Neuropsychiatric applications of DTI – a review

Abstract

Psychiatric disorders are common throughout the world and are a leading cause of disability. There is a growing appreciation of the importance of connectivity to brain function. Disruption of this connectivity can result in brain dysfunction manifested in impaired cognitive functioning and the development of clinical symptoms. White matter forms the basis of anatomical connectivity. Diffusion tensor imaging (DTI) is a useful tool for examining and quantifying white matter microstructure. Clinical research studies in alcoholism, HIV-1 infection, geriatric depression and schizophrenia using DTI have revealed abnormalities in white matter microstructure. The use of complementary imaging methods may be helpful in further characterizing these abnormalities. Other psychiatric disorders may also have white matter involvement amenable to study with DTI. Advances in acquisition and analysis methods will be necessary to further advance work in this field. The study of animal models and postmortem tissue may be helpful in elucidating the neurobiological underpinnings of abnormalities observed with DTI.

Longitudinal Diffusion Changes in Cerebral Hemispheres after MCA Infarcts

“…In the white matter, the restriction of water diffusion in specific directions due to the presence of axonal membranes and myelin leads to anisotropic diffusion. Pathological processes responsible for microstructural tissue changes, such as neuronal swelling or shrinkage, increased or decreased extracellular space, and modifications of the tissue organization can result in significant changes of water diffusivity and/or anisotropy (Lim and Helpern, 2002).…”

Fiber Tract-Oriented Statistics for Quantitative Diffusion Tensor MRI Analysis

“…We denote the space of all diffusion tensors, i.e., the space of all 3 × 3 symmetric, positive-definite matrices, as PD (3). Averaging and interpolation of diffusion tensors can be formulated as a least-squares minimization problem in this space.…”

“…The Riemannian metric is chosen to be invariant under the group transformations. The symmetric space structure of PD (3) arises from transformations by GL (3), the group of positivedeterminant matrices. The transformation of a diffusion tensor p ∈ PD (3) by a matrix…”

“…So far, analysis schemes have mostly focused on measuring properties in regions of interest and to a lesser extent along fiber bundles [1], [2], and they have not made use of the full tensor information. Consequently, clinical studies have mostly been limited to statistics of FA or MD maps on a voxel-by-voxel basis [3].…”

Active Imaging with Dual Spin-Echo Diffusion MRI

“…DTI uses diffusion weighted measurements along at least six noncollinear directions to estimate a rank-two diffusion tensor at each point in the image, which is proportional to the covariance matrix of a 3D Gaussian distribution over molecular displacements. A scalar value commonly derived from the tensor is fractional anisotropy, a measure of dispersion in the tensor eigenvalues, which has been shown to be locally or globally reduced in a number of diseases [4], as well as some psychiatric disorders such as schizophrenia [5], reflecting changes in the underlying tissue. The principal eigenvector of the tensor, indicating the direction of greatest meansquared displacement, was the original basis for dMRI-based white matter fibre tracking, which has provided insights in basic neuroscience with regard to the connectivity of the brain (e.g.…”