Applications of diffusion-weighted and diffusion tensor MRI to white matter diseases - a review

Structure-specific statistical mapping of white matter tracts

We present a new model-based framework for the statistical analysis of diffusion imaging data associated with specific white matter tracts. The framework takes advantage of the fact that several of the major white matter tracts are thin sheet-like structures that can be effectively modeled by medial representations. The approach involves segmenting major tracts and fitting them with deformable geometric medial models. The medial representation makes it possible to average and combine tensor-based features along directions locally perpendicular to the tracts, thus reducing data dimensionality and accounting for errors in normalization. The framework enables the analysis of individual white matter structures, and provides a range of possibilities for computing statistics and visualizing differences between cohorts. The framework is demonstrated in a study of white matter differences in pediatric chromosome 22q11.2 deletion syndrome.

Focal white matter changes in spasmodic dysphonia: a combined diffusion tensor imaging and neuropathological study

Spasmodic dysphonia is a neurological disorder characterized by involuntary spasms in the laryngeal muscles during speech production. Although the clinical symptoms are well characterized, the pathophysiology of this voice disorder is unknown. We describe here, for the first time to our knowledge, disorder-specific brain abnormalities in these patients as determined by a combined approach of diffusion tensor imaging (DTI) and postmortem histopathology. We used DTI to identify brain changes and to target those brain regions for neuropathological examination. DTI showed right-sided decrease of fractional anisotropy in the genu of the internal capsule and bilateral increase of overall water diffusivity in the white matter along the corticobulbar/corticospinal tract in 20 spasmodic dysphonia patients compared to 20 healthy subjects. In addition, water diffusivity was bilaterally increased in the lentiform nucleus, ventral thalamus and cerebellar white and grey matter in the patients. These brain changes were substantiated with focal histopathological abnormalities presented as a loss of axonal density and myelin content in the right genu of the internal capsule and clusters of mineral depositions, containing calcium, phosphorus and iron, in the parenchyma and vessel walls of the posterior limb of the internal capsule, putamen, globus pallidus and cerebellum in the postmortem brain tissue from one patient compared to three controls. The specificity of these brain abnormalities is confirmed by their localization, limited only to the corticobulbar/corticospinal tract and its main input/output structures. We also found positive correlation between the diffusivity changes and clinical symptoms of spasmodic dysphonia (r = 0.509, P = 0.037). These brain abnormalities may alter the central control of voluntary voice production and, therefore, may underlie the pathophysiology of this disorder.

Corticospinal dysgenesis and upper-limb deficits in congenital hemiplegia: a diffusion tensor imaging study

OBJECTIVES

Precision grasping critically relies on the integrity of the corticospinal tract as evidenced in congenital hemiplegia by the correlation found between corticospinal dysgenesis and hand-movement deficits. Therefore, corticospinal dysgenesis could be used to anticipate upper-limb deficits in young infants with congenital hemiplegia. However, most studies have quantified corticospinal dysgenesis by measuring the cross-sectional area of cerebral peduncles on T1 MRI, a measure biased by other structures present in the peduncles. The purpose of this study was to evaluate the extent to which this may have hampered the conclusions of previous studies. We also aimed to investigate the relationship between upper-limb deficits and a more accurate measure of corticospinal dysgenesis to provide a tool for anticipating upper-limb deficits in infants with congenital hemiplegia.

METHODS

To address this issue, we measured corticospinal tract areas in 12 patients with congenital hemiplegia and 12 matched control subjects by using the diffusion tensor imaging technique. Corticospinal dysgenesis was quantified by computing a symmetry index between the area of the contralateral and ipsilateral corticospinal tracts. This value was then compared with that resulting from the conventional MRI method.

RESULTS

The symmetry indexes gathered with these 2 methods were highly correlated, although the diffusion tensor imaging symmetry indexes were significantly smaller. This indicates that, in patients with congenital hemiplegia, the conventional MRI measurement has led to a systematic underestimate of corticospinal dysgenesis. These 2 estimates of corticospinal dysgenesis were also correlated with upper-limb impairments and disabilities. Although the symmetry index computed from peduncle measurements was correlated solely with deficits in stereognosis, the diffusion tensor imaging index correlated with stereognosis, digital and manual dexterities, and ABILHAND-Kids, a measure of manual ability in daily life activities.

CONCLUSIONS

The diffusion tensor imaging symmetry index provides a useful prognostic tool for anticipating upper-limb deficits and their consequences in daily life activities.

Diffusion tensor imaging in children with periventricular leukomalacia: variability of injuries to white matter tracts

BACKGROUND AND PURPOSE

Conventional MR imaging shows evidence of brain injury and/or maldevelopment in 70%-90% of children with cerebral palsy (CP), though its capability to identify specific white matter tract injury is limited. The great variability of white matter lesions in CP already demonstrated by postmortem studies is thought to be one of the reasons why response to treatment is so variable. Our hypothesis is that diffusion tensor imaging (DTI) is a suitable technique to provide in vivo characterization of specific white matter tract lesions in children with CP associated with periventricular leukomalacia (PVL).

MATERIALS AND METHODS

In this study, 24 children with CP associated with PVL and 35 healthy controls were evaluated with DTI. Criteria for identification of 26 white matter tracts on the basis of 2D DTI color-coded maps were established, and a qualitative scoring system, based on visual inspection of the tracts in comparison with age-matched controls, was used to grade the severity of abnormalities. An ordinal grading system (0=normal, 1=abnormal, 2=severely abnormal or absent) was used to score each white matter tract.

RESULTS

There was marked variability in white matter injury pattern in patients with PVL, with the most frequent injury to the retrolenticular part of the internal capsule, posterior thalamic radiation, superior corona radiata, and commissural fibers.

CONCLUSION

DTI is a suitable technique for in vivo assessment of specific white matter lesions in patients with PVL and, thus, a potentially valuable diagnostic tool. The tract-specific evaluation revealed a family of tracts that are highly susceptible in PVL, important information that can potentially be used to tailor treatment options in the future.

Impact of an improved combination of signals from array coils in diffusion tensor imaging

An improved method for the combination of signals from array coils is presented as a way to reduce the influence of the noise floor on the estimation of diffusion tensor imaging (DTI) parameters. By an optimized combination of signals from the array channels and complex averaging of measurements, this method leads to a significant reduction of the noise bias. This combination algorithm allows computation of accurate tensors by using the simple two point method and is shown to provide results similar to the ones obtained using the standard signal combination and a nonlinear regression method with noise parameter estimation. In many applications, the use of this combination method would result in a scan time reduction in comparison to the current standard. The effects of the improved combination on diffusion decay curves, fractional anisotropy maps, and apparent diffusion coefficient (ADC) profiles are demonstrated.

High-dimensional spatial normalization of diffusion tensor images improves the detection of white matter differences: an example study using amyotrophic lateral sclerosis

Spatial normalization of diffusion tensor images plays a key role in voxel-based analysis of white matter (WM) group differences. Currently, it has been achieved using low-dimensional registration methods in the large majority of clinical studies. This paper aims to motivate the use of high-dimensional normalization approaches by generating evidence of their impact on the findings of such studies. Using an ongoing amyotrophic lateral sclerosis (ALS) study, we evaluated three normalization methods representing the current range of available approaches: low-dimensional normalization using the fractional anisotropy (FA), high-dimensional normalization using the FA, and high-dimensional normalization using full tensor information. Each method was assessed in terms of its ability to detect significant differences between ALS patients and controls. Our findings suggest that inadequate normalization with low-dimensional approaches can result in insufficient removal of shape differences which in turn can confound FA differences in a complex manner, and that utilizing high-dimensional normalization can both significantly minimize the confounding effect of shape differences to FA differences and provide a more complete description of WM differences in terms of both size and tissue architecture differences. We also found that high-dimensional approaches, by leveraging full tensor features instead of tensor-derived indices, can further improve the alignment of WM tracts.

Effects of signal-to-noise ratio on the accuracy and reproducibility of diffusion tensor imaging-derived fractional anisotropy, mean diffusivity, and principal eigenvector measurements at 1.5 T

PURPOSE

To develop an experimental protocol to calculate the precision and accuracy of fractional anisotropy (FA), mean diffusivity (MD), and the orientation of the principal eigenvector (PEV) as a function of the signal-to-noise ratio (SNR) in vivo.

MATERIALS AND METHODS

A healthy male volunteer was scanned in three separate scanning sessions, yielding a total of 45 diffusion tensor imaging (DTI) scans. To provide FA, MD, and PEV as a function of SNR, sequential scans from a scan session were grouped into nonintersecting sets. Analysis of the accuracy and precision of the DTI-derived contrasts was done in both a voxel-wise and region of interest (ROI)-based manner.

RESULTS

An upward bias of FA and no significant bias in MD were present as SNR decreased, confirming results from simulation-based studies. Notably, while the precision of the PEV became worse at low SNR, no bias in the PEV orientation was observed. Overall, an accurate and precise quantification of FA values in GM requires substantially more SNR than the quantification of white matter (WM) FA values

CONCLUSION

This study provides guidance for FA, MD, and PEV quantification and a means to investigate the minimal detectable differences within and across scan sessions as a function of SNR.

An empirical characterization of the quality of DTI data and the efficacy of dyadic sorting

Metrics calculated from images acquired using the diffusion tensor imaging (DTI) technique possess a systematic bias that depends on signal-to-noise ratio (SNR). Dyadic sorting provides a simple method for remediating some of this bias within a region(s) of interest (ROI). Although this bias and its removal using dyadic sorting have been studied previously within a theoretical framework, one can employ precise geometric knowledge of microstructures to perform an empirical comparison between expected DTI results and those measured with a scanner. In this project, the biasing effect of low SNR (approximately 1-10) on DTI eigenvalues was measured directly using water-filled capillary structures of two different sizes, and the magnitude of the corrective effect of dyadically sorting eigenvector-eigenvalue pairs was characterized. Multiple DTI series were acquired for determining DTI metrics at eight unique SNR values, using T(R) to vary signal intensity via T(1) contrast. Differences between the second and third eigenvalues, which should be equal for prolate geometry, ranged from approximately 23% to 45% and from 19% to 41% for large and small inner diameter capillaries after sorting eigenvalues by magnitude, and ranged from approximately 1% to 18% and from 1% to 4% after dyadic sorting. A high-resolution DTI series was used to observe the effect of ROI size on dyadic sorting. For restriction of diffusion on the scale of the small capillary at SNR approximately 18, an ROI with > or =50 pixels is adequate to determine fractional anisotropy to 99% accuracy, while larger ROI are required to resolve the two smaller eigenvalues to the same accuracy ( approximately 330-390 pixels). At low values of SNR, the iteration of dyadic sorting is suggested to achieve good accuracy. A method for the incorporation of empirical measurements into a bias-correction map, which would be useful for characterizing uncertainty and for reducing systematic bias in DTI data, is introduced.

MR diffusion changes correlate with ultra-structurally defined axonal degeneration in murine optic nerve

Diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) are widely used to investigate central nervous system (CNS) white matter structure and pathology. Changes in principal diffusivities parallel and perpendicular to nerve fibers or axonal tracts have been associated with axonal pathology and de/dysmyelination respectively. However, the ultra-structural properties and the pathological alterations of white matter responsible for diffusivity changes have not been fully elucidated. We examined the relationship between the directional diffusivities and ultra-structural properties in mouse optic nerve using healthy animals, and mice with optic neuritis (ON) that exhibited marked inflammatory changes and moderately severe axonal pathology. Progressive axonal degeneration in ON resulted in a 23% reduction of parallel diffusivity as detected by diffusion MRI (P<10(-5)), but no change in perpendicular diffusivity. Parallel diffusion changes were highly correlated with the total axolemmal cross-sectional area in the pre-chiasmal portion of the optic nerve (r=0.86, P<0.001). This study provides quantitative evidence that reduced parallel diffusivity in the optic nerve correlates significantly with axolemmal cross-sectional area reductions. MRI-based assessment of axonal degeneration in murine ON is feasible and potentially useful for monitoring of neuro-protective therapies in preclinical trials in animals.

Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics

There is much interest in using magnetic resonance diffusion imaging to provide information on anatomical connectivity in the brain by measuring the diffusion of water in white matter tracts. Among the measures, the most commonly derived from diffusion data is fractional anisotropy (FA), which quantifies local tract directionality and integrity. Many multi-subject imaging studies are using FA images to localize brain changes related to development, degeneration and disease. In a recent paper, we presented a new approach, tract-based spatial statistics (TBSS), which aims to solve crucial issues of cross-subject data alignment, allowing localized cross-subject statistical analysis. This works by transforming the data from the centers of the tracts that are consistent across a study's subjects into a common space. In this protocol, we describe the MRI data acquisition and analysis protocols required for TBSS studies of localized change in brain connectivity across multiple subjects.

Numerical simulations of motion-insensitive diffusion imaging based on the distant dipolar field effects

Diffusion weighting in MRI is commonly achieved with the pulsed-gradient spin-echo (PGSE) method. When combined with spin-warping image formation, this method often results in ghosts due to the sample's macroscopic motion. It has been shown experimentally (Kennedy and Zhong, MRM 2004;52:1-6) that these motion artifacts can be effectively eliminated by the distant dipolar field (DDF) method, which relies on the refocusing of spatially modulated transverse magnetization by the DDF within the sample itself. In this report, diffusion-weighted images (DWIs) using both DDF and PGSE methods in the presence of macroscopic sample motion were simulated. Numerical simulation results quantify the dependence of signals in DWI on several key motion parameters and demonstrate that the DDF DWIs are much less sensitive to macroscopic sample motion than the traditional PGSE DWIs. The results also show that the dipolar correlation distance (d(c)) can alter contrast in DDF DWIs. The simulated results are in good agreement with the experimental results reported previously.

On analyzing diffusion tensor images by identifying manifold structure using isomaps

This paper addresses the problem of statistical analysis of diffusion tensor magnetic resonance images (DT-MRI). DT-MRI cannot be analyzed by commonly used linear methods, due to the inherent nonlinearity of tensors, which are restricted to lie on a nonlinear submanifold of the space in which they are defined, namely R6. We estimate this submanifold using the Isomap manifold learning technique and perform tensor calculations using geodesic distances along this manifold. Multivariate statistics used in group analyses also use geodesic distances between tensors, thereby warranting that proper estimates of means and covariances are obtained via calculations restricted to the proper subspace of R6. Experimental results on data with known ground truth show that the proposed statistical analysis method properly captures statistical relationships among tensor image data, and it identifies group differences. Comparisons with standard statistical analyses that rely on Euclidean, rather than geodesic distances, are also discussed.

High b-value diffusion imaging of dementia: Application to vascular dementia and alzheimer disease

Alzheimer's disease (AD) and Vascular Dementia (VaD) are the most common types of dementia and are progressive diseases affecting millions of people. Despite the high sensitivity of MRI to neurological disorders it has not thus far been found to be specific for the detection of either of these pathologies. In the present study high b-value q-space diffusion-weighted MRI (DWI) was applied to VaD and AD. Controls (N=4), VaD patients (N=8) and AD patients (N=6) were scanned with high b-value DWI, which emphasizes the water component which exhibits restricted diffusion. VaD patients were found to present major WM loss while, in AD, the major pathology found was GM changes, as expected. Also, WM changes in VaD and AD were of a different pattern, more specific to frontal and temporal areas in AD and more widespread in VaD. This pattern of WM changes may be utilized as a diagnosis criterion. Conventional diffusion tensor imaging did not show significant changes between either of the groups and controls. These results demonstrate the potential of high b-value DWI in the diagnosis of dementia.

Single-shot fast spin-echo diffusion tensor imaging of the lumbar spine at 1.5 and 3 T

Diffusion tensor imaging (DTI) of the lumbar spine could improve diagnostic specificity. The purpose of this work was to determine the feasibility of and to validate DTI with single-shot fast spin-echo (SSFSE) for lumbar intervertebral discs at 1.5 and 3 T. Six normal volunteers were scanned with DTI-SSFSE using an eight- and a three-b-value protocol at 1.5 and 3 T, respectively. Apparent diffusion coefficient (ADC) values were computed and validated based on those obtained at 1.5 T from corresponding diffusion tensor scans using line scan diffusion imaging (LSDI), a technique that has been previously validated for use in the spine. Pearson correlation coefficients for LSDI and DTI-SSFSE ADC values were .88 and .89 for 1.5 and 3 T, respectively, with good quantitative agreement according to the Bland-Altman method. Results indicate that DTI-SSFSE is a candidate as a clinical sequence for obtaining diffusion tensor images of the lumbar intervertebral discs with scan times shorter than 4 min.

Relationship between white matter fractional anisotropy and other indices of cerebral health in normal aging: Tract-based spatial statistics study of aging

White matter (WM) fractional anisotropy (FA) is thought to be related to WM integrity and decline in FA is often used as an index of decreasing WM health. However, the relationship of FA to other structural indices of cerebral health has not been well studied. We hypothesized that the decline in WM health will be associated with changes in several other indices of cerebral health. In this manuscript we studied the correlation between whole-brain/hemispheric/corpus callosum FA and gray matter (GM) thickness, sulcal span, and the volume of T2-hyperintense WM in a group of 31 healthy aging individuals (12 males/19 females) aged 57-82 years old. Individual subjects' FA measures were calculated from diffusion tracing imaging (DTI) data using tract-based spatial statistics--an approach specifically designed and validated for voxel-wise multi-subject FA analysis. Age-controlled correlation analysis showed that whole-brain average FA values were significantly and positively correlated with the subject's average GM thickness and negatively correlated with hyperintense WM volume. Intra-hemispheric correlations between FA and other measures of cerebral health had generally greater effect sizes than inter-hemispheric correction, with correlation between left FA and left GM thickness being the most significant (r=0.6, p<0.01). Regional analysis of FA values showed that late-myelinating fiber tracts of the genu of corpus callosum had higher association with other cerebral health indices. These data are consistent with the hypothesis that late-myelinating regions of the brain bear the brunt of age-related degenerative changes.

Magnetic resonance approaches to brain aging and Alzheimer disease-associated neuropathology

The noninvasive, nonradioactive, quantitative nature of magnetic resonance techniques has propelled them to the forefront of neuroscience and neuropsychiatric research. In particular, recent advances have confirmed their enormous potential in patients with Alzheimer disease (AD). Structural and functional magnetic resonance (MR) imaging have demonstrated significant correlation with clinical outcomes and underlying pathology and are used increasingly in the AD clinic. This review will highlight the role of high-resolution structural MR imaging and functional magnetic resonance imaging in the identification of atrophic and hemodynamic changes in AD and their potential as diagnostic biomarkers and surrogates of therapeutic response. Advanced MR techniques based on diffusion, perfusion, and neurochemical abnormalities in the aging brain will be presented briefly. These newer techniques continue to expand our understanding of neuropathology in the aging brain and are likely to play an important clinical role in the future.

High-resolution DTI of a localized volume using 3D single-shot diffusion-weighted STimulated echo-planar imaging (3D ss-DWSTEPI)

Diffusion tensor MRI (DTI) using conventional single-shot (SS) 2D diffusion-weighted (DW)-EPI is subject to severe susceptibility artifacts. Multishot DW imaging (DWI) techniques can reduce these distortions, but they generally suffer from artifacts caused by motion-induced phase errors. Parallel imaging can also reduce the distortions if the sensitivity profiles of the receiver coils allow a sufficiently high reduction factor for the desired field of view (FOV). A novel 3D DTI technique, termed 3D single-shot STimulated EPI (3D ss-STEPI), was developed to acquire high-resolution DW images of a localized region. The new technique completes k-space acquisition of a limited 3D volume after a single diffusion preparation. Because the DW magnetization is stored in the longitudinal direction until readout, it undergoes T(1) rather than T(2) decay. Inner volume imaging (IVI) is used to limit the imaging volume. This reduces the time required for EPI readout of each complete k(x)-k(y) plane, and hence reduces T(2)(*) decay during the readout and T(1) decay between the readout of each k(z). 3D ss-STEPI images appear to be free of severe susceptibility and motion artifacts. 3D ss-STEPI allows high-resolution DTI of limited volumes of interest, such as localized brain regions, cervical spinal cord, optic nerve, and other extracranial organs.

Diffusion Tensor Estimation by Maximizing Rician Likelihood

Diffusion tensor imaging (DTI) is widely used to characterize white matter in health and disease. Previous approaches to the estimation of diffusion tensors have either been statistically suboptimal or have used Gaussian approximations of the underlying noise structure, which is Rician in reality. This can cause quantities derived from these tensors - e.g., fractional anisotropy and apparent diffusion coefficient - to diverge from their true values, potentially leading to artifactual changes that confound clinically significant ones. This paper presents a novel maximum likelihood approach to tensor estimation, denoted Diffusion Tensor Estimation by Maximizing Rician Likelihood (DTEMRL). In contrast to previous approaches, DTEMRL considers the joint distribution of all observed data in the context of an augmented tensor model to account for variable levels of Rician noise. To improve numeric stability and prevent non-physical solutions, DTEMRL incorporates a robust characterization of positive definite tensors and a new estimator of underlying noise variance. In simulated and clinical data, mean squared error metrics show consistent and significant improvements from low clinical SNR to high SNR. DTEMRL may be readily supplemented with spatial regularization or a priori tensor distributions for Bayesian tensor estimation.

Mixtures of Gaussians on tensor fields for DT-MRI segmentation

In this paper, an original approach for the segmentation of tensor fields is proposed. Based on the modeling of the data by means of Gaussian mixtures directly in the tensor domain, this technique presents a wide range of applications in medical image processing, particularly for Diffusion Tensor Magnetic Resonance Imaging (DT-MRI). The performance of the segmentation method proposed is shown through the segmentation of the corpus callosum from a dataset of 32 DT-MRI volumes. Comparison with a recent and related segmentation approach is favorable to our method, showing its capability for the automatic extraction of anatomical structures in the white matter.

Diffusion tensor imaging of post mortem multiple sclerosis brain

Magnetic resonance imaging (MRI) is being used to probe the central nervous system (CNS) of patients with multiple sclerosis (MS), a chronic demyelinating disease. Conventional T₂-weighted MRI (cMRI) largely fails to predict the degree of patients' disability. This shortcoming may be due to poor specificity of cMRI for clinically relevant pathology. Diffusion tensor imaging (DTI) has shown promise to be more specific for MS pathology. In this study we investigated the association between histological indices of myelin content, axonal count and gliosis, and two measures of DTI (mean diffusivity [MD] and fractional anisotropy [FA]), in unfixed post mortem MS brain using a 1.5-T MR system. Both MD and FA were significantly lower in post mortem MS brain compared to published data acquired in vivo. However, the differences of MD and FA described in vivo between white matter lesions (WMLs) and normal-appearing white matter (NAWM) were retained in this study of post mortem brain: average MD in WMLs was 0.35 × 10^− 3 mm²/s (SD, 0.09) versus 0.22 (0.04) in NAWM; FA was 0.22 (0.06) in WMLs versus 0.38 (0.13) in NAWM. Correlations were detected between myelin content (Tr_myelin) and (i) FA (r = − 0.79, p < 0.001), (ii) MD (r = 0.68, p < 0.001), and (iii) axonal count (r = − 0.81, p < 0.001). Multiple regression suggested that these correlations largely explain the apparent association of axonal count with (i) FA (r = 0.70, p < 0.001) and (ii) MD (r = − 0.66, p < 0.001). In conclusion, this study suggests that FA and MD are affected by myelin content and – to a lesser degree – axonal count in post mortem MS brain.

Childhood white matter disorders: quantitative MR imaging and spectroscopy

PURPOSE

To prospectively investigate whether quantitative magnetic resonance (MR) parameters, including magnetization transfer ratio (MTR), apparent diffusion coefficient (ADC), fractional anisotropy (FA), and MR spectroscopic metabolite concentrations, allow for discrimination between different types of pathologic conditions that underlie signal intensity abnormalities in white matter.

MATERIALS AND METHODS

Institutional review board approval and informed consent were obtained. Forty-one patients (19 male, 22 female; mean age, 15.4 years) and 41 control subjects (25 male, 16 female; mean age, 11.3 years) were included. Twelve patients had a hypomyelinating disorder; 14, a demyelinating disorder; five, a disorder characterized by myelin vacuolation; and 10, a disorder characterized by cystic degeneration. Regions of interest were selected within the parietal white matter and were transferred to the corresponding sections of the generated ADC, FA, and MTR maps to extract quantitative measurements. Linear discriminant analysis and univariate analysis of covariance were used for statistical evaluation.

RESULTS

Linear discriminant analysis showed that 95% of patients were correctly classified by using total creatine, choline-containing compounds, myo-inositol, MTR, and ADC. In the hypomyelination group, all MR parameters were close to normal, with the exception of elevated total creatine (P = .03) and myo-inositol (P < .001) levels and decreased MTR values (P < .001). In the demyelination group, the levels of choline-containing compounds (P = .02) and myo-inositol (P < .001) were highly elevated. In the myelin vacuolation and cystic degeneration groups, high ADC values (P < .001) and variable decreases in all MR spectroscopic metabolites were seen. MTR was significantly reduced (P < .001) in the cystic degeneration group.

CONCLUSION

Quantitative MR techniques can be used to discriminate between different types of white matter disorders and to classify white matter lesions of unknown origin with respect to underlying pathologic conditions.

[Primary central nervous system degeneration in elderly patients. Characteristic imaging features]

Despite further development of new magnetic resonance imaging techniques, e.g., diffusion tensor imaging and 1H magnetic resonance spectroscopy, structural imaging will continue to play a major role in the diagnosis of primary central nervous system degeneration in ageing. Characteristic imaging patterns of multisystem atrophies and primary dementias as well as differential diagnostic features are demonstrated. While such features may have high specificity, their sensitivity is low especially in cross-sectional studies. Longitudinal studies are the optimal method to characterize the dynamic neuroanatomical correlates of the disease. However, according to disease duration and progression, neuroimaging will show increased overlapping and convergence of pathological changes in multisystem atrophy as well as in dementia.

A comparative study on the individual and combined effects of baicalin and jasminoidin on focal cerebral ischemia-reperfusion injury

To compare the individual effects of baicalin and jasminoidin with the combined effect of them on cerebral ischemia-reperfusion injury, and test whether the combined administration of baicalin and jasminoidin can improve the therapeutic effect. Male Sprague-Dawley rats underwent focal cerebral ischemia for 1.5 h and reperfusion for 24 h. Just before reperfusion, tested drugs (baicalin, jasminoidin, a drug combination consisting of baicalin and jasminoidin, or nimodipine) were intravenously treated. Diffusion weighted imaging (DWI) of magnetic resonance imaging (MRI), behavior examination, 2,3,5-triphenyltetrazolium chloride (TTC) staining, histological examination, and real-time PCR for BDNF and caspase-3 were performed. All of the drug treatments could significantly ameliorate the results of TTC and histological examination, and the baicalin/jasminoidin combination did so most prominently. This combination could also significantly ameliorate DWI of MRI and behavior examination results, and promote the expression of BDNF and inhibit the expression of caspase-3. On the whole, both baicalin and jasminoidin have a preventive effect against ischemic stroke, although their effects are not very strong. However, the combination of baicalin and jasminoidin can significantly improve their effectiveness. This may be related to its better regulation on the BDNF and caspase-3.

Principles of diffusion tensor imaging and its applications to basic neuroscience research

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 noninvasive 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.

Multiscale white matter fiber tract coregistration: a new feature-based approach to align diffusion tensor data

In this paper an automatic multiscale feature-based rigid-body coregistration technique for diffusion tensor imaging (DTI) based on the local curvature kappa and torsion tau of the white matter (WM) fiber pathways is presented. As a similarity measure, the mean squared difference (MSD) of corresponding fiber pathways in (kappa, tau)-space is chosen. After the MSD is minimized along the arc length of the curve, principal component analysis is applied to calculate the transformation parameters. In addition, a scale-space representation of the space curves is incorporated, resulting in a multiscale robust coregistration technique. This fully automatic technique inherently allows one to apply region of interest (ROI) coregistration, and is adequate for performing both global and local transformations. Simulations were performed on synthetic DT data to evaluate the coregistration accuracy and precision. An in vivo coregistration example is presented and compared with a voxel-based coregistration approach, demonstrating the feasibility and advantages of the proposed technique to align DT data of the human brain.

Use of capillaries in the construction of an MRI phantom for the assessment of diffusion tensor imaging: demonstration of performance

Although diffusion tensor imaging (DTI) shows great potential for the diagnosis of a variety of pathologies, no consensus for an appropriate assessment standard of DTI exists. This study examined the feasibility of using water-filled arrays of glass capillaries to construct a DTI phantom suitable for making repeated and reproducible measurements required in a quality assessment program. Three phantoms were constructed using arrays of capillaries with three inner diameters (23, 48, and 82 microm). Data were acquired using DTI protocols; the fractional anisotropy (FA), mean apparent diffusion coefficient (ADC) and principal eigenvectors of the diffusion tensors were calculated. This study demonstrated four results: (1) echo-planar images show that susceptibility within the capillary arrays does not lead to substantial differences in precessional frequency in regions containing the arrays and neither do the regions show noticeable image distortion; (2) principal eigenvectors of the diffusion tensors agree to within<10.3 degrees of the array orientations; (3) mean FA values (0.18-0.50) and ADC values (1.40-1.93x10-(3) mm2/s) within specified regions of interest are in general agreement with simulations after a simple noise correction; and (4) these array performance characteristics are observable using a typical clinical DTI protocol.

Fornix integrity and hippocampal volume in male schizophrenic patients

BACKGROUND

The hippocampus has been shown to be abnormal in schizophrenia. The fornix is one of the main fiber tracts connecting the hippocampus with other brain regions. Few studies have evaluated the fornix in schizophrenia, however. A focus on fornix abnormalities and their association with hippocampal abnormalities might figure importantly in our understanding of the pathophysiology of schizophrenia.

METHODS

Line-scan diffusion tensor imaging (DTI) was used to evaluate diffusion in the fornix in 24 male patients with chronic schizophrenia and 31 male control subjects. Maps of fractional anisotropy (FA) and mean diffusivity (D(m)), which are indices sensitive to white-matter integrity, were generated to quantify diffusion within the fornix. We used high spatial resolution magnetic resonance imaging (MRI) to measure hippocampal volume.

RESULTS

FA and cross-sectional area of the fornix were significantly reduced in patients compared with control subjects. D(m) was significantly increased, whereas hippocampal volume was bilaterally reduced in patients. Reduced hippocampal volume was correlated with increased mean D(m) and reduced cross-sectional area of the fornix for patients. Patients also showed a significant correlation between reduced scores on neuropsychologic measures of declarative-episodic memory and reduced hippocampal volumes.

CONCLUSIONS

These findings demonstrate a disruption in fornix integrity in patients with schizophrenia.

Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data

There has been much recent interest in using magnetic resonance diffusion imaging to provide information about anatomical connectivity in the brain, by measuring the anisotropic diffusion of water in white matter tracts. One of the measures most commonly derived from diffusion data is fractional anisotropy (FA), which quantifies how strongly directional the local tract structure is. Many imaging studies are starting to use FA images in voxelwise statistical analyses, in order to localise brain changes related to development, degeneration and disease. However, optimal analysis is compromised by the use of standard registration algorithms; there has not to date been a satisfactory solution to the question of how to align FA images from multiple subjects in a way that allows for valid conclusions to be drawn from the subsequent voxelwise analysis. Furthermore, the arbitrariness of the choice of spatial smoothing extent has not yet been resolved. In this paper, we present a new method that aims to solve these issues via (a) carefully tuned non-linear registration, followed by (b) projection onto an alignment-invariant tract representation (the "mean FA skeleton"). We refer to this new approach as Tract-Based Spatial Statistics (TBSS). TBSS aims to improve the sensitivity, objectivity and interpretability of analysis of multi-subject diffusion imaging studies. We describe TBSS in detail and present example TBSS results from several diffusion imaging studies.

Diffusion-weighted imaging in Huntington's disease

Huntington's disease (HD) is an autosomal dominant progressive neurodegenerative disorder that results from an expanded trinucleotide (CAG) repeat on the huntingtin gene. Neurodegeneration in HD affects most prominently the basal ganglia. Therefore, diffusivity was obtained in the basal ganglia and thalamus of 29 patients with early HD and 27 healthy volunteers by means of the trace of the diffusion tensor (Trace(D)). Putaminal, caudate, pallidal, and thalamic Trace(D) values were increased in patients with HD compared with controls. Increased diffusivity in the putamen and caudate nucleus correlated with global functional impairment, CAG repeat length, as well as bicaudate ratio. Diffusion-weighted imaging appears to be a promising surrogate marker for disease severity in HD. Sensitivity to change remains to be established longitudinally.

Brain dysmyelination and recovery assessment by noninvasive in vivo diffusion tensor magnetic resonance imaging

Diffusion tensor magnetic resonance imaging (DT-MRI) was applied for in vivo quantification of myelin loss and regeneration. A transgenic mouse line (Oligo-TTK) expressing a truncated form of the herpes simplex virus 1 thymidine kinase gene (hsv1-tk) in oligodendrocytes was studied along with two induced phenotypes of myelin pathology. Myelin loss and axonal abnormalities differentially affect values of DT-MRI parameters in the brain of transgenic mice. Changes in the anisotropy of the white matter were assessed by calculating and mapping the radial (D perpendicular) and axial (D parallel) water diffusion to axonal tracts and fractional anisotropy (FA). A significant increase in D perpendicular attributed to the lack of myelin was observed in all selected brain white matter tracts in dysmyelinated mice. Lower D parallel values were consistent with the histological observation of axonal modifications, including reduced axonal caliber and overexpression of neurofilaments and III beta-tubulin. We show clearly that myelination and axonal changes play a role in the degree of diffusion anisotropy, because FA was significantly decreased in dysmyelinated brain. Importantly, myelin reparation during brain postnatal development induced a decrease in the magnitude of D( perpendicular) and an increase in FA compared with the same brain before recovery. The progressive increase in D parallel values was attributed to the gain in normal axonal morphology. This regeneration was confirmed by the detection of enlarged oligodendrocyte population, newly formed myelin sheaths around additional axons, and a gradual increase in axonal caliber.

High-resolution DTI with 2D interleaved multislice reduced FOV single-shot diffusion-weighted EPI (2D ss-rFOV-DWEPI)

Diffusion tensor MRI (DTI), using single-shot 2D diffusion weighted-EPI (2D ss-DWEPI), is limited to intracranial (i.c.) applications far from the sinuses and bony structures, due to the severe geometric distortions caused by significant magnetic field inhomogeneities at or near the tissue-air or tissue-bone interfaces. Reducing these distortions in single-shot EPI by shortening the readout period generally requires a reduced field of view (and the potential of wraparound artifact) in the phase-encoding direction and/or reduced spatial resolution. To resolve the problem, a novel 2D reduced FOV single-shot diffusion-weighted EPI (2D ss-rFOV-DWEPI) pulse sequence applicable for high resolution diffusion-weighted MRI of local anatomic regions, such as brainstem, cervical spinal cord, and optic nerve, has been developed. In the proposed technique, time-efficient interleaved acquisition of multiple slices with a limited FOV was achieved by applying an even number of refocusing 180 degrees pulses with the slice-selection gradient applied in the phase-encoding direction. The two refocusing pulses used for each slice acquisition were separated by a short time interval (typically less than 45 ms) required for the 2D EPI echotrain acquisition. The new technique can be useful for high resolution DTI of various anatomies, such as localized brain structures, cervical spinal cord, optic nerve, heart, or other extra-cerebral organ, where conventional 2D ss-DWEPI is limited in usage due to the severity of image distortions.

Influence of SENSE on image properties in high-resolution single-shot echo-planar DTI

Limited spatial resolution is a key obstacle to the study of brain white matter structure with diffusion tensor imaging (DTI). In its frequent implementation with single-excitation spin-echo echo-planar sequences, DTI's ability to resolve small structures is strongly restricted by T2 and T2* decay, B0 inhomogeneity, and limited signal-to-noise ratio (SNR). In this work the influence of sensitivity encoding (SENSE) on diffusion-weighted (DW) image properties is investigated. Computer simulations showed that the PSF becomes narrower with increasing SENSE reduction factors, R, enhancing the intrinsic resolution. After a brief theoretical discussion, we describe the estimation of SNR on a pixel-by-pixel basis as a function of R. The mean image SNR behavior is manifold: SENSE is capable of increasing SNR efficiency by reducing the echo time (TE). Each SNR(R) curve reveals a maximum that depends on the amount of partial Fourier encoding used. The overall best SNR efficiency for an eight-element head coil array and a b-factor of 1000 s/mm2 is achieved at R = 2.1 and partial Fourier encoding of 60%. In vivo tensor maps of volunteers and a patient, with an in-plane resolution of 0.78 x 0.78 mm2, are also presented to demonstrate the practical implementation of the parallel approach.

76-space analysis of grey matter diffusivity: methods and applications

Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) allow in vivo investigation of molecular motion of tissue water at a microscopic level in cerebral gray matter (GM) and white matter (WM). DWI/DTI measure of water diffusion has been proven to be invaluable for the study of many neurodegenerative diseases (e.g., Alzheimer's disease and Creutzfeldt-Jakob disease) that predominantly involve GM. Thus, quantitative analysis of GM diffusivity is of scientific interest and is promised to have a clinical impact on the investigation of normal brain aging and neuropathology. In this paper, we propose an automated framework for analysis of GM diffusivity in 76 standard anatomic subdivisions of gray matter to facilitate studies of neurodegenerative and other gray matter neurological diseases. The computational framework includes three enabling technologies: (1) automatic parcellation of structural MRI GM into 76 precisely defined neuroanatomic subregions ("76-space"), (2) automated segmentation of GM, WM and CSF based on DTI data, and (3) automatic measurement of the average apparent diffusion coefficient (ADC) in each segmented GM subregion. We evaluate and validate this computational framework for 76-space GM diffusivity analysis using data from normal volunteers and from patients with Creutzfeldt-Jakob disease.

Global brain atrophy and corticospinal tract alterations in ALS, as investigated by voxel-based morphometry of 3-D MRI

In ALS, advanced magnetic resonance imaging (MRI) techniques are increasingly used to investigate the underlying pathology. In this study, the technique of voxel-based morphometry (VBM) was applied to 3-D MRI data in ALS patients to localize regional grey and white matter changes. Twenty-two ALS patients (mean age 58+/-9 years) with clinically definite ALS by revised El Escorial criteria were studied. None of the patients had any signs of associated frontotemporal dementia. High-resolution 3-D MRI data sets of the whole brain, collected on a 1.5 T scanner, were analysed by statistical parametric mapping (SPM) and VBM in comparison to an age-matched normal data base consisting of 22 healthy volunteers (mean age 59+/-11 years), for grey matter and white matter segments separately. Global brain atrophy was assessed by calculation of brain parenchymal fractions (BPF). In ALS patients, BPF were significantly reduced compared to controls (p = 0.0003), indicating global brain atrophy. Regional decreases of grey matter density were found in the ALS patients at corrected p<0.01 in the right-hemispheric primary motor cortex (area of the highest Z-score) and in the left medial frontal gyrus. Furthermore, regional white matter alterations were observed along the corticospinal tracts bilaterally and in multiple smaller areas including corpus callosum, cerebellum, frontal and occipital subcortical regions. Besides considerable global atrophy in ALS, the topography of ALS-associated cerebral morphological changes could be mapped using VBM, in particular white matter signal changes along the bilateral corticospinal tracts, but also in extra-motor areas. VBM might be a potential tool to visualize disease progression in future longitudinal studies.

Characterization of displaced white matter by brain tumors using combined DTI and fMRI

In vivo white matter tractography by diffusion tensor imaging (DTI) has become a popular tool for investigation of white matter architecture in the normal brain. Despite some unresolved issues regarding the accuracy of DTI, recent studies applied DTI for delineating white matter organization in the vicinity of brain lesions and especially brain tumors. Apart from the intrinsic limitations of DTI, the tracking of fibers in the vicinity or within lesions is further complicated due to changes in diseased tissue such as elevated water content (edema), tissue compression and degeneration. These changes deform the architecture of the white matter and in some cases prevent definite selection of the seed region of interest (ROI) from which fiber tracking begins. We show here that for displaced fiber systems, the use of anatomical approach for seed ROI selection yields insufficient results. Alternatively, we propose to select the seed points based on functional MRI activations which constrain the subjective seed ROI selection. The results are demonstrated on two major fiber systems: the pyramidal tract and the superior longitudinal fasciculus that connect critical motor and language areas, respectively. The fMRI based seed ROI selection approach enabled a more comprehensive mapping of these fiber systems. Furthermore, this procedure enabled the characterization of displaced white matter using the eigenvalue decomposition of DTI. We show that along the compressed fiber system, the diffusivity parallel to the fiber increases, while that perpendicular to the fibers decreases, leading to an overall increase in the fractional anisotropy index reflecting the compression of the fiber bundle. We conclude that definition of the functional network of a subject with deformed white matter should be done carefully. With fMRI, one can more accurately define the seed ROI for DTI based tractography and to provide a more comprehensive, functionally related, white matter mapping, a very important tool used in pre-surgical mapping.

Tensor deflection (TEND) tractography with adaptive subvoxel stepping

PURPOSE

To develop an adaptive subvoxel stepping scheme, as an adjunct to tensor deflection (TEND) tractography, that automatically adjusts the stepping size by considering the tensor linearity to properly trace fiber bundles in regions with different degrees of tensor anisotropy.

MATERIALS AND METHODS

A theoretical investigation of the TEND algorithm was performed to assess the degree of deflection of the propagation vector toward the major eigenvector. Mathematically generated phantoms (one with curved fibers and the other with crossing fibers) at wide ranges of signal-to-noise ratio (SNR), and human brain images obtained in vivo were used to test the performance of the adaptive stepping algorithm.

RESULTS

The degree of deflection was found to be inversely related to the stepping size. A small stepping size was advantageous for tracing single curved fiber bundles, whereas a large stepping size was beneficial for passing through fiber crossing regions. The performance of the adaptive stepping algorithm was superior to fixed stepping in both situations, leading to an approximately 0.17 voxel of deviation in curved fibers and a nearly 100% successful tracking rate in crossing fibers at typical SNR. Human brain images demonstrated similar results.

CONCLUSION

The adaptive stepping algorithm is a helpful adjunct to TEND tractography.

Measuring injury and repair of myelin and neurons in multiple sclerosis

Neuroprotection in MS needs to be considered in the context of several pathological processes: limitation of acute inflammatory injury to myelin and axons, remyelination, survival of demyelinated axons, and limitation of more diffuse, nonlesional pathology that affects myelin and axons. Advanced MRI techniques are capable of reporting on all of these different pathological features of MS and will be an important aspect of the assessment of neuroprotection strategies in MS, when these become available.

Improved detectability of experimental allergic encephalomyelitis in excised swine spinal cords by high b-value q-space DWI

Experimental allergic encephalomyelitis (EAE) is the primary experimental model of multiple sclerosis (MS), which involves both inflammation and demyelination and is known to be species-dependent. Spinal cord abnormalities were found in more than 80% of postmortem specimens of MS patients. In the present study, T1, T2 and high b-value q-space diffusion-weighted magnetic resonance imaging (MRI) were used, for the first time, to characterize the EAE model in excised swine spinal cords. The MR images were compared with histological staining and clinical scoring. Although all spinal cords were excised from swine with severe or very severe (clinical score between 3 to 5 on a scale of 5) motor impairments, T1- and T2-weighted MRI revealed white matter (WM) abnormalities in only five of the ten EAE diseased spinal cords studied, while high b-value q-space diffusion weighted MRI (q-space DWI) detected WM abnormalities in all diseased spinal cords studied. Interestingly, high b-value q-space DWI was able to detect abnormalities in the normal appearing white matter (NAWM) even in spinal cords where no plaques were identified by the T1- and T2-weighted MR images. Good anatomical correlation was observed between the high b-value q-space MR images and histology. The extent of DWI abnormalities paralleled the clinical scoring and correlated with histology. In addition, areas classified as NAWM by the T1- and T2-weighted MR images that showed abnormalities in the q-space DWI were also found to have abnormal histology. This improved detection level of the EAE model by high b-value q-space DWI over conventional T1-, and T2-weighted MRI is briefly discussed.

Unsupervised identification of white matter tracts in a mouse brain using a directional correlation-based region growing (DCRG) algorithm

The inner product of the major eigenvectors of adjacent pixels, known as the directional correlation (DC), has been used previously as a quantitative index to investigate directional similarity in white matter (WM) tracts. A high degree of directional similarity (i.e., high DC) among pixels within individual WM tracts was observed. Based on this observation, a region growing algorithm was employed to propagate an area from a seed point as a function of the DC threshold (DCt) to manually identify WM tracts in two-dimensional (2D) slices from diffusion tensor imaging (DTI). In the present study, an improved unsupervised DC based region growing (DCRG) method was implemented to reduce the operator-dependent variance and to improve the ease of use of the technique. By employing improved method, a multi-slice DTI data set of an in vivo mouse brain was used to identify the external capsule, visual pathway, and corpus callosum. The resultant WM tracts are computer rendered in three-dimensional (3D) images with anatomical images as structural references. In addition, three sets of ex vivo mouse brain data were used to examine the effects of different slice thickness and the signal-to-noise ratio (SNR) to the outcome of DCRG.

Optic nerve diffusion tensor imaging in optic neuritis

Diffusion tensor magnetic resonance imaging (DT-MRI) provides in vivo information about the pathology of multiple sclerosis lesions. Increases in mean diffusivity (MD) and reductions in fractional anisotropy (FA) have been found and may represent axonal disruption. The optic nerve is an ideal structure for study by DT-MRI but previous clinical studies did not obtain the full diffusion tensor necessary to calculate MD and FA. In this study, a technique that was specifically developed to achieve full diffusion tensor measurements from the optic nerve (zonal oblique multislice (ZOOM) echoplanar imaging) was applied to 25 patients with a single unilateral episode of optic neuritis at least one year previously, and 15 controls. The intraorbital nerves were segmented on non-diffusion-weighted images and the regions of interest transferred to MD, FA, and eigenvalue maps to obtain quantitative data. Quantitative visual testing and electrophysiology were also performed. In affected nerves, mean MD and mean orthogonal eigenvalue lambda( perpendicular) were elevated, and mean FA reduced compared with clinically unaffected contralateral nerves (P < 0.001) and control nerves (P < 0.001). The mean principal eigenvalue lambda\\ was significantly increased in affected nerves compared to contralateral unaffected nerves (P = 0.04) but not compared to control nerves (P = 0.13). There was no association of clinical measures of visual function in affected eyes with the DT-MRI parameters but there was a significant correlation of the whole field visual evoked potential (VEP) amplitude with MD (r = -0.57, P = 0.006) and lambda( perpendicular) (r = -0.56, P = 0.007). These findings suggest that optic nerve DT-MRI measures provide an indication of the structural integrity of axons.

Diffusion Tensor Magnetic Resonance Imaging in Multiple Sclerosis

Multiple sclerosis (MS), a demyelinating disease, occurs principally in the white matter (WM) of the central nervous system. Conventional magnetic resonance imaging (MRI) is sensitive to some, but not all, brain changes associated with MS. Diffusion-weighted imaging (DWI) provides information about water diffusion in tissue and diffusion tensor MRI (DT-MRI) about fiber direction, allowing for the identification of WM abnormalities that are not apparent on conventional MRI images. These techniques can quantitatively characterize the local microstructure of tissues. MS-associated disease processes lead to regions characterized by an increased amount of water diffusion and a decrease in the anisotropy of diffusion direction. These changes have been found to produce different patterns in MS patients presenting different courses of the disease. Changes in water diffusion may allow examination of the type, appearance, enhancement, and location of lesions not readily visible by other means. Ongoing studies of MS are integrating conventional MRI and DT-MRI measures with connectivity-based regional assessment, aiming to provide a better understanding of the nature and the location of WM lesions. This integration and the development of novel image-processing and visualization techniques may improve the understanding of WM architecture and its disruption in MS. This article presents a brief history of DWI, its basic principles and applications in the study of MS, a review of the properties and applications of DT-MRI, and their use in the study of MS. In addition, this article illustrates the methodology for the analysis of DT-MRI in ongoing studies of MS.

Diffusion tensor imaging of subcortical brain injury in patients infected with human immunodeficiency virus

Diffusion tensor imaging (DTI) was used to derive in vivo tissue status measurements of subcortical brain regions that are vulnerable to injury in human immunodeficiency virus (HIV)-infected patients. Quantitative measurements, including the mean diffusivity (MD) and fractional anisotropy (FA), were determined in lateralized basal ganglia (caudate and putamen) and centrum semiovale in 11 well-characterized HIV patients and in 11 control subjects. DTI measurements were examined for patterns of relationship with markers of clinical and cognitive progression. DTI measures acquired in subcortical regions were significantly correlated with loss of function in specific cognitive domains. Significant relationships were identified between measures for putamen and verbal memory (MD), visual memory (FA), working memory (FA), and overall cognitive impairment (MD). Measures for caudate (FA) were significantly correlated with visual memory. Measures for centrum semiovale were significantly correlated with visual memory deficits (MD) and visuoconstruction (FA). Relationships between anisotropy measures and anemia (basal ganglia) and CD4 counts (centrum semiovale) were also observed. Findings from this investigation indicate that DTI is a sensitive tool for correlating neuroanatomic pathologic features with specific cognitive deficits in patients with HIV infection.

Diffusion tensor imaging to study anisotropy in a particular porous system: the trabecular bone network

During the last decade, considerable effort has been invested into the development of diffusion tensor imaging (DTI) mainly used to investigate cerebral morphology. The aim of this paper is to review and to discuss our recent results about high magnetic field DTI application to study spongy bone tissue. Due to its peculiar properties, spongy bone represents a particular porous system sample. Strategies to perform DTI on porous systems and issues linked to DTI outcome interpretation are presented on the basis of our results concerning trabecular bone network characterization.

Diagnostic value of diffusion-weighted magnetic resonance imaging in pediatric cerebral diseases

The purpose of this study was to detect the diagnostic value of diffusion-weighted magnetic resonance imaging in different pediatric cerebral diseases involving the cerebral white and gray matter and to compare the diffusion properties with age-matched normal children. Conventional and diffusion-weighted magnetic resonance imaging were performed in 21 children with various neurologic disorders and 25 normal control subjects. Apparent diffusion coefficients were measured from the brain lesions and 12 normal-appearing white and gray matter areas in the study group. Twelve normal-appearing areas were also measured in the control group. Apparent diffusion coefficient values obtained from the normal subjects were similar to values described in the literature but were significantly different from the control subjects. Apparent diffusion coefficient values for the neurodegenerative disease group (n = 8), the anoxic encephalopathy group (n = 4), the subacute sclerosing panencephalitis group (n = 4), the acute disseminated encephalomyelitis group (n = 3), and the encephalitis group (n = 2) were respectively between 0.29-1.85 x 10(-5) cm2/s, 0.13-1.87 x 10(-5) cm2/s, 0.96-1.57 x 10(-5) cm2/s, 0.49-0.73 x 10(-5) cm2/s, and 0.42-1.50 x 10(-5) cm2/s. Although this study is limited because of the size of the patient sample and disease heterogeneity, diffusion-weighted magnetic resonance imaging provides useful and complementary information regarding the degree of involvement in different pediatric neurologic disorders.

Age-related signal intensity changes in the corpus callosum: assessment with three orthogonal FLAIR images

The presence of age-related hyperintensities of the corpus callosum has not been thoroughly evaluated. Fifty-two patients of 50 years of age or older (mean, 71 years; range, 50-87 years) were included in this study. Fluid-attenuated inversion recovery images were obtained in three orthogonal planes. Periventricular hyperintensities (PVHs) and deep white matter hyperintensities (DWMHs) were graded according to Fazekas' rating scale. Correlations between the presence of hyperintensities in the corpus callosum and age, and the grade of PVH and DWMH were statistically analyzed. PVH was categorized as grade 0 (n=4), grade 1 (n=28), grade 2 (n=10), or grade 3 (n=10). DWMH was categorized as grade 0 (n=4), grade 1 (n=25), grade 2 (n=8), or grade 3 (n=15). Hyperintensity was considered present in the corpus callosum in 31 of the 52 patients (60%). In these 31 patients, PVH was categorized as grade 1 (n=16), grade 2 (n=7), or grade 3 (n=8), while DWMH was categorized as grade 0 (n=1), grade 1 (n=10), grade 2 (n=7), or grade 3 (n=13). The presence of callosal hyperintensities was significantly correlated with age (p=0.001), and with PVH (p=0.04) and DWMH grades (p=0.004). Hyperintensities may be present in the corpus callosum with aging, and are correlated with PVH and DWMH.