Diffusion tensor fiber tracking of human brain connectivity: aquisition methods, reliability analysis and biological results.

We present a description, biological results and a reliability analysis for the method of diffusion tensor tracking (DTT) of white matter fiber pathways. In DTT, diffusion-tensor MRI (DT-MRI) data are collected and processed to visualize the line trajectories of fiber bundles within white matter (WM) pathways of living humans. A detailed description of the data acquisition is given. Technical aspects and experimental results are illustrated for the geniculo-calcarine tract with broad projections to visual cortex, occipital and parietal U-fibers, and the temporo-calcarine ventral pathway. To better understand sources of error and to optimize the method, accuracy and precision were analyzed by computer simulations. In the simulations, noisy DT-MRI data were computed that would be obtained for a WM pathway having a helical trajectory passing through gray matter. The error vector between the real and ideal track was computed, and random errors accumulated with the square root of track length consistent with a random-walk process. Random error was most dependent on signal-to-noise ratio, followed by number of averages, pathway anisotropy and voxel size, in decreasing order. Systematic error only occurred for a few conditions, and was most dependent on the stepping algorithm, anisotropy of the surrounding tissue, and non-equal voxel dimensions. Both random and systematic errors were typically below the voxel dimension. Other effects such as track rebound and track recovery also depended on experimental conditions. The methods, biological results and error analysis herein may improve the understanding and optimization of DTT for use in various applications in neuroscience and medicine.

Differences between gray matter and white matter water diffusion in stroke: diffusion-tensor MR imaging in 12 patients.

PURPOSE: To investigate differences in water diffusion between white matter and gray matter in acute to early subacute stroke with diffusion-tensor magnetic resonance (MR) imaging. MATERIALS AND METHODS: Twelve patients with unilateral middle cerebral arterial infarcts were examined with diffusion tensor-encoded echo-planar MR imaging 17 hours to 5 days after stroke onset. Isotropic diffusion coefficient (D) and diffusion anisotropy (A(sigma)) images were computed. (D) values were measured in ischemic and contralateral gray matter and white matter by using A(sigma) images to differentiate white matter from gray matter. (D) images were compared with unidirectional and directionally averaged diffusion-weighted images. RESULTS: In all patients, (D) images showed two distinct levels of diffusion reduction in the infarct; more severe reduction occurred exclusively in white matter. (D) values were significantly less in infarcted white matter than in infarcted gray matter, whereas (D) values in the contralateral white matter and gray matter were not significantly different. Relative to the contralateral side, (D) values in the infarct were reduced by 46% in white matter and by 31% in gray matter (P <.001). Diffusion-weighted imaging caused underestimation of the magnitude and, in some cases, the spatial extent of the white matter diffusion abnormality. CONCLUSION: Isotropic diffusion is more reduced in white matter than in gray matter in acute to early subacute middle cerebral arterial stroke. Diffusion-tensor imaging may be more sensitive than diffusion-weighted imaging to white matter ischemia.

Tracking neuronal fiber pathways in the living human brain.

Functional imaging with positron emission tomography and functional MRI has revolutionized studies of the human brain. Understanding the organization of brain systems, especially those used for cognition, remains limited, however, because no methods currently exist for noninvasive tracking of neuronal connections between functional regions [Crick, F. & Jones, E. (1993) Nature (London) 361, 109-110]. Detailed connectivities have been studied in animals through invasive tracer techniques, but these invasive studies cannot be done in humans, and animal results cannot always be extrapolated to human systems. We have developed noninvasive neuronal fiber tracking for use in living humans, utilizing the unique ability of MRI to characterize water diffusion. We reconstructed fiber trajectories throughout the brain by tracking the direction of fastest diffusion (the fiber direction) from a grid of seed points, and then selected tracks that join anatomically or functionally (functional MRI) defined regions. We demonstrate diffusion tracking of fiber bundles in a variety of white matter classes with examples in the corpus callosum, geniculo-calcarine, and subcortical association pathways. Tracks covered long distances, navigated through divergences and tight curves, and manifested topological separations in the geniculo-calcarine tract consistent with tracer studies in animals and retinotopy studies in humans. Additionally, previously undescribed topologies were revealed in the other pathways. This approach enhances the power of modern imaging by enabling study of fiber connections among anatomically and functionally defined brain regions in individual human subjects.

Quantitative diffusion-tensor anisotropy brain MR imaging: normative human data and anatomic analysis.

PURPOSE: To obtain normative human cerebral data and evaluate the anatomic information in quantitative diffusion anisotropy magnetic resonance (MR) imaging. MATERIALS AND METHODS: Quantitative diffusion anisotropy MR images were obtained in 13 healthy adults by using single-shot echo-planar MR imaging and a combination of tetrahedral and orthogonal gradient encoding (whole-brain coverage in about 1 minute). White matter (WM) anatomy was assessed at visual inspection, and values were measured in various brain regions. Different anisotropy measures, including total anisotropy (A sigma), were compared on the basis of information content, rotational invariance, and susceptibility to noise. Partial volume and noise effects were simulated. RESULTS: Anisotropy MR images depicted WM features not typically seen on conventional MR images (e.g., external capsule, thalamic substructures, basal ganglia, occipital WM, thickness of the internal capsule). Statistically significant anisotropy differences occurred across brain regions, which were reproducible within and across subjects. A sigma was highest in commissural WM and progressively lower in projection and association WM. This order paralleled that of known resistance to spread of vasogenic edema, which suggested that anisotropy may be sensitive to WM histologic structure. Gray matter (GM) A sigma data were consistent with zero anisotropy, and partial volume WM-GM effects were approximately linear. A sigma image quality could be effectively improved by means of averaging. CONCLUSION: Quantitative diffusion anisotropy images can be obtained rapidly and demonstrate subtle WM anatomy. Different histologic types of WM have significant and reproducible anisotropy differences.