The success of diffusion magnetic resonance imaging (MRI) is deeply rooted in the powerful concept that during their random, diffusion-driven displacements molecules probe tissue structure at a microscopic scale well beyond the usual image resolution. As diffusion is truly a three-dimensional process, molecular mobility in tissues may be anisotropic, as in brain white matter. With diffusion tensor imaging (DTI), diffusion anisotropy effects can be fully extracted, characterized, and exploited, providing even more exquisite details on tissue microstructure. The most advanced application is certainly that of fiber tracking in the brain, which, in combination with functional MRI, might open a window on the important issue of connectivity. DTI has also been used to demonstrate subtle abnormalities in a variety of diseases (including stroke, multiple sclerosis, dyslexia, and schizophrenia) and is currently becoming part of many routine clinical protocols. The aim of this article is to review the concepts behind DTI and to present potential applications.

/pdf/diffusion-tensor-imaging-concepts-and-applications-40utq0zjun.pdf

Diffusion tensor imaging: Concepts and applications

Fiber tract trajectories in coherently organized brain white matter pathways were computed from in vivo diffusion tensor magnetic resonance imaging (DT-MRI) data. First, a continuous diffusion tensor field is constructed from this discrete, noisy, measured DT-MRI data. Then a Frenet equation, describing the evolution of a fiber tract, was solved. This approach was validated using synthesized, noisy DT-MRI data. Corpus callosum and pyramidal tract trajectories were constructed and found to be consistent with known anatomy. The method's reliability, however, degrades where the distribution of fiber tract directions is nonuniform. Moreover, background noise in diffusion-weighted MRIs can cause a computed trajectory to hop from tract to tract. Still, this method can provide quantitative information with which to visualize and study connectivity and continuity of neural pathways in the central and peripheral nervous systems in vivo, and holds promise for elucidating architectural features in other fibrous tissues and ordered media.

/pdf/in-vivo-fiber-tractography-using-dt-mri-data-2svl53vsnk.pdf

In vivo fiber tractography using DT-MRI data

A fully probabilistic framework is presented for estimating local probability density functions on parameters of interest in a model of diffusion. This technique is applied to the estimation of parameters in the diffusion tensor model, and also to a simple partial volume model of diffusion. In both cases the parameters of interest include parameters defining local fiber direction. A technique is then presented for using these density functions to estimate global connectivity (i.e., the probability of the existence of a connection through the data field, between any two distant points), allowing for the quantification of belief in tractography results. This technique is then applied to the estimation of the cortical connectivity of the human thalamus. The resulting connectivity distributions correspond well with predictions from invasive tracer methods in nonhuman primate.

/pdf/characterization-and-propagation-of-uncertainty-in-diffusion-22y3bpncsw.pdf

Characterization and propagation of uncertainty in diffusion-weighted MR imaging.

http://pages.stat.wisc.edu/~mchung/teaching/MIA/reading/DTI.alexander.2007.pdf

Diffusion Tensor Imaging of the Brain

Evidence concerning anatomical connectivities in the human brain is sparse and based largely on limited post-mortem observations. Diffusion tensor imaging has previously been used to define large white-matter tracts in the living human brain, but this technique has had limited success in tracing pathways into gray matter. Here we identified specific connections between human thalamus and cortex using a novel probabilistic tractography algorithm with diffusion imaging data. Classification of thalamic gray matter based on cortical connectivity patterns revealed distinct subregions whose locations correspond to nuclei described previously in histological studies. The connections that we found between thalamus and cortex were similar to those reported for non-human primates and were reproducible between individuals. Our results provide the first quantitative demonstration of reliable inference of anatomical connectivity between human gray matter structures using diffusion data and the first connectivity-based segmentation of gray matter.

Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging

The relationship between brain structure and complex behavior is governed by large-scale neurocognitive networks. The availability of a noninvasive technique that can visualize the neuronal projections connecting the functional centers should therefore provide new keys to the understanding of brain function. By using high-resolution three-dimensional diffusion magnetic resonance imaging and a newly designed tracking approach, we show that neuronal pathways in the rat brain can be probed in situ. The results are validated through comparison with known anatomical locations of such fibers.

Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging.

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Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging.