An introduction to diffusion tensor image analysis

Abstract

Diffusion tensor magnetic resonance imaging (DTI) is a relatively new technology that is popular for imaging the white matter of the brain. This article provides a basic and broad overview of DTI to enable the reader to develop an intuitive understanding of these types of data, and an awareness of their strengths and weaknesses.

Figure 1

Illustration of anisotropic diffusion, in the ideal case of a coherently oriented tissue. This example compares the diffusion measured parallel and perpendicular to the axons in a white matter fiber tract.

Figure 2

Three example diffusion tensors, selected from a DTI scan of the human brain to illustrate differences in tensor anisotropy and orientation.

Figure 3

Six diffusion-weighted images (the minimum number required for tensor calculation). In diffusion MRI, magnetic field gradients are employed to sensitize the image to diffusion in a particular direction. The direction is different for each image, resulting in a different pattern of signal loss (dark areas) due to anisotropic diffusion.

Figure 4

Scalar measures derived from DTI include FA, mode, C_L, C_P, and C_S. Also shown (top row, middle) is a mapping of the major eigenvector orientation to colors. See the text for more information about the definition of these measures.

Figure 5

An example using glyphs and colors for DTI visualization. On the left an axial image plane, showing the average diffusion-weighted image with semi-transparent color overlay indicating the major eigenvector orientation, and a white square indicating the zoomed-in area (right image). In both images the color red indicates right-left orientation, blue is superior-inferior, and green is anterior-posterior. The right image contains glyphs representing major eigenvector orientations (and scaled by the largest eigenvalue) in the region of the corpus callosum (yellow and red) and right lateral ventricle. The cingulum can be seen in blue, and the posterior limb of the internal capsule in green.

Figure 6

Example whole-brain streamline DTI tractography. Colors were assigned automatically according to an atlas-based tractography segmentation method [60].

Figure 7

The major eigenvector may not be aligned with a fiber tract in the case of crossing fibers.

Figure 8

Example false negative streamline tractography error. The motor fibers (yellow) do not reach all functional magnetic resonance (fMRI) motor activations (aqua, blue, and pink) due in part to the superior longitudinal fasciculus (green) that runs perpendicular to the motor tract. In the right column are coronal views of the typical streamline tractography result (top) and expected anatomy (bottom).

Figure 9

Example false positive streamline tractography error. In the left image, fibers (yellow with black dotted line) have traced parts of two anatomical structures by incorrectly crossing from one to the other (at arrow). In the right image, both structures (arcuate fasciculus in magenta and corona radiata in yellow) can be seen.