On the Problem of Diffusivity in Heterogeneous Biological Materials with Random Structure

Biological tissues are multicompartmental heterogeneous media composed of cellular and subcellular domains. Randomly walking water molecules may have different diffusion coefficients and densities (concentrations) in different domains, namely within cells and within the outer medium. Results of the proposed effective media scale-averaging iterative scheme are used to explore the effects of a large range of microstructural and compositional parameters on the apparent (effective) diffusion coefficient. A self-consistent modelling framework for predicting the steady-state effective diffusion coefficient is presented; the framework reveals the strong dependence of the apparent diffusion coefficient on the ratio of the microscopic diffusion coefficients of the comprising phases, permeability of the cells, and their volume fractions.     

Multi-Shell Hybrid Diffusion Imaging (HYDI) at 7 Tesla in TgF344-AD Transgenic Alzheimer Rats

Diffusion weighted imaging (DWI) is widely used to study microstructural characteristics of the brain. Diffusion tensor imaging (DTI) and high-angular resolution imaging (HARDI) are frequently used in radiology and neuroscience research but can be limited in describing the signal behavior in composite nerve fiber structures. Here, we developed and assessed the benefit of a comprehensive diffusion encoding scheme, known as hybrid diffusion imaging (HYDI), composed of 300 DWI volumes acquired at 7-Tesla with diffusion weightings at b = 1000, 3000, 4000, 8000 and 12000 s/mm² and applied it in transgenic Alzheimer rats (line TgF344-AD) that model the full clinico-pathological spectrum of the human disease. We studied and visualized the effects of the multiple concentric “shells” when computing three distinct anisotropy maps–fractional anisotropy (FA), generalized fractional anisotropy (GFA) and normalized quantitative anisotropy (NQA). We tested the added value of the multi-shell q-space sampling scheme, when reconstructing neural pathways using mathematical frameworks from DTI and q-ball imaging (QBI). We show a range of properties of HYDI, including lower apparent anisotropy when using high b-value shells in DTI-based reconstructions, and increases in apparent anisotropy in QBI-based reconstructions. Regardless of the reconstruction scheme, HYDI improves FA-, GFA- and NQA-aided tractography. HYDI may be valuable in human connectome projects and clinical research, as well as magnetic resonance research in experimental animals.     

Advanced diffusion MRI fiber tracking in neurosurgical and neurodegenerative disorders and neuroanatomical studies: A review

Diffusion MRI enabled in vivo microstructural imaging of the fiber tracts in the brain resulting in its application in a wide range of settings, including in neurological and neurosurgical disorders. Conventional approaches such as diffusion tensor imaging (DTI) have been shown to have limited applications due to the crossing fiber problem and the susceptibility of their quantitative indices to partial volume effects. To overcome these limitations, the recent focus has shifted to the advanced acquisition methods and their related analytical approaches. Advanced white matter imaging techniques provide superior qualitative data in terms of demonstration of multiple crossing fibers in their spatial orientation in a three dimensional manner in the brain. In this review paper, we discuss the advancements in diffusion MRI and introduce their roles. Using examples, we demonstrate the role of advanced diffusion MRI-based fiber tracking in neuroanatomical studies. Results from its preliminary application in the evaluation of intracranial space occupying lesions, including with respect to future directions for prognostication, are also presented. Building upon the previous DTI studies assessing white matter disease in Huntington's disease and Amyotrophic lateral sclerosis; we also discuss approaches which have led to encouraging preliminary results towards developing an imaging biomarker for these conditions.     

Microstructure of temporo-parietal white matter as a basis for reading ability: evidence from diffusion tensor magnetic resonance imaging

Diffusion tensor magnetic resonance imaging (MRI) was used to study the microstructural integrity of white matter in adults with poor or normal reading ability. Subjects with reading difficulty exhibited decreased diffusion anisotropy bilaterally in temporoparietal white matter. Axons in these regions were predominantly anterior-posterior in direction. No differences in T1-weighted MRI signal were found between poor readers and control subjects, demonstrating specificity of the group difference to the microstructural characteristics measured by diffusion tensor imaging (DTI). White matter diffusion anisotropy in the temporo-parietal region of the left hemisphere was significantly correlated with reading scores within the reading-impaired adults and within the control group. The anisotropy reflects microstructure of white matter tracts, which may contribute to reading ability by determining the strength of communication between cortical areas involved in visual, auditory, and language processing.     

Clinical application of diffusion tensor imaging and tractography in a child with holoprosencephaly

Diffusion tensor imaging and fiber tracking can be methods used for the study of congenital brain malformations associated to white matter bundle abnormalities.Their use is illustrated in a child with semilobar holoprosencephaly in whom diffusion tensor imaging and tractography showed diencephalic ventral induction failure and abnormal white matter fascicles in brain and brainstem.     

Inter Subject Variability and Reproducibility of Diffusion Tensor Imaging within and between Different Imaging Sessions

The aim of these studies was to provide reference data on intersubject variability and reproducibility of diffusion tensor imaging. Healthy volunteers underwent imaging on two occasions using the same 3T Siemens Verio magnetic resonance scanner. At each session two identical diffusion tensor sequences were obtained along with standard structural imaging. Fractional anisotropy, apparent diffusion coefficient, axial and radial diffusivity maps were created and regions of interest applied in normalised space. The baseline data from all 26 volunteers were used to calculate the intersubject variability, while within session and between session reproducibility were calculated from all the available data. The reproducibility of measurements were used to calculate the overall and within session 95% prediction interval for zero change. The within and between session reproducibility data were lower than the values for intersubject variability, and were different across the brain. The regional mean (range) coefficient of variation figures for within session reproducibility were 2.1 (0.9–5.5%), 1.2 (0.4–3.9%), 1.2 (0.4–3.8%) and 1.8 (0.4–4.3%) for fractional anisotropy, apparent diffusion coefficient, axial and radial diffusivity, and were lower than between session reproducibility measurements (2.4 (1.1–5.9%), 1.9 (0.7–5.7%), 1.7 (0.7–4.7%) and 2.4 (0.9–5.8%); p<0.001). The calculated overall and within session 95% prediction intervals for zero change were similar. This study provides additional reference data concerning intersubject variability and reproducibility of diffusion tensor imaging conducted within the same imaging session and different imaging sessions. These data can be utilised in interventional studies to quantify change within a single imaging session, or to assess the significance of change in longitudinal studies of brain injury and disease.     

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when studying the brain, as the functional role that a brain area fulfills may be largely defined by its connections to other brain areas. In this report, we describe a novel, non-invasive approach for relating brain structure and function using magnetic resonance imaging (MRI). This approach, a combination of structural imaging of long-range fiber connections and functional imaging data, is illustrated in two distinct cognitive domains, visual attention and face perception. Structural imaging is performed with diffusion-weighted imaging (DWI) and fiber tractography, which track the diffusion of water molecules along white-matter fiber tracts in the brain (Figure 1). By visualizing these fiber tracts, we are able to investigate the long-range connective architecture of the brain. The results compare favorably with one of the most widely-used techniques in DWI, diffusion tensor imaging (DTI). DTI is unable to resolve complex configurations of fiber tracts, limiting its utility for constructing detailed, anatomically-informed models of brain function. In contrast, our analyses reproduce known neuroanatomy with precision and accuracy. This advantage is partly due to data acquisition procedures: while many DTI protocols measure diffusion in a small number of directions (e.g., 6 or 12), we employ a diffusion spectrum imaging (DSI)^{1, 2} protocol which assesses diffusion in 257 directions and at a range of magnetic gradient strengths. Moreover, DSI data allow us to use more sophisticated methods for reconstructing acquired data. In two experiments (visual attention and face perception), tractography reveals that co-active areas of the human brain are anatomically connected, supporting extant hypotheses that they form functional networks. DWI allows us to create a "circuit diagram" and reproduce it on an individual-subject basis, for the purpose of monitoring task-relevant brain activity in networks of interest.     

NODDI and Tensor-Based Microstructural Indices as Predictors of Functional Connectivity

In Diffusion Weighted MR Imaging (DWI), the signal is affected by the biophysical properties of neuronal cells and their relative placement, as well as extra-cellular tissue compartments. Typically, microstructural indices, such as fractional anisotropy (FA) and mean diffusivity (MD), are based on a tensor model that cannot disentangle the influence of these parameters. Recently, Neurite Orientation Dispersion and Density Imaging (NODDI) has exploited multi-shell acquisition protocols to model the diffusion signal as the contribution of three tissue compartments. NODDI microstructural indices, such as intra-cellular volume fraction (ICVF) and orientation dispersion index (ODI) are directly related to neuronal density and orientation dispersion, respectively. One way of examining the neurophysiological role of these microstructural indices across neuronal fibres is to look into how they relate to brain function. Here we exploit a statistical framework based on sparse Canonical Correlation Analysis (sCCA) and randomised Lasso to identify structural connections that are highly correlated with resting-state functional connectivity measured with simultaneous EEG-fMRI. Our results reveal distinct structural fingerprints for each microstructural index that also reflect their inter-relationships.     

Episodic Memory in Detoxified Alcoholics: Contribution of Grey Matter Microstructure Alteration

Even though uncomplicated alcoholics may likely have episodic memory deficits, discrepancies exist regarding to the integrity of brain regions that underlie this function in healthy subjects. Possible relationships between episodic memory and 1) brain microstructure assessed by magnetic resonance diffusion tensor imaging (DTI), 2) brain volumes assessed by voxel-based morphometry (VBM) were investigated in uncomplicated, detoxified alcoholics.Diffusion and morphometric analyses were performed in 24 alcohol dependent men without neurological or somatic complications and in 24 healthy men. The mean apparent coefficient of diffusion (ADC) and grey matter volumes were measured in the whole brain. Episodic memory performance was assessed using a French version of the Free and Cued Selective Reminding Test (FCSRT). Correlation analyses between verbal episodic memory, brain microstructure, and brain volumes were carried out using SPM2 software.In those with alcohol dependence, higher ADC was detected mainly in frontal, temporal and parahippocampal regions, and in the cerebellum. In alcoholics, regions with higher ADC typically also had lower grey matter volume. Low verbal episodic memory performance in alcoholism was associated with higher mean ADC in parahippocampal areas, in frontal cortex and in the left temporal cortex; no correlation was found between regional volumes and episodic memory scores. Regression analyses for the control group were not significant.These findings support the hypothesis that regional microstructural but no macrostructural alteration of the brain might be responsible, at least in part, for episodic memory deficits in alcohol dependence.     

研究报告: 小动物高分辨扩散磁共振成像数据分析方法

扩散磁共振成像(dMRI)是一种非侵入性的、能提供生物体内水分子扩散运动相关信息的成像技术,可用于检测神经纤维微观结构的变化．dMRI的出现为大脑结构与功能研究提供了全新的检测手段．过去的20年中,dMRI在实验方法和临床应用上均取得了重大进展．然而dMRI应用在基于动物模型的临床前脑成像研究中却并不常见．本文针对dMRI在临床前脑成像研究中的应用,建立了系列针对小动物高分辨dMRI数据的分析方法：a．构建了大鼠高分辨dMRI图像模板;b．实现了适用于小动物研究的基于体素的统计分析(VBA)方法与基于纤维束的空间统计分析(TBSS)方法;c．实现了小动物脑白质纤维束的确定性与概率性跟踪．这些方法的实现不仅能为小动物脑dMRI研究提供统一的图像模板与完善的计算方法,还将大大促进dMRI技术在小动物脑成像研究中的应用．     

MR diffusion tensor spectroscopy and imaging.

This paper describes a new NMR imaging modality--MR diffusion tensor imaging. It consists of estimating an effective diffusion tensor, Deff, within a voxel, and then displaying useful quantities derived from it. We show how the phenomenon of anisotropic diffusion of water (or metabolites) in anisotropic tissues, measured noninvasively by these NMR methods, is exploited to determine fiber tract orientation and mean particle displacements. Once Deff is estimated from a series of NMR pulsed-gradient, spin-echo experiments, a tissue's three orthotropic axes can be determined. They coincide with the eigenvectors of Deff, while the effective diffusivities along these orthotropic directions are the eigenvalues of Deff. Diffusion ellipsoids, constructed in each voxel from Deff, depict both these orthotropic axes and the mean diffusion distances in these directions. Moreover, the three scalar invariants of Deff, which are independent of the tissue's orientation in the laboratory frame of reference, reveal useful information about molecular mobility reflective of local microstructure and anatomy. Inherently tensors (like Deff) describing transport processes in anisotropic media contain new information within a macroscopic voxel that scalars (such as the apparent diffusivity, proton density, T1, and T2) do not.     

Bayesian regularization of diffusion tensor images

Diffusion tensor imaging (DTI) is a powerful tool in the study of the course of nerve fiber bundles in the human brain. Using DTI, the local fiber orientation in each image voxel can be described by a diffusion tensor which is constructed from local measurements of diffusion coefficients along several directions. The measured diffusion coefficients and thereby the diffusion tensors are subject to noise, leading to possibly flawed representations of the 3-dimensional (3D) fiber bundles. In this paper, we develop a Bayesian procedure for regularizing the diffusion tensor field, fully utilizing the available 3D information of fiber orientation. The use of the procedure is exemplified on synthetic and in vivo data.     

Optimization of in vivo high-resolution DTI of non-human primates on a 3T human scanner

Magnetic resonance (MR) diffusion tensor imaging (DTI) has emerged as a unique technique to reveal small anatomical structures of brain by characterizing the diffusion process of water molecules within an image voxel. Combined with fiber tractography techniques, DTI can be further used to reveal white matter fibers and connectivity in the brain non-invasively. The non-human primate brain study provides important supplemental means for human brain exploration since the two species share close anatomical and functional similarities. There is therefore increasing interest in in vivo non-human primate DTI studies. However, several technical challenges need to be addressed to perform non-human primate brain DTI and fiber tractography. We have established an imaging protocol together with a post-acquisition procedure for high-resolution in vivo non-human primate DTI studies using a 3T human clinical scanner. Data acquired with this procedure is appropriate for accurate diffusion tensor quantification and fiber tractography, and is accessible within an acceptable scan time. We investigated in detail the effects of spatial resolution and SNR on diffusion tensor-derived quantities and fiber tractography. Our results should be of general utility for implementation of in vivo non-human primate DTI studies.     

Reliability and Repeatability of Quantitative Tractography Methods for Mapping Structural White Matter Connectivity in Preterm and Term Infants at Term-Equivalent Age

Premature infants exhibit widespread insults and delays in white matter maturation that can be sensitively detected early using diffusion tensor imaging. Diffusion tensor tractography facilitates in vivo visualization of white matter tracts and has the potential to be more sensitive than simpler two-dimensional DTI-based measures. However, the reliability and reproducibility of performing tractography for major white matter tracts in preterm infants is not known. The main objective of our study was to develop highly reliable and repeatable methods for ten white matter tracts in extremely low birth weight infants (birth weight ≤1000 g) at term-equivalent age. To demonstrate clinical utility, we also compared fiber microstructural and macrostructural parameters between preterm and healthy term controls. Twenty-nine ELBW infants and a control group of 15 healthy term newborns were studied. A team of researchers experienced in neuroanatomy/neuroimaging established the manual segmentation protocol based on a priori anatomical knowledge and an extensive training period to identify sources of variability. Intra- and inter-rater reliability and repeatability was tested using intra-class correlation coefficient, within-subject standard deviation (SD), repeatability, and Dice similarity index. Our results support our primary goal of developing highly reliable and reproducible comprehensive methods for manual segmentation of 10 white matter tracts in ELBW infants. The within-subject SD was within 1–2% and repeatability within 3–7% of the mean values for all 10 tracts. The intra-rater Dice index was excellent with a range of 0.97 to 0.99, and as expected, the inter-rater Dice index was lower (range: 0.80 to 0.91), but still within a very good reliability range. ELBW infants exhibited fewer fiber numbers and/or abnormal microstructure in a majority of the ten quantified tracts, consistent with injury/delayed development. This protocol could serve as a valuable tool for prompt evaluation of the impact of neuroprotective therapies and as a prognostic biomarker for neurodevelopmental impairments.     

Cortical Grey Matter and Subcortical White Matter Brain Microstructural Changes in Schizophrenia Are Localised and Age Independent: A Case-Control Diffusion Tensor Imaging Study

It is still unknown whether the structural brain impairments that characterize schizophrenia (SZ) worsen during the lifetime. Here, we aimed to describe age-related microstructural brain changes in cortical grey matter and subcortical white matter of patients affected by SZ. In this diffusion tensor imaging study, we included 69 patients diagnosed with SZ and 69 healthy control (HC) subjects, age and gender matched. We carried out analyses of covariance, with diagnosis as fixed factor and brain diffusion-related parameters as dependent variables, and controlled for the effect of education. White matter fractional anisotropy decreased in the entire age range spanned (18–65 years) in both SZ and HC and was significantly lower in younger patients with SZ, with no interaction (age by diagnosis) effect in fiber tracts including corpus callosum, corona radiata, thalamic radiations and external capsule. Also, grey matter mean diffusivity increased in the entire age range in both SZ and HC and was significantly higher in younger patients, with no age by diagnosis interaction in the left frontal operculum cortex, left insula and left planum polare and in the right temporal pole and right intracalcarine cortex. In individuals with SZ we found that localized brain cortical and white matter subcortical microstructural impairments appear early in life but do not worsen in the 18–65 year age range.     

Mapping traumatic axonal injury using diffusion tensor imaging: correlations with functional outcome

Background

Traumatic brain injury is a major cause of morbidity and mortality worldwide. Ameliorating the neurocognitive and physical deficits that accompany traumatic brain injury would be of substantial benefit, but the mechanisms that underlie them are poorly characterized. This study aimed to use diffusion tensor imaging to relate clinical outcome to the burden of white matter injury.

Methodology/Principal Findings

Sixty-eight patients, categorized by the Glasgow Outcome Score, underwent magnetic resonance imaging at a median of 11.8 months (range 6.6 months to 3.7 years) years post injury. Control data were obtained from 36 age-matched healthy volunteers. Mean fractional anisotropy, apparent diffusion coefficient (ADC), and eigenvalues were obtained for regions of interest commonly affected in traumatic brain injury. In a subset of patients where conventional magnetic resonance imaging was completely normal, diffusion tensor imaging was able to detect clear abnormalities. Significant trends of increasing ADC with worse outcome were noted in all regions of interest. In the white matter regions of interest worse clinical outcome corresponded with significant trends of decreasing fractional anisotropy.

Conclusions/Significance

This study found that clinical outcome was related to the burden of white matter injury, quantified by diffusivity parameters late after traumatic brain injury. These differences were seen even in patients with the best outcomes and patients in whom conventional magnetic resonance imaging was normal, suggesting that diffusion tensor imaging can detect subtle injury missed by other techniques. An improved in vivo understanding of the pathology of traumatic brain injury, including its distribution and extent, may enhance outcome evaluation and help to provide a mechanistic basis for deficits that remain unexplained by other approaches.     

磁共振波谱成像结合扩散加权成像在脑胶质瘤及脑转移瘤鉴别诊断中的意义

目的:评估磁共振波谱成像(Proton Magnetic Resonance Spectroscopy,1H-MRS)联合磁共振扩散加权成像(Diffusion Weighted Imaging,DWI)在鉴别脑胶质瘤及孤立的脑转移瘤中的作用。方法:应用3.0T磁共振扫描仪,对临床手术确诊及组织病理学诊断证实的49例脑肿瘤患者(35例多形性胶质母细胞瘤,14例脑转移瘤)进行常规磁共振成像、磁共振波谱成像及磁共振扩散加权成像,并并对获得的数据进一步测量瘤内及瘤周区的代谢比、N-乙酰天门冬氨酸(NAA)、胆碱(Cho)、肌酸(Cr)值以及表观弥散系数(ADC值),分析两肿瘤组之间不同参数的统计学差异。此外,我们研究了感兴趣区域(ROI)的大小对肿瘤区域的病变扩散性能潜在影响。结果:胶质母细胞瘤瘤周N-乙酰天门冬氨酸(NAA)、肌酸(Cr),胆碱(Cho)/Cr,Cho/NAA和r CBV显著高于颅内转移瘤(P0.05);ADC值在两肿瘤组之间无显著差异(P0.05)。结论:在瘤周区1H-MRS有助于鉴别胶质母细胞瘤与单发的脑转移瘤。在瘤内扩散性的定量特性依赖ROI大小的设置。     

Differences in Brain Morphological Findings between Narcolepsy with and without Cataplexy

Objective

Maps of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) obtained by diffusion tensor imaging (DTI) can detect microscopic axonal changes by estimating the diffusivity of water molecules using magnetic resonance imaging (MRI). We applied an MRI voxel-based statistical approach to FA and ADC maps to evaluate microstructural abnormalities in the brain in narcolepsy and to investigate differences between patients having narcolepsy with and without cataplexy.

Methods

Twelve patients with drug-naive narcolepsy with cataplexy (NA/CA), 12 with drug-naive narcolepsy without cataplexy (NA w/o CA) and 12 age-matched healthy normal controls (NC) were enrolled. FA and ADC maps for these 3 groups were statistically compared by using voxel-based one-way ANOVA. In addition, we investigated the correlation between FA and ADC values and clinical variables in the patient groups.

Results

Compared to the NC group, the NA/CA group showed higher ADC values in the left inferior frontal gyrus and left amygdala, and a lower ADC value in the left postcentral gyrus. The ADC value in the right inferior frontal gyrus and FA value in the right precuneus were higher for NA/CA group than for the NA w/o CA group. However, no significant differences were observed in FA and ADC values between the NA w/o CA and NC groups in any of the areas investigated. In addition, no correlation was found between the clinical variables and ADC and FA values of any brain areas in these patient groups.

Conclusions

Several microstructural changes were noted in the inferior frontal gyrus and amygdala in the NA/CA but not in the NA w/o CA group. These findings suggest that these 2 narcolepsy conditions have different pathological mechanisms: narcolepsy without cataplexy form appears to be a potentially broader condition without any significant brain imaging differences from normal controls.     

Efficacy of Distortion Correction on Diffusion Imaging: Comparison of FSL Eddy and Eddy_Correct Using 30 and 60 Directions Diffusion Encoding

Diffusion imaging is a unique noninvasive tool to detect brain white matter trajectory and integrity in vivo. However, this technique suffers from spatial distortion and signal pileup or dropout originating from local susceptibility gradients and eddy currents. Although there are several methods to mitigate these problems, most techniques can be applicable either to susceptibility or eddy-current induced distortion alone with a few exceptions. The present study compared the correction efficiency of FSL tools, “eddy_correct” and the combination of “eddy” and “topup” in terms of diffusion-derived fractional anisotropy (FA). The brain diffusion images were acquired from 10 healthy subjects using 30 and 60 directions encoding schemes based on the electrostatic repulsive forces. For the 30 directions encoding, 2 sets of diffusion images were acquired with the same parameters, except for the phase-encode blips which had opposing polarities along the anteroposterior direction. For the 60 directions encoding, non–diffusion-weighted and diffusion-weighted images were obtained with forward phase-encoding blips and non–diffusion-weighted images with the same parameter, except for the phase-encode blips, which had opposing polarities. FA images without and with distortion correction were compared in a voxel-wise manner with tract-based spatial statistics. We showed that images corrected with eddy and topup possessed higher FA values than images uncorrected and corrected with eddy_correct with trilinear (FSL default setting) or spline interpolation in most white matter skeletons, using both encoding schemes. Furthermore, the 60 directions encoding scheme was superior as measured by increased FA values to the 30 directions encoding scheme, despite comparable acquisition time. This study supports the combination of eddy and topup as a superior correction tool in diffusion imaging rather than the eddy_correct tool, especially with trilinear interpolation, using 60 directions encoding scheme.     

Characterization of central nervous system structures by magnetic resonance diffusion anisotropy

Diffusion-weighted magnetic resonance imaging (MRI) provides information about tissue water diffusion. Diffusion anisotropy, which can be measured with diffusion tensor MRI, is a quantitative measure of the directional dependence of the diffusion restriction that is introduced by biological structures such as nerve fibers. Diffusion tensor MRI data was obtained in the brain, brain stem, and cervical spinal cord. For each region, scans were performed in four normal volunteers. Fractional anisotropy (FA), an index of diffusion anisotropy, was measured within regions of interest located in the corpus callosum, capsula interna, thalamus, caudate nucleus, putamen, brain cortex, pyramidal tract of the medulla, accessory olivary nucleus, dorsal olivary nucleus, inferior olivary nucleus, spinal white and gray matter. The highest FA value was measured in the corpus callosum (81 +/- 3%). The values of the other areas decreased in the following order: pyramidal tract in the medulla (72 +/- 1%), spinal white matter (65 +/- 4%), capsula interna (62 +/- 3%), accessory olivary nucleus (36 +/- 2%), spinal gray matter (35 +/- 5%), dorsal olivary nucleus in the medulla (29 +/- 2%), thalamus (28 +/- 2%), inferior olivary nucleus (15 +/- 2%), putamen (13 +/- 2%), caudate nucleus (13 +/- 2%), and brain cortex (9 +/- 1%). Our results indicate that the underlying fiber architecture, fiber density, and uniformity of nerve fiber direction affect anisotropy values of the various structures. Characterization of various central nervous system structures with diffusion anisotropy is possible and may be useful to monitor degenerative diseases in the central nervous system.