Transcript DTI-Based White Matter Fiber Analysis and Visualization

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 Simulation
Computer Science Department
University Of Kentucky
Lexington, KY 40506
Outline
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Introduction - DTI and AD
Methods
Experimental results
Discussion and Conclusion
Isotropic/Anisotropic Diffusion
Diffusion Tensor Imaging (DTI)
The six gradients in the
image acquisition may be:
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 means the gradient:
(0.000, 0.000, 0.000)
b0 and the six gradient applied images
Diffusion Tensor – Mathematical Model
and Derived Diffusivity Measures
 t xx t xy t xz 


T   t yx t yy t yz 
t

t
t
 zx zy zz 
T V = λV
Det(T – λI) = 0
(T – λI) V = 0
Measures of the diffusivity:
FA 
3
2
(1   ) 2  (2   ) 2  (3   ) 2
12  22  32
(1  2  3 )
MD 
3
Aging and Diffusions in the White Matter
Linear (λ1 » λ2 ≈ λ3)
Planar (λ1 ≈ λ2 » λ3)
Spherical (λ1 ≈ λ2 ≈ λ3)
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, 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
Individual Tensor Images
Averaged Tensor Image
FA
Eigenvectors
Fiber Tracking
The tracking target ROI plane is in blue – All fibers passing through this
plane were kept.
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
a group of isonodes
Starting point plane
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)
FA alteration (yellow)
Left cingulum
Seed points (blue)
1
0.7
CONTROL
MCI
0.6
FA
p value
0.5
0.5
0.4
0.3
0.1
0.2
-100
0
100
200
Geodesic distance
300
0
-100
0
100
Geodesic distance
No white matter alteration is found for the right cingulum.
200
300
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
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).
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
Scatter 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!