1

Detecting Subtle Changes in Structure

Chris Rorden– Diffusion Tensor Imaging

Measuring white matter integrityTractography and analysis.

2

Diffusion Weighted Imaging

Diffusion weighted images measures random motion of water molecules. – In ventricles, CSF is unconstrained, so high velocity

diffusion– In brain tissue, water more constrained, so less

diffusion.

DWI

3

Diffusion Tensor Imaging (DTI)

DTI is an extension of DWI that allows us to measure direction of motion.

DTI allows us to measure both the velocity and preferred direction of diffusion– In gray matter, diffusion is isotropic (similar in all directions)– In white matter, diffusion is anisotropic (prefers motion along

fibers).

4

DTI

The amount of diffusion occurring in one pixel of a MR image is termed the Apparent Diffusion Coefficient (ADC) or Mean Diffusivity (MD).

The non-uniformity of diffusion with direction is usually described by the term Fractional Anisotropy (FA).

MD differs FA differs

5

Raw DTI data

DTI scans apply gradients of different strengths (b-values) and directions (b-vectors).

These highlight different diffusion directions.Simplest DTI is shown below: one b=0 image

(no directionality), plus six images with b=1000 but each with a different b-vector.

6

Eddy current correction

Gradients for DTI data cause spatial distortions. Different directions have different distortions. The B0 image has little distortion (it is a T2 weighted Image) Eddy current correction aligns all directions to the b0

(reference) image. Analogous to motion correction for fMRI data.

7

What is a tensor?

A tensor is composed of three vectors.– Think of a vector like an arrow

in 3D space – it points in a direction and has a length.

The first vector is the longest – it points along the principle axis.

The second and third vectors are orthogonal to the first.

Sphere: V1=V2=V3

Football: V1>V2 V1>V3 V3 = V2

???: V1>V2>V3

8

DTI

MD FA

V1 modulated by FA

Color shows principle tensor direction,

brightness shows FA

9

The crossing fibers problem

Tensor (DTI) will have trouble distinguishing voxels with crossing fibers from isotropic regions.

TensorsReality

CSF (isotropic)Crossing fibers

10

Tractography

Programs like medInria allow us to measure integrity of connections between different regions.

11

Statistics – MD and FA

The FA and MD maps from each individual can be normalized to standard space.

Standard voxelwise statistics applied (like VBM)Allows us to infer differences in white matter integrity

between groups.

Group mean images based on normalized data.

12

Statistics – tensors

You can measure fiber strength connectivity brain regions and see if this differs between groups.

Traditionally, tensor maps are very difficult to normalize – we do not want to squish relative shape of tensor.– Recent advances are addressing this (DTITK)

13

TBSS - Tract-Based Spatial Statistics

TBSS is a FSL approach to conduct between group comparisons of DTI data.

projects data onto group-mean tract skeleton, allowing voxelwise analysis

addresses alignment problems unsolved by nonlinear registration

Overview www.fmrib.ox.ac.uk/fsl/tbss/index.html

Tutorial www.fmrib.ox.ac.uk/fslcourse/lectures/practicals/fdt/index.htm

14

Sample application

Young adults vary in their ability to recollect information.

TBSS shows that Fornix integrity predicts this variability (but not variability in familiarity).

Rudebeck (2009) JoN