Table 1.

Diffusion Tensor Imaging Definitions.

Characteristic	Definition
Eigenvectors/eigenvalues	Eigenvectors are characteristic vectors of a linear transformation that do not change direction when the transformation is applied to them. The eigenvalue is the scalar value by which the eigenvector is multiplied by when it is subject to the transformation. In the diffusion tensor model, this linear algebraic concept is used to estimate the extent of water diffusion along the x-, y-, and z-axes within a given tensor.7
Diffusion tensor	A 3 × 3 matrix that represents molecular diffusion in a 3-dimensional space. Often represented as an ellipsoid defined by 3 eigenvalues: λ1, λ2, and λ3, where λ1 > λ2 > λ3.6
Diffusion tensor imaging	Magnetic resonance imaging modality that maps the extent and direction of water molecule diffusion within tissue using the tensor model.
Diffusion tractography	Technique used to map out white matter bundles. This is done by fitting adjacent tensors to predict the most probable course of fibers.
Fractional anisotropy (FA)	Represents the degree of diffusion within a given tensor that is anisotropic. FA = √(3/2) * (√((λ1 − MD)2 + (λ2 − MD)2 + (λ3 − MD)2)/√(λ12 + λ22 + λ32).6
Mean diffusivity (MD)	Represents mean diffusion across all three axes within a given tensor. MD = (λ1 + λ2 + λ3)/3.7
Radial diffusivity (RD)	Represents the magnitude of diffusion along axes perpendicular to the principal direction of diffusion within a given tensor. RD = (λ2 + λ3)/2.30
Axial diffusivity (AD)	Represents magnitude of molecular diffusion along the axis parallel to the principal direction of diffusion within a given tensor. AD = λ1.30