Anisotropic water diffusion in neural fibres such as nerve, white matter in spinal cord, or white matter in brain forms the basis for the utilization of diffusion tensor imaging (DTI) to track fibre pathways. The fact that water diffusion is sensitive to the underlying tissue microstructure provides a unique method of assessing the orientation and integrity of these neural fibres, which may be useful in assessing a number of neurological disorders. The purpose of this review is to characterize the relationship of nuclear magnetic resonance measurements of water diffusion and its anisotropy (i.e. directional dependence) with the underlying microstructure of neural fibres. The emphasis of the review will be on model neurological systems both in vitro and in vivo. A systematic discussion of the possible sources of anisotropy and their evaluation will be presented followed by an overview of various studies of restricted diffusion and compartmentation as they relate to anisotropy. Pertinent pathological models, developmental studies and theoretical analyses provide further insight into the basis of anisotropic diffusion and its potential utility in the nervous system.

The state of the art of reconstruction of the axonal tracts in the central nervous system (CNS) using diffusion tensor imaging (DTI) is reviewed. This relatively new technique has generated much enthusiasm and high expectations because it presently is the only approach available to non-invasively study the three-dimensional architecture of white matter tracts. While there is no doubt that DTI fiber tracking is providing exciting new opportunities to study CNS anatomy, it is very important to understand its limitations. In this review we therefore assess the basic principles and the assumptions that need to be made for each step of the study, including both data acquisition and the elaborate fiber reconstruction algorithms. Special attention is paid to situations where complications may arise, and possible solutions are reviewed. Validation issues and potential future directions and improvements are also discussed.

This article treats the theoretical underpinnings of diffusion-tensor magnetic resonance imaging (DT-MRI), as well as experimental design and data analysis issues. We review the mathematical model underlying DT-MRI, discuss the quantitative parameters that are derived from the measured effective diffusion tensor, and describe artifacts that arise in typical DT-MRI acquisitions. We also discuss difficulties in identifying appropriate models to describe water diffusion in heterogeneous tissues, as well as in interpreting experimental data obtained in such issues. Finally, we describe new statistical methods that have been developed to analyse DT-MRI data, and their potential uses in clinical and multi-site studies.

Magnetic resonance diffusion tensor imaging (DTI) provides a powerful tool for mapping neural histoarchitecture in vivo. However, DTI can only resolve a single fiber orientation within each imaging voxel due to the constraints of the tensor model. For example, DTI cannot resolve fibers crossing, bending, or twisting within an individual voxel. Intravoxel fiber crossing can be resolved using q-space diffusion imaging, but q-space imaging requires large pulsed field gradients and time-intensive sampling. It is also possible to resolve intravoxel fiber crossing using mixture model decomposition of the high angular resolution diffusion imaging (HARDI) signal, but mixture modeling requires a model of the underlying diffusion process.Recently, it has been shown that the HARDI signal can be reconstructed model-independently using a spherical tomographic inversion called the Funk-Radon transform, also known as the spherical Radon transform. The resulting imaging method, termed q-ball imaging, can resolve multiple intravoxel fiber orientations and does not require any assumptions on the diffusion process such as Gaussianity or multi-Gaussianity. The present paper reviews the theory of q-ball imaging and describes a simple linear matrix formulation for the q-ball reconstruction based on spherical radial basis function interpolation. Open aspects of the q-ball reconstruction algorithm are discussed.

Magnetic resonance (MR) diffusion tensor imaging (DTI) can resolve the white matter fiber orientation within a voxel provided that the fibers are strongly aligned. However, a given voxel may contain a distribution of fiber orientations due to, for example, intravoxel fiber crossing. The present study sought to test whether a geodesic, high b-value diffusion gradient sampling scheme could resolve multiple fiber orientations within a single voxel. In regions of fiber crossing the diffusion signal exhibited multiple local maxima/minima as a function of diffusion gradient orientation, indicating the presence of multiple intravoxel fiber orientations. The multimodality of the observed diffusion signal precluded the standard tensor reconstruction, so instead the diffusion signal was modeled as arising from a discrete mixture of Gaussian diffusion processes in slow exchange, and the underlying mixture of tensors was solved for using a gradient descent scheme. The multitensor reconstruction resolved multiple intravoxel fiber populations corresponding to known fiber anatomy. Ma

Myelin loss and axonal damage are both observed in white matter injuries. Each may have significant impact on the long-term disability of patients. Currently, there does not exist a noninvasive biological marker that enables differentiation between myelin and axonal injury. We describe herein the use of magnetic resonance diffusion tensor imaging (DTI) to quantify the effect of dysmyelination on water directional diffusivities in brains of shiverer mice in vivo. The principal diffusion eigenvalues of eight axonal fiber tracts that can be identified with certainty on DTI maps were measured. The water diffusivity perpendicular to axonal fiber tracts, lambda(perpendicular), was significantly higher in shiverer mice compared with age-matched controls, reflecting the lack of myelin and the increased freedom of cross-fiber diffusion in white matter. The water diffusivity parallel to axonal fiber tracts, lambda(parallel), was not different, which is consistent with the presence of intact axons. It is clear that dysmyelination alone does not impact lambda(parallel). The presence of intact axons in the setting of incomplete myelination was confirmed by electron microscopy. Although further validation is still needed, our finding suggests that changes in lambda(perpendicular) and lambda(parallel) may potentially be used to differentiate myelin loss versus axonal injury.

PURPOSE: To examine a new way of body diffusion weighted imaging (DWI) using the short TI inversion recovery-echo planar imaging (STIR-EPI) sequence and free breathing scanning (diffusion weighted whole body imaging with background body signal suppression; DWIBS) to obtain three-dimensional displays. MATERIALS AND METHODS: 1) Apparent contrast-to-noise ratios (AppCNR) between lymph nodes and surrounding fat tissue were compared in three types of DWI with and without breath-holding, with variable lengths of scan time and slice thickness. 2) The STIR-EPI sequence and spin echo-echo planar imaging (SE-EPI) sequence with chemical shift selective (CHESS) pulse were compared in terms of their degree of fat suppression. 3) Eleven patients with neck, chest, and abdominal malignancy were scanned with DWIBS for evaluation of feasibility. Whole body imaging was done in a later stage of the study using the peripheral vascular coil. RESULTS: The AppCNR of 8 mm slice thickness images reconstructed from 4 mm slice thickness source images obtained in a free breathing scan of 430 sec were much better than 9 mm slice thickness breath-hold scans obtained in 25 sec. High resolution multi-planar reformat (MPR) and maximum intensity projection (MIP) images could be made from the data set of 4 mm slice thickness images. Fat suppression was much better in the STIR-EPI sequence than SE-EPI with CHESS pulse. The feasibility of DWIBS was showed in clinical scans of 11 patients. Whole body images were successfully obtained with adequate fat suppression. CONCLUSION: Three-dimensional DWIBS can be obtained with this technique, which may allow us to screen for malignancies in the whole body.

While functional brain imaging methods can locate the cortical regions subserving particular cognitive functions, the connectivity between the functional areas of the human brain remains poorly understood. Recently, investigators have proposed a method to image neural connectivity noninvasively using a magnetic resonance imaging method called diffusion tensor imaging (DTI). DTI measures the molecular diffusion of water along neural pathways. Accurate reconstruction of neural connectivity patterns from DTI has been hindered, however, by the inability of DTI to resolve more than a single axon direction within each imaging voxel. Here, we present a novel magnetic resonance imaging technique that can resolve multiple axon directions within a single voxel. The technique, called q-ball imaging, can resolve intravoxel white matter fiber crossing as well as white matter insertions into cortex. The ability of q-ball imaging to resolve complex intravoxel fiber architecture eliminates a key obstacle to mapping neural connectivity in the human brain noninvasively.

We review the current state-of-the-art of diffuse optical imaging, which is an emerging technique for functional imaging of biological tissue. It involves generating images using measurements of visible or near-infrared light scattered across large (greater than several centimetres) thicknesses of tissue. We discuss recent advances in experimental methods and instrumentation, and examine new theoretical techniques applied to modelling and image reconstruction. We review recent work on in vivo applications including imaging the breast and brain, and examine future challenges.

The application of diffusion tensor imaging (DTI) to the evaluation of developing brain remains an area of active investigation. This review focuses on the changes in DTI parameters which accompany both brain maturation and injury. The two primary pieces of information available from DTI studies-water apparent diffusion coefficient and diffusion anisotropy measures-change dramatically during development, reflecting underlying changes in tissue water content and cytoarchitecture. DTI parameters also change in response to brain injury. In this context, not only does DTI offer the possibility of detecting injury earlier than conventional imaging methods, but also appears more sensitive to disruption of white matter than any other imaging method. DTI offers unique insight into brain injury and maturation, and does so in a fashion that can be readily applied in a clinical setting.