DTI of commissural fibers in patients with Chiari II-malformation.

Chiari II-malformation is a complex congenital deformity of the brain which is frequently associated with hydrocephalus. Abnormalities of the corpus callosum are known to occur in the majority of patients. The objective of the present study was to study the microstructure of the corpus callosum (CC) and the anterior commissure (AC) to differentiate between different mechanisms of damage to these structures. We investigated 6 patients with Chiari II-malformation and 6 well-matched healthy volunteers employing T1-weighted 3D imaging and diffusion tensor imaging (DTI) to determine the fractional anisotropy (FA) and cross-sectional area of the CC and AC, as well as with neuropsychological testing. Four patients showed hydrocephalus, two patients had callosal dysplasia and four had a hypoplastic CC. The callosal FA in the patients was significantly reduced which was less pronounced for the genu alone. The area of CC was also reduced in Chiari II-patients. There was a strong correlation between the size and FA of the CC in the patients. In contrast, the thickness of the AC was significantly increased and was associated with higher FA in the patients. In psychological tests all patients showed reduced verbal memory; all but one patient showed reduced IQ as well as impaired visuo-spatial performance, indicating deficits in tasks requiring parieto-occipital integration. The existence of callosal dysplasia in two patients, the diminished FA reduction in the genu and the correlation of the cross-sectional area and FA in the patients point to a developmental white matter damage beside that exerted by hydrocephalus alone.

Fiber tracking of human brain using fourth-order tensor and high angular resolution diffusion imaging.

The accuracy of fiber tracking on the basis of diffusion tensor magnetic resonance imaging (DTI) is affected by many parameters. To increase accuracy of the tracking algorithm, we introduce DTI with a fourth-order tensor. Tensor elements comprise information obtained by high angular resolution diffusion imaging (HARDI). We further developed the flattened high rank tensor (FLAHRT) method and applied it to the measured fourth-order tensor. We then compared FLAHRT with: 1) the standard tracking algorithm using a second-order tensor; and 2) existing techniques involving the representation of conventional second-order tensor components as a weighted average of fourth-order tensor elements. Such techniques have been formulated in recent DT studies to link high-rank to low-rank Cartesian diffusion tensors (DTs). Diagonalization of the second-order tensor decomposes the tensor into three eigenvalues and three eigenvectors, which in turn are used to describe the diffusivity profile of a particular voxel. Diagonalization after application of the FLAHRT method reveals six eigenvalues and six eigentensors, resulting in a more accurate description of the anisotropy. We performed fiber tracking based on the eigenvalues and eigentensors calculated with the FLAHRT and standard methods. We could show that the FLAHRT technique gives more consistent and more accurate results even with a data set acquired in 15 directions only. The decomposition of the fourth-order tensor into six eigentensors has the potential to describe six different fiber orientations within a voxel.