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FIBER BUNDLE LENGTH IN CEREBRAL WHITE MATTER 23

Figure 1. Visual depiction of tensor-based modeling and diffusion tensor images: an illustration of tensor-based modeling and diffusion
tensor imaging. The top panel shows a single tensor model, which can be decomposed into eigenvectors and eigenvalues. The eigenvec-
tors (v1, v2, v3) represent the major, medium, and minor principle axes of the ellipsoid, and the eigenvalues (λ1, λ2, λ3) represent the
diffusivities in these three directions, respectively. The eigenvalues can be used to describe the shape with fractional anisotropy (FA) and
mean diffusivity (MD). The bottom panel shows diffusion tensor images, which are composed of glyphs representing the tensor models
in each image voxel. The glyphs are ellipsoid shaped and can be colored based on fiber orientation, FA, MD, etc
properties of white matter; however, inclusion of the representing the three-dimensional (3D) path as well
full structure of the tensor model assists in deter- as diffusivity properties sampled along the fiber bun-
mining subtle changes related to tract directionality dle. The trajectories are then graphically depicted
(17,25). using 3D rendering of lines, tubes, or surfaces (31,54).
Tractography can be performed using both determin-
DTI Tractography istic and probabilistic approaches. In deterministic
DTI tractography is a technique for creating geo- tractography, white matter tracts are reconstructed
metric models that reflect the large-scale structure by selecting a seed region and performing streamline
of fiber bundles. These models are created based on integration based on the preferred direction of the dif-
voxel-wise estimates of local fiber orientation using fusion ellipsoids until one of several stopping criteria
the primary tensor eigenvector, which is indicative is reached. Stopping criteria include decreased anisot-
of the direction of the dominant fiber bundle. The ropy, sharp curvature, and reaching tissue boundaries
primary advantage of tractography compared with (33). However, deterministic tractography is limited
regional analysis of scalar metrics is the integration by the accumulation of errors during tracking and
of data across an entire white matter tract (17). This sensitivity to seeding conditions (26). Probabilistic
process can be repeated to provide both a curve tractography is an alternative approach that more