Brain registration to a stereotaxic atlas is an effective way to report anatomic locations of interest and to perform anatomic quantification. However, existing stereotaxic atlases lack comprehensive coordinate information about white matter structures. In this paper, white matter specific atlases in stereotaxic coordinates are introduced. As a reference template, the widely-used ICBM-152 was used. The atlas contains fiber orientation maps and hand-segmented white matter parcellation maps based on diffusion tensor imaging (DTI). Registration accuracy by linear and nonlinear transformation was measured, and automated template-based white matter parcellation was tested. The results showed high correlation between the manual ROI-based and the automated approaches for normal adult populations. The atlases are freely available and believed to be a useful resource as a target template and for automated parcellation methods.

Tractography based on diffusion tensor imaging (DTI) allows visualization of white matter tracts. In this study, protocols to reconstruct eleven major white matter tracts are described. The protocols were refined by several iterations of intra-and inter-rater measurements and identification of sources of variability. Reproducibility of the established protocols was then tested by raters who did not have previous experience in tractography. The protocols were applied to a DTI database of adult normal subjects to study size, fractional anisotropy (FA), and T 2 of individual white matter tracts. Distinctive features in FA and T 2 were found for the corticospinal tract and callosal fibers. Hemispheric asymmetry was observed for the size of white matter tracts projecting to the temporal lobe. This protocol provides guidelines for reproducible DTI-based tract-specific quantification.

Diffusion tensor imaging (DTI) is an exciting new MRI modality that can reveal detailed anatomy of the white matter. DTI also allows us to approximate the 3D trajectories of major white matter bundles. By combining the identified tract coordinates with various types of MR parameter maps, such as T 2 and diffusion properties, we can perform tract-specific analysis of these parameters. Unfortunately, 3D tract reconstruction is marred by noise, partial volume effects, and complicated axonal structures. Furthermore, changes in diffusion anisotropy under pathological conditions could alter the results of 3D tract reconstruction. In this study, we created a white matter parcellation atlas based on probabilistic maps of 11 major white matter tracts derived from the DTI data from 28 normal subjects. Using these probabilistic maps, automated tract-specific quantification of fractional anisotropy and mean diffusivity were performed. Excellent correlation was found between the automated and the individual tractography-based results. This tool allows efficient initial screening of the status of multiple white matter tracts.

The brain contains more than 100 billion neurons that communicate with each other via axons for the formation of complex neural networks. The structural mapping of such networks during health and disease states is essential for understanding brain function. However, our understanding of brain structural connectivity is surprisingly limited, due in part to the lack of noninva-sive methodologies to study axonal anatomy. Diffusion tensor imaging (DTI) is a recently developed MRI technique that can measure macroscopic axonal organization in nervous system tissues. In this article, the principles of DTI methodologies are explained, and several applications introduced, including visualization of axonal tracts in myelin and axonal injuries as well as human brain and mouse embryonic development. The strengths and limitations of DTI and key areas for future research and development are also discussed. Introduction The human brain consists of more than 100 billion neu-rons, and it is arguably the most complex structure in our body. Imaging has been a powerful technique to navigate us through this vast entity and identify the places where biological events of interest occur. In animal studies, histology followed by examination with light or electron microscopy has been one of the most widely used imaging methods. Various staining techniques can highlight the locations of proteins and genes of interests, and electron microscopy can extend our observation to objects at the molecular level. However, histology-based imaging has several serious drawbacks. First, it is invasive. Second, its labor-intensive and destructive nature makes it a nonideal choice for examining the entire brain or for performing quantitative three-dimensional analyses. MRI is probably at the other end of the spectrum of imaging modalities. It is noninva-sive, three-dimensional, and requires as little as a few minutes to characterize the entire brain anatomy. The end results are often merely a few megabytes (MBs) of data, in which all the relevant brain information is condensed by a consistent sampling scheme. Its strength is, however, also its weakness. While the brain anatomical information is condensed, much biological information is degenerated, which causes a loss of specificity and sensitivity to certain biological processes. It is a never-ending quest for the MRI research community to attempt to recover more types of biological information that would otherwise be lost with conventional MRI techniques. In this review, we would like to introduce a new MRI technique called diffusion tensor imaging (DTI). This imaging technique can delineate the axonal organization of the brain, which we could not appreciate with conventional MRI. DTI was introduced in the mid 1990s (Basser et al., 1994), and its applications to small animal studies have only recently been initiated (Ahrens et al., 1998; Harsan et al., 2006; Kroenke et al., 2006; Mori et al., 2001; Nair et al., 2005). The purpose of this review is to explain how DTI works and to introduce state-of-the-...