » λ λ3)3) Spherical (Spherical (λλ1 ≈1 ≈ λ λ2 ≈2 ≈ λ λ3)3)

It is widely believed that degradations of axons and oligodendrocytes result in value of fractional anisotropy (FA) reductions in neuropathological studies of AD.

Existing Approaches – Voxel Based Morphormetry (VBM)

Rose et al 2006

Cons: No geometric spatial information is considered.

Existing Approaches – Region of Interest (ROI)

Ying Zhang et al 2007

Cons: Only one or more intersections of fiber bundles are sampled. Subjective and conflict conclusions, Poor reproducibility, inconsistentSubjective and conflict conclusions, Poor reproducibility, inconsistent

Objectives

• to develop effective strategies to inspect possible tissue damages caused by regional micro structural white matter changes along the major bundles for both strong and hardly reconstructed fiber tract bundles

• to interactively visualize hidden regional statistical features along neural pathways in vivo for a better understanding of the progression of certain brain diseases

Proposed Methods• DTI tractography – to approximate the

volumetric neuronal pathways• Geodesic Distance Mapping - to re-parameterize

fibers to establish point to point correspondences among fibers as well as subjects

• Fiber tract bundle mask - to measure thin fiber bundles in group analysis

• Isonode visualization method - to render explored regional statistical features along the fiber pathways

The Right Cingulum Fiber Bundle Mask

The tracking target ROI plane is in blue – All fibers passing through this plane were kept.

FA

Eigenvectors

Individual Tensor Images Averaged Tensor Image

Fiber Tracking

Geodesics and Geodesic Distance

• Geodesics – To obtain a distance between two points of a connected Riemannian manifold, we take the minimum length among the smooth curves joining these points. The curves realizing this minimum for any two points of the manifold are called geodesics.

The length is obtained as by integrating this value along the curve.

Illustration of Attributes Bundling

Starting point plane

a group of isonodes Isonodes (yellow) Fiber tracts (red)

Experiments - Subjects

• 17 normal controls• 17 age matched amnestic mild cognitive

impairment (MCI) patients• No significant difference exists which will

invalidate the experimental results• 1.5T Siemens Sonata scanner• 256*256*48 and 0.9*0.9*2.75mm3

• Non-linearly registered all subjects’ b0 images

Experiments – Fiber Bundles• The left major cingulum bundle• The right major cingulum bundle• The GCC bundle (4 controls and 2 MCIs are

excluded since their extracted short fiber tracts in the GCC bundle experiment)

The GCC bundle in different views

Left Cingulum - Regional Structural White Matter Changes (FA)

-100 0 100 200 3000.2

0.3

0.4

0.5

0.6

0.7

Geodesic distance

F A

CONTROLMCI

-100 0 100 200 3000

0.1

0.5

1

Geodesic distance

p va

lue

FA alteration (yellow)

Seed points (blue)

Left cingulum

No white matter alteration is found for the right cingulum.

Left Cingulum - Voxels Exhibiting FA Degradations in MCI

A group of 17 connected voxels (yellow) exhibit significantly different FA

The GCC Bundle - Averaged FA and MD Values of the Entire Volumetric Bundle

GCC bundle Control MCI p-value df

FA 0.56 ±0.05 0.51±0.05 0.004 26

MD 844±62 921±88 0.006 26

Mean (±SD) values for FA and MD measures for computed GCC pathways for MCI and normal control groups. The unit of MD is (106 mm2/sec).

Scatter PlotsScatter Plots

The GCC Bundle - Regional Structural White Matter Changes (FA)

The GCC Bundle - Regional Structural White Matter Changes (MD)

Discussion

• Dependence on fiber tracking;

• Evaluating common parts (shortest) of fiber bundles;

• Relatively compact fiber bundle;

• Unclear – Structural connectivity and VBM;

Conclusion

• A novel approach to measure regional diffusion property alterations along brain structural connectivity;

• Experiment results show that this new analysis method may provide a more sensitive approach to evaluating the integrity of neural pathways human brain.

Acknowledgement• Collaborators• Stephen Rose, University of Queensland• Ning Kang, Ning Cao, Xuwei Liang, Qi Zhuang,

UK Computer Science• Charles Smith, Peter Hardy, Brian Gold, UK

Medical School

Thank you!