In vivo diffusion tensor imaging of the human optic chiasm at sub-millimeter resolution

Abstract

In this work we report findings from an in vivo diffusion tensor imaging (DTI) study of the human optic chiasm at sub-millimeter voxel resolution. Data were collected at 3 T using a diffusion-weighted radial-FSE sequence, which provides images free from typical magnetic susceptibility artifacts. The general DTI features observed in the optic chiasm region were consistent across subjects. They included a central area with high anisotropy and highest diffusivity in a predominately right/left direction corresponding to the decussation of nasal hemiretinae fibers, surrounded by a band of low anisotropy reflecting heterogeneous orientation of fibers within the voxel, and a lateral area with high anisotropy and highest diffusivity in a predominately anterior/posterior direction corresponding to temporal hemiretinae fibers that do not cross. Animal studies indicate that there is a significant dorsal-ventral reorganization of the retinotopic distribution of fibers along the optic pathways. We found that diffusion ellipsoids in the central portion of the optic chiasm show considerable planar anisotropy in the coronal plane indicating fiber crossings in the superior/inferior direction, rather than strictly right/left. This architectural feature of the chiasm suggests that dorso-ventral reorganization of fibers in the optic pathways also occurs in humans. We have shown that by collecting sub-millimeter resolution data, DTI can be used to investigate fine details of small and complex white matter structures, in vivo, with a clinical scanner. High spatial resolution, however, is necessary in the slice direction as well as in-plane to reduce the CSF contribution to the signal and to increase fiber coherence within voxels.

Figure 1

Images of a resolution phantom acquired with a standard FSE (A) and the radial-FSE (B) sequence at 0.9 x 0.9mm in-plane resolution. The images have been cropped to the area of pertinent resolution. The large squares are 2 x 2mm with 2mm spacing, while the smaller squares are 1 x 1mm with 1mm spacing.

Figure 2

Images of the optic nerves, chiasm, and tracts region in a healthy volunteer. The acquired T1-FLAIR image is shown in A for general anatomical reference. The cropped T1-FLAIR image is shown in E overlaid with representative ROIs. Corresponding mean diffusivity (B–D) and LI-ε₁ DEC (F–H) maps are displayed. Images with 8mm³ voxels were collected with SSEPI (B and F) and radial-FSE (C and G). Images with 0.729mm³ voxels acquired with radial-FSE are shown in D and H.

Figure 3

Line field map, corresponding to the LI-ε₁ DEC map in Fig. 2H, displaying a segment whose length is proportional to anisotropy with orientation of the first eigenvector projected on to the slice plane. Map displays one segment per voxel at the original resolution. Arrows point to the fibers entering the lateral geniculate bodies.

Figure 4

LI-ε₁ DEC maps collected at the same in-plane resolution, 0.8 x 0.8mm, with slice thickness of 3mm (A) and 0.8mm (B), respectively.

Figure 5

LI-ε₁ DEC maps of a healthy volunteer from three separate scan sessions, all acquired at 0.9mm isotropic resolution.

Figure 6

Maps of linear and planar measures corresponding to the DTI data shown in Fig. 5. The C_l-ε₁ DEC maps (A–C) are color-coded with the direction of ε₁. The C_p-ε₃ DEC maps (D–F) are color-coded with the direction of ε₃, which is perpendicular to the plane.

Figure 7

Schematic of the proposed crossing trajectory pattern in the central chiasm. The pattern is shown from the three orthogonal views: axial, coronal, and sagittal. The coronal view illustrates that there is a superior/inferior component to the trajectory consequent of the topological rearrangement of fibers from the optic nerve to optic tract.

Figure 8

Depiction of the average ε₃ corresponding to an ROI encompassing the red voxels in the central chiasm from the DTI data shown in Fig. 5A–C. The average ε₃ is represented by the black line in the center of the corresponding cone of uncertainty, a measure of dispersion of the averaged eigenvectors.