Figure 2.

The “diffusion tensor.” (A) Six combinations of gradients applied with different intensities along three orthogonal orientations (x. y, and z), and a measurement without diffusion weighting, are the minimum requirements to probe diffusion in a 3D space; each non-collinear combination is called a “diffusion direction.” (B) A larger number of diffusion directions, N_d, can estimate the directional dependence of microstructural restrictions to water diffusion with greater precision. (C) Basser et al. (1994b) proposed the formulation of a diffusion tensor (represented by an ellipsoid) to capture diffusion behaviors in 3D with a finite N_d. (D) The tensor can be rotated to match the principal direction of diffusion, i.e., in white matter, the first eigenvector (ε₁) matches the predominant fiber tract orientation; thus, the largest eigenvalue (λ₁, known as “axial diffusivity”) quantifies water mobility along this orientation. Analogously, ε₂ and ε₃ define the plane perpendicular to the axonal arrangement so that λ₂ and λ₃ can be averaged as a “radial diffusivity” (RD). In addition, all three eigenvalues can be averaged to estimate the “mean square displacement” of water molecules—that is, the “mean diffusivity” (MD).