In vivo three-dimensional reconstruction of rat brain axonal projections by diffusion tensor imaging

Macroscopic orientation component analysis of brain white matter and thalamus based on diffusion tensor imaging

Diffusion tensor imaging (DTI) can delineate white matter architecture based on fiber orientation. The purpose of this paper is to use the orientation information contained in DTI to study axonal organization of the brain both macroscopically and quantitatively. After performing gray/white matter segmentation using a fractional anisotropy threshold, the white matter can be further decomposed into components composed of tracts oriented along three orthogonal anatomic axes (right-left, superior-inferior, and anterior-posterior). For each component, the volume and MR parameters were quantified. To characterize the axonal architecture of the brain, this technique was applied to the entire brain using a Talairach-based brain parcellation method and to the thalamus by manual segmentation. Reproducibility of this analysis tool was examined by repeating the measurements in the same subject, and individual differences were appreciated from the data acquired in 11 healthy volunteers. Based on the results from these preliminary data sets, this new analysis technique is expected to be an effective tool for macroscopic white matter characterization.

Mapping the orientation of intravoxel crossing fibers based on the phase information of diffusion circular spectrum

A new method is presented to map the orientation of intravoxel crossing fibers by using the phase of the diffusion circular spectrum harmonics. In a previous study [Zhan, W., Gu, H., Xu, S., Silbersweig, D.A., Stern, E., Yang, Y., 2003. Circular spectrum mapping for intravoxel fiber structures based on high angular resolution apparent diffusion coefficients. Magn. Reson. Med. 49, 1077-1088], we demonstrated that the magnitude of the 4th-order harmonic of the diffusion circular spectrum can be used to identify the existence of fiber crossings. However, the orientation of the intravoxel crossing fibers remained unknown. This study extends the diffusion circular spectrum mapping method so that it is able to identify the orientation of the intravoxel crossing fibers by utilizing the phase information of the circular spectrum. In general, the phase of the circular harmonic determines the rotation of the apparent diffusion coefficient (ADC) profile on the sampling circle that is spanned by the major and medium eigenvector of the diffusion tensor and thus can be used to determine the orientation of the crossing fibers. Simulation results show that the regular tensor-based major eigenvector maps have obvious artifacts in the fiber-crossing area, whereas the estimated crossing fibers by the proposed method are much more consistent with the orientation of the actual intravoxel fibers. Diffusion MRI experiments were performed on five healthy human brains using a 3T scanner. The brain regions with fiber crossings were selected by thresholding the magnitudes of the 4th-order circular spectrum map. Intravoxel crossing fibers were estimated by the phase of the 4th-order harmonic for each voxel within these areas. The estimated intravoxel crossing fibers demonstrated a clear consistency with the orientations of fiber tracks in the surrounding tissues, reducing the fiber orientation discontinuity of the regular major eigenvector map.

In vivo diffusion tensor mapping of the brain of squirrel monkey, rat, and mouse using single-shot STEAM MRI

The purpose was to assess the potential of half Fourier diffusion-weighted single-shot STEAM MRI for diffusion tensor mapping of animal brain in vivo. A STEAM sequence with image acquisition times of about 500 ms was implemented at 2.35 T using six gradient orientations and b values of 200, 700, and 1200 s mm(-2). The use of half Fourier phase-encoding increased the signal-to-noise ratio by 45% relative to full Fourier acquisitions. Moreover, STEAM-derived maps of the relative anisotropy and main diffusion direction were completely free of susceptibility-induced signal losses and geometric distortions. Within measuring times of 3 h, the achieved resolution varied from 600x700x1000 microm3 for squirrel monkeys to 140x280x720 microm3 for mice. While in monkeys the accessible white matter fiber connections were comparable to those reported for humans, detectable fiber structures in mice focused on the corpus callosum, anterior commissure, and hippocampal fimbria. In conclusion diffusion-weighted single-shot STEAM MRI allows for in vivo diffusion tensor mapping of the brain of squirrel monkeys, rats, and mice without motion artifacts and susceptibility distortions.

Novel MR contrasts to reveal more about the brain

Twenty percent of patients with refractory focal epilepsy have an undetermined etiologic basis for their epilepsy despite extensive investigation, including optimal MR imaging. Surgical treatment of this group is associated with a less favorable postoperative outcome. Even with improvements in imaging techniques, a proportion of these patients will remain "MR imaging-negative." It is likely, however, that some of the discrete macroscopic focal lesions that are currently occult will be identified by imaging techniques interrogating different microstructural characteristics. Furthermore, these methods may provide pathologic specificity when used in combination. The description and application of these techniques in epilepsy are the focus of this article.

DT-MRI denoising and neuronal fiber tracking

Diffusion tensor imaging can provide the fundamental information required for viewing structural connectivity. However, robust and accurate acquisition and processing algorithms are needed to accurately map the nerve connectivity. In this paper, we present a novel algorithm for extracting and visualizing the fiber tracts in the CNS, specifically in the brain. The automatic fiber tract mapping problem will be solved in two phases, namely a data smoothing phase and a fiber tract mapping phase. In the former, smoothing of the diffusion-weighted data (prior to tensor calculation) is achieved via a weighted TV-norm minimization, which strives to smooth while retaining all relevant detail. For the fiber tract mapping, a smooth 3D vector field indicating the dominant anisotropic direction at each spatial location is computed from the smoothed data. Neuronal fibers are then traced by calculating the integral curves of this vector field. Results are expressed using three modes of visualization: (1) Line integral convolution produces an oriented texture which shows fiber pathways in a planar slice of the data. (2) A streamtube map is generated to present a 3D view of fiber tracts. Additional information, such as degree of anisotropy, can be encoded in the tube radius, or by using color. (3) A particle system form of visualization is also presented. This mode of display allows for interactive exploration of fiber connectivity with no additional preprocessing.

Subcortical pathways serving cortical language sites: initial experience with diffusion tensor imaging fiber tracking combined with intraoperative language mapping

The combination of mapping functional cortical neurons by intraoperative cortical stimulation and axonal architecture by diffusion tensor MRI fiber tracking can be used to delineate the pathways between functional regions. In this study the authors investigated the feasibility of combining these techniques to yield connectivity associated with motor speech and naming. Diffusion tensor MRI fiber tracking provides maps of axonal bundles and was combined with intraoperative mapping of eloquent cortex for a patient undergoing brain tumor surgery. Tracks from eight stimulated sites in the inferior frontal cortex including mouth motor, speech arrest, and anomia were generated from the diffusion tensor MRI data. The regions connected by the fiber tracking were compared to foci from previous functional imaging reports on language tasks. Connections were found between speech arrest, mouth motor, and anomia sites and the SMA proper and cerebral peduncle. The speech arrest and a mouth motor site were also seen to connect to the putamen via the external capsule. This is the first demonstration of delineation of subcortical pathways using diffusion tensor MRI fiber tracking with intraoperative cortical stimulation. The combined techniques may provide improved preservation of eloquent regions during neurological surgery, and may provide access to direct connectivity information between functional regions of the brain.

Diffusion MRI of complex neural architecture

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

Three-dimensional anatomical characterization of the developing mouse brain by diffusion tensor microimaging

Investigation of three-dimensional (3D) morphometry of developing brains has been hindered by a lack of imaging modalities that can monitor the 3D evolution of various anatomical structures without sectioning and staining processes. In this study, we combined magnetic resonance microimaging and diffusion tensor imaging techniques to accomplish such visualization. The application of this approach to developing mouse embryos revealed that it could clearly delineate early critical structures such as neuroepithelium, cortical plate, and various axonal structures, and follow their developmental evolution. The technique was applied to the study of the Netrin-1 mutant, allowing verification of its anatomical phenotype.

Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia

Both axon and myelin degeneration have significant impact on the long-term disability of patients with white matter disorder. However, the clinical manifestations of the neurological dysfunction caused by white matter disorders are not sufficient to determine the origin of neurological deficits. A noninvasive biological marker capable of detecting and differentiating axon and myelin degeneration would be a significant addition to currently available tools. Directional diffusivities derived from diffusion tensor imaging (DTI) have been previously proposed by this group as potential biological markers to detect and differentiate axon and myelin degeneration. To further test the hypothesis that axial (lambdaparallel) and radial (lambdaperpendicular) diffusivities reflect axon and myelin pathologies, respectively, the optic nerve was examined serially using DTI in a mouse model of retinal ischemia. A significant decrease of lambdaparallel, the putative DTI axonal marker, was observed 3 days after ischemia without concurrently detectable changes in lambdaperpendicular, the putative myelin marker. This result is consistent with histological findings of significant axonal degeneration with no detectable demyelination at 3 days after ischemia. The elevation of lambdaperpendicular observed 5 days after ischemia is consistent with histological findings of myelin degeneration at this time. These results support the hypothesis that lambdaparallel and lambdaperpendicular hold promise as specific markers of axonal and myelin injury, respectively, and, further, that the coexistence of axonal and myelin degeneration does not confound this utility.

Three-dimensional diffusion tensor microscopy of fixed mouse hearts

The relative utility of 3D, microscopic resolution assessments of fixed mouse myocardial structure via diffusion tensor imaging is demonstrated in this study. Isotropic 100-microm resolution fiber orientation mapping within 5.5 degrees accuracy was achieved in 9.1 hr scan time. Preliminary characterization of the diffusion tensor primary eigenvector reveals a smooth and largely linear angular rotation across the left ventricular wall. Moreover, a higher level of structural hierarchy is evident from the organized secondary and tertiary eigenvector fields. These findings are consistent with the known myocardial fiber and laminar structures reported in the literature and suggest an essential role of diffusion tensor microscopy in developing quantitative atlases for studying the structure-function relationships of mouse hearts.

Fiber Tract–based Atlas of Human White Matter Anatomy

Two- and three-dimensional (3D) white matter atlases were created on the basis of high-spatial-resolution diffusion tensor magnetic resonance (MR) imaging and 3D tract reconstruction. The 3D trajectories of 17 prominent white matter tracts could be reconstructed and depicted. Tracts were superimposed on coregistered anatomic MR images to parcel the white matter. These parcellation maps were then compared with coregistered diffusion tensor imaging color maps to assign visible structures. The results showed (a). which anatomic structures can be identified on diffusion tensor images and (b). where these anatomic units are located at each section level and orientation. The atlas may prove useful for educational and clinical purposes.

Analysis of noise effects on DTI-based tractography using the brute-force and multi-ROI approach

Diffusion tensor tractography based on line propagation is a promising and widely used technique, but it is known to be sensitive to noise and the size and location of the seed regions of interest (ROIs). The effects of these parameters on the tractography results were analyzed quantitatively using high-resolution diffusion tensor imaging (DTI) with a high signal-to-noise ratio (SNR) on a fixed mouse brain. The anterior commissure (AC), as judged from a T2-weighted image, was used as an anatomical reference within which the tracts could be located. Monte Carlo simulation was performed by adding Gaussian noise to the time domain data and repeating the tractography. Deviations of the tracking results were measured as a function of SNR. Such noise effects were evaluated for a simple one-ROI approach and a combined two-ROI and brute-force (BF) approach. The influence of ROI size and location for the two-ROI + BF approach was also analyzed. The results confirmed the hypothesis that one can increase the validity of DTI-based tractography by adopting the BF and multi-ROI approach, with respect to the simple one-ROI approach.

An error analysis of white matter tractography methods: synthetic diffusion tensor field simulations

White matter tractography using diffusion tensor MR images is a promising method for estimating the pathways of white matter tracts in the human brain. The success of this method ultimately depends upon the accuracy of the white matter tractography algorithms. In this study, a Monte Carlo simulation was used to investigate the impact of SNR, tensor anisotropy, and diffusion tensor encoding directions on the accuracy of six tractography algorithms. The accuracy was assessed in straight and curved tracts and tract geometries with divergence properties. In general, the tract dispersion increased with distance and decreased with SNR and anisotropy. The tract orientation with respect to the encoding scheme also influenced tract dispersion. Divergent tract geometries increased tract dispersion, whereas convergent tract geometries reduced dispersion. Analytic models of tract dispersion were constructed as a function of the tract distance, SNR, eigenvalues of the tracts, voxel size, and the relationship between the tract direction and the diffusion tensor encoding directions. In certain cases, the mean tract trajectory was found to deviate from the ideal pathway for curved trajectories. Analytical models of mean displacement were constructed as a function of the curvature, tract distance, step size, and tensor eigenvalues. These models may be used in future studies to assess the level of confidence associated with a tractography result.

Magnetic resonance imaging in experimental models of brain disorders

This review gives an overview of the application of magnetic resonance imaging (MRI) in experimental models of brain disorders. MRI is a noninvasive and versatile imaging modality that allows longitudinal and three-dimensional assessment of tissue morphology, metabolism, physiology, and function. MRI can be sensitized to proton density, T1, T2, susceptibility contrast, magnetization transfer, diffusion, perfusion, and flow. The combination of different MRI approaches (e.g., diffusion-weighted MRI, perfusion MRI, functional MRI, cell-specific MRI, and molecular MRI) allows in vivo multiparametric assessment of the pathophysiology, recovery mechanisms, and treatment strategies in experimental models of stroke, brain tumors, multiple sclerosis, neurodegenerative diseases, traumatic brain injury, epilepsy, and other brain disorders. This report reviews established MRI methods as well as promising developments in MRI research that have advanced and continue to improve our understanding of neurologic diseases and that are believed to contribute to the development of recovery improving strategies.

In vivo mapping of functional domains and axonal connectivity in cat visual cortex using magnetic resonance imaging

Noninvasive cognitive neuroimaging studies based on functional magnetic resonance imaging (fMRI) are of ever-increasing importance for basic and clinical neurosciences. The explanatory power of fMRI could be greatly expanded, however, if the pattern of the neuronal circuitry underlying functional activation could be made visible in an equally noninvasive manner. In this study, blood oxygenation level-dependent (BOLD)-based fMRI and diffusion tensor imaging (DTI) were performed in the same cat visual cortex, and the foci of fMRI activation utilized as seeding points for 3D DTI fiber reconstruction algorithms, thus providing the map of the axonal circuitry underlying visual information processing. The methods developed in this study will lay the foundation for in vivo neuroanatomy and the ability for noninvasive longitudinal studies of brain development.

Asymmetry of subinsular anisotropy by in vivo diffusion tensor imaging

The cortical regions specialized in speech-language exhibit a left-right asymmetry, e.g., a larger cortical size in the left auditory cortex and Wernicke's area. The possibility of developmental asymmetry in axonal fibers interconnecting speech-language cortical areas can be investigated by in vivo diffusion tensor imaging. Fifteen right-handed native English speakers showed a markedly significant asymmetry (P < 0. 0005) in the relative anisotropy of water diffusion in the subinsular white matter, greater on the left. Additionally, the first principal diffusivity was greater and the second and third principal diffusivities were smaller on the left than right side. These results suggest the subinsular axonal structures developed differently between the left and right sides. A possible association between the hemispheric specialization in language and speech and the subinsular axonal fiber development is discussed.

Functional activation using apparent diffusion coefficient-dependent contrast allows better spatial localization to the neuronal activity: evidence using diffusion tensor imaging and fiber tracking

Recent studies suggested that functional activation using apparent diffusion coefficient (ADC) contrast can be used to detect synchronized functional MRI (fMRI) signal changes during brain activation. Such changes may reflect better spatial localization to the smaller vessels, which are closely coupled to the true neuronal activation. Since it is generally believed that there are neural pathways among neuronally relevant areas, methods that would allow clear delineation of such pathways could help validate the neuronal relevance of the activated functional areas. The development of diffusion tensor imaging (DTI) has shown promise in detailed nerve fiber tracking. In this report, DTI was adopted to track the fiber connections among the discrete areas determined using the ADC contrast, in an effort to confirm the neuronal origin of these activated areas. As a comparison, activated areas using blood oxygenation level-dependent (BOLD) contrast were also obtained. Our results showed that the areas determined by the ADC contrast consistently allowed better fiber tracking within, while the BOLD-activated areas were more spatially diffused due to the smearing effect of brain vasculature, rendering the task of fiber tracking more difficult. This observation provides converging evidence that the activated areas using ADC contrast are more closely coupled to the neuronal activity than those using BOLD contrast.

Relative indices of water diffusion anisotropy are equivalent in live and formalin-fixed mouse brains

Formalin fixation of tissue is a common laboratory practice. A direct comparison of diffusion tensor imaging (DTI) parameters from mouse brains before (in vivo) and after (ex vivo) formalin fixation is reported herein. Five diffusion indices were examined in a cohort of seven mice: relative anisotropy (RA), directional correlation (DC), trace (Tr(D)), trace-normalized axial diffusivity (D(axially)), and radial diffusivity (D(radially)). Seven regions of interest (ROIs), including five in white matter and two in gray matter, were selected for examination. Consistent with previous findings, a significant decrease of Tr(D) was observed for all ROIs after fixation. However, water diffusion anisotropy, as defined by the indices RA, DC, D(axially), and D(radially), remained unchanged after fixation. Thus, fixation does not appear to alter diffusion anisotropy in the mouse brain. This finding supports the utility of diffusion anisotropy analysis of fixed tissue. The combination of DTI measurements and standard histology may shed light on the microstructural determinants of diffusion anisotropy in normal and disease states.

Circular spectrum mapping for intravoxel fiber structures based on high angular resolution apparent diffusion coefficients

A method is presented for mapping intravoxel fiber structures using spectral decomposition onto a circular distribution of measured apparent diffusion coefficients (ADCs). The zeroth-, second-, and fourth-order harmonic components of the ADC distribution on the circle spanned by the major and median eigenvectors of the diffusion tensor can be used to provide quantitative indices for isotropic, linear, and fiber-crossing diffusion, respectively. A diffusion-weighted MRI technique with 90 encoding orientations was implemented to estimate the circular ADC distribution and calculate the circular spectrum. A digital phantom was used to simulate various diffusion patterns. Comparisons were made between the circular spectrum and regular DTI-based index maps. The results indicated that the zeroth- and second-order circular spectrum maps exhibited a strong consistency with the DTI-based mean diffusivity and linear indices, respectively, and the fourth-order circular spectrum map was able to identify the fiber crossings. MRI experiments were performed on seven healthy human brains using a 3T scanner. The in vivo fourth-order maps showed significantly higher densities in several brain regions, including the corpus callosum, cingulum bundle, superior longitudinal fasciculus, corticospinal tract, and middle cerebellar peduncle, which indicated the existence of fiber crossings in these regions.

Differences in the BOLD fMRI response to direct and indirect cortical stimulation in the rat

Functional MRI (fMRI) exploits a relationship between neuronal activity, metabolism, and cerebral blood flow to functionally map the brain. We have developed a model of direct cortical stimulation in the rat that can be combined with fMRI and used to compare the hemodynamic responses to direct and indirect cortical stimulation. Unilateral electrical stimulation of the rat hindpaw motor cortex, via stereotaxically positioned carbon-fiber electrodes, yielded blood oxygenation level-dependent (BOLD) fMRI signal changes in both the stimulated and homotypic contralateral motor cortices. The maximal signal intensity change in both cortices was similar (stimulated = 3.7 +/- 1.7%; contralateral = 3.2 +/- 1.0%), although the response duration in the directly stimulated cortex was significantly longer (48.1 +/- 5.7 sec vs. 19.0 +/- 5.3 sec). Activation of the contralateral cortex is likely to occur via stimulation of corticocortical pathways, as distinct from direct electrical stimulation, and the response profile is similar to that observed in remote (e.g., forepaw) stimulation fMRI studies. Differences in the neuronal pool activated, or neurovascular mediators released, may account for the more prolonged BOLD response observed in the directly stimulated cortex. This work demonstrates the combination of direct cortical stimulation in the rat with fMRI and thus extends the scope of rodent fMRI into brain regions inaccessible to peripheral stimulation techniques.

Brain fiber tracking with clinically feasible diffusion-tensor MR imaging: initial experience

Two technical challenges must be overcome before brain fiber tracking with diffusion-tensor magnetic resonance (MR) imaging can be applied to clinical practice: Imaging time must be shortened, and image distortion must be minimized. Single-shot echo-planar MR imaging with parallel imaging technique enabled both objectives to be accomplished. Twenty-three consecutive patients with brain tumors underwent MR imaging with a 1.5-T whole-body MR system. Fiber tracts on the lesion side in the brain had varying degrees of displacement or disruption as a result of the tumor. Tract disruption resulted from direct tumor involvement, compression on the tract, and vasogenic edema surrounding the tumor. This diffusion-tensor MR imaging method with the parallel imaging technique allows clinically feasible brain fiber tracking.

Classification and quantification of neuronal fiber pathways using diffusion tensor MRI

Quantitative characterization of neuronal fiber pathways in vivo is of significant neurological and clinical interest. Using the capability of MR diffusion tensor imaging to determine the local orientations of neuronal fibers, novel algorithms were developed to bundle neuronal fiber pathways reconstructed in vivo with diffusion tensor images and to quantify various physical and geometric properties of fiber bundles. The reliability of the algorithms was examined with reproducibility tests. Illustrative results show that consistent physical and geometric measurements of novel properties of neuronal tissue can be obtained, which offer considerable potential for the quantitative study of fiber pathways in vivo.

White matter tractography using diffusion tensor deflection

Diffusion tensor MRI provides unique directional diffusion information that can be used to estimate the patterns of white matter connectivity in the human brain. In this study, the behavior of an algorithm for white matter tractography is examined. The algorithm, called TEND, uses the entire diffusion tensor to deflect the estimated fiber trajectory. Simulations and imaging experiments on in vivo human brains were performed to investigate the behavior of the tractography algorithm. The simulations show that the deflection term is less sensitive than the major eigenvector to image noise. In the human brain imaging experiments, estimated tracts were generated in corpus callosum, corticospinal tract, internal capsule, corona radiata, superior longitudinal fasciculus, inferior longitudinal fasciculus, fronto-occipital fasciculus, and uncinate fasciculus. This approach is promising for mapping the organizational patterns of white matter in the human brain as well as mapping the relationship between major fiber trajectories and the location and extent of brain lesions.

Parametric and non-parametric statistical analysis of DT-MRI data

In this work parametric and non-parametric statistical methods are proposed to analyze Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) data. A Multivariate Normal Distribution is proposed as a parametric statistical model of diffusion tensor data when magnitude MR images contain no artifacts other than Johnson noise. We test this model using Monte Carlo (MC) simulations of DT-MRI experiments. The non-parametric approach proposed here is an implementation of bootstrap methodology that we call the DT-MRI bootstrap. It is used to estimate an empirical probability distribution of experimental DT-MRI data, and to perform hypothesis tests on them. The DT-MRI bootstrap is also used to obtain various statistics of DT-MRI parameters within a single voxel, and within a region of interest (ROI); we also use the bootstrap to study the intrinsic variability of these parameters in the ROI, independent of background noise. We evaluate the DT-MRI bootstrap using MC simulations and apply it to DT-MRI data acquired on human brain in vivo, and on a phantom with uniform diffusion properties.

Directional correlation characterization and classification of white matter tracts

To study the architectural characteristics of white matter (WM) tracts, the directional correlation (DC), defined as the inner product of the major eigenvector of adjacent pixels, was used as a quantitative index to investigate directional similarity in WM tracts. A region-growing algorithm was employed to propagate an area from a seed point as a function of the DC threshold (DCt) to critically evaluate the directional properties of WM tracts. As the DCt was increased, more pixels were excluded from the propagated region as their DC fell below the DCt, and neighboring WM tracts could be distinguished as the area decreased. Taking the DC into account, a systematic classification routine for WM tracts was devised and tested on a mouse brain in vivo. The results show that individual WM tracts possess a high degree of directional similarity, and, by careful choice of the DCt value, the proposed classification algorithm can recognize all possible WM tracts in a given data set.

Pyramidal tract mapping by diffusion tensor magnetic resonance imaging in multiple sclerosis: improving correlations with disability

BACKGROUND

Current magnetic resonance imaging (MRI) outcome measures such as T2 lesion load correlate poorly with disability in multiple sclerosis. Diffusion tensor imaging (DTI) of the brain can provide unique information regarding the orientation and integrity of white matter tracts in vivo.

OBJECTIVE

To use this information to map the pyramidal tracts of patients with multiple sclerosis, investigate the relation between burden of disease in the tracts and disability, and compare this with more global magnetic resonance estimates of disease burden.

METHODS

25 patients with relapsing-remitting multiple sclerosis and 17 healthy volunteers were studied with DTI. An algorithm was used that automatically produced anatomically plausible maps of white matter tracts. The integrity of the pyramidal tracts was assessed using relative anisotropy and a novel measure (L(t)) derived from the compounded relative anisotropy along the tracts. The methods were compared with both traditional and more recent techniques for measuring disease burden in multiple sclerosis (T2 lesion load and "whole brain" diffusion histograms).

RESULTS

Relative anisotropy and L(t) were significantly lower in patients than controls (p < 0.05). Pyramidal tract L(t) in the patients correlated significantly with both expanded disability status scale (r = -0.48, p < 0.05), and to a greater degree, the pyramidal Kurtzke functional system score (KFS-p) (r = -0.75, p < 0.0001). T2 lesion load and diffusion histogram parameters did not correlate with disability.

CONCLUSIONS

Tract mapping using DTI is feasible and may increase the specificity of MRI in multiple sclerosis by matching appropriate tracts with specific clinical scoring systems. These techniques may be applicable to a wide range of neurological conditions.

From diffusion tractography to quantitative white matter tract measures: a reproducibility study

The aim of this study is to propose methods for assessing the reproducibility of diffusion tractography algorithms in future clinical studies and to show their application to the tractography algorithm developed in our unit, fast marching tractography (FMT). FMT estimates anatomical connectivity between brain regions using the information provided by diffusion tensor imaging. Three major white-matter pathways were investigated in 11 normal subjects--anterior callosal fibers, optic radiations, and pyramidal tracts. FMT was used to generate maps of connectivity metric, and regions of voxels with highest connectivity metric to an anatomically defined starting point were identified for each tract under investigation. The reproducibilities of tract-"normalized" volume (NV) and fractional anisotropy (FA) measurements were assessed over such regions. The values of tract volumes are consistent with the postmortem data. Coefficients of variation (CVs) for FA and NV ranged from 1.7 to 7.1% and from 2.2 to 18.6%, respectively. CVs were lowest in the anterior callosal fibers (range: 1.7- 7.8%), followed by the optic radiations (range: 1.2-18.6%) and pyramidal tracts (range: 2.6-15.5%), suggesting that fiber organization plays a role in determining the level of FMT reproducibility. In conclusion, these findings underline the importance of assessing the reliability of diffusion tractography before investigating white matter pathology.

Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water

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

Fiber tracking: principles and strategies - a technical review

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

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

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

A framework for callosal fiber distribution analysis

This paper presents a framework for analyzing the spatial distribution of neural fibers in the brain, with emphasis on interhemispheric fiber bundles crossing through the corpus callosum. The proposed approach combines methodologies for fiber tracking and spatial normalization and is applied on diffusion tensor images and standard magnetic resonance images.

High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity

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

Exploring white matter tracts in band heterotopia using diffusion tractography

Band heterotopia is a malformation of cortical development characterized by bands of gray matter in the white matter parallel to the surface of the neocortex. Histopathological studies have suggested that small white matter tracts pass through the heterotopia, and functional magnetic resonance imaging studies have shown activation in the malformation. We used diffusion tractography to explore the anatomical connectivity of band heterotopia and, in particular, whether in vivo white matter tracts traverse the heterotopic gray matter. Five patients with band heterotopia and five control subjects were scanned with whole brain diffusion tensor imaging. Anisotropy maps were calculated. Using fast marching tractography, we produced maps of connectivity and tract traces from two seed points, in the splenium of the corpus callosum and the right parietal lobe. Eigenvectors were found to pass through the band heterotopia in an aligned fashion. Patterns for maps of connectivity were similar in patients and control subjects. Areas of high connectivity were found in the band heterotopia and in cortical areas on the far side of the malformation from the seed point. The tracts hence appeared to traverse or end within the band heterotopia. The results are in agreement with previous histopathological studies and indicate the structural basis of the functional connectivity and absence of focal deficits in these patients.

Pathway selection by pulsed field gradients

A method for pathway selection in a multiple spin-echo pulse sequence applying crusher gradients before and after each pi pulse, to dephase unwanted pathways, is described. This method selects the only pathway that would contribute to the measurable signal if the pi pulses were perfect (1,-1,1,-1, em leader ). Good pathway selection is essential in pulse programming, especially when the CPMG condition is not met. An interactive applet was also developed to deal with these calculations.

MR microscopy and high resolution small animal MRI: applications in neuroscience research

The application of magnetic resonance (MR) imaging in the study of human disease using small animals has steadily evolved over the past two decades and strongly established the fields of "small animal MR imaging" and "MR microscopy." An increasing number of neuroscience related investigations now implement MR microscopy in their experiments. Research areas of growth pertaining to MR microscopy studies are focused on (1). phenotyping of genetically engineered mice models of human neurological diseases and (2). rodent brain atlases. MR microscopy can be performed in vitro on tissue specimens, ex vivo on brain slice preparations and in vivo (typically on rodents). Like most new imaging technologies, MR microscopy is technologically demanding and requires broad expertise. Uniform guidelines or "standards" of a given MR microscopy experiment are non-existent. The main focus therefore of this review will be on biological applications of MR microscopy and the experimental requirements. We also take a critical look at the biological information that small animal (rodent) MR imaging has provided in neuroscience research.

Holoprosencephaly in children: diffusion tensor MR imaging of white matter tracts of the brainstem--initial experience

PURPOSE

To evaluate the dimensions of specific white matter tracts in the brainstems (region of brain thought to be least affected) of children with holoprosencephaly by using diffusion tensor magnetic resonance (MR) imaging and to correlate these abnormalities with forebrain malformation severity and neurologic deficit severity.

MATERIALS AND METHODS

Thirteen patients with holoprosencephaly underwent diffusion tensor MR imaging, with which white matter color maps were generated. Type of holoprosencephaly was correlated with presence or absence of specific brainstem white matter tracts. Furthermore, patient rank based on cortico-ponto-spinal tract (CPST) and middle cerebellar peduncle (MCP) dimensions was correlated with holoprosencephaly type and neurodevelopmental score by using Spearman rank correlation analysis.

RESULTS

Two patients had alobar holoprosencephaly, five had the semilobar type, one had the lobar type, and one had the middle-hemisphere-variant type. Four patients were excluded from analysis. In the two patients with alobar holoprosencephaly, the CPSTs were absent bilaterally. In all of the remaining patients except one, who had semilobar holoprosencephaly in which the CPSTs could not be identified at the level of the medulla oblongata, all tracts were present bilaterally. Holoprosencephaly type and neurodevelopmental score correlated strongly with CPST and MCP dimensions (P <.01) over and above the effect of age.

CONCLUSION

In vivo identification of brainstem white matter tract abnormalities in patients with holoprosencephaly can be achieved by performing diffusion tensor MR imaging.

EZ-tracing: a new ready-to-use algorithm for magnetic resonance tractography

A new algorithm for tractography based on diffusion tensor analysis (DTA) is presented. This method, called EZ-tracing, is based on a new algorithm for analyzing DTA data, lambda chart analysis (LCA), and effectively overcomes the main shortcomings of previous methods for tractography. EZ-tracing is written in MATLAB scripting language (MathWorks, Natick, MA, USA) and can be implemented on any of the common operating systems, such as Microsoft Windows, UNIX, and LINUX. The program is available in public at coe@bri.niigata-u.ac.jp.

High-resolution isotropic 3D diffusion tensor imaging of the human brain

High-resolution cardiac-gated 3D diffusion tensor imaging (3D-DTI) is demonstrated in vivo for several areas of the human brain. Anatomical mapping of subcortical white matter (WM), as well as definition and identification of major WM bundles from the brainstem were performed in humans for the first time using this technique. Improved intrinsic signal-to-noise ratio (SNR) and relatively reduced sensitivity to physiological motion (e.g., brain pulsations) with respect to cardiac-gated multislice acquisition are demonstrated. The advantages and weaknesses of this approach are discussed.

Three-dimensional diffusion tensor magnetic resonance microimaging of adult mouse brain and hippocampus

The use of diffusion tensor information as an additional contrast in MR microimaging was investigated in ex vivo mouse brain and isolated hippocampus. Diffusion Tensor Imaging (DTI) provided unique contrast to identify many internal structures of the gray matter such as hippocampus, thalamus, and cortex. In hippocampus, stratum granulosum and stratum pyramidale could be identified using the isotropic water diffusion constant. Stratum moleculare and stratum radiatum were identified from their characteristic fiber architecture revealed by color-coded DTI. Identification of these structures allowed reconstruction of their 3-D volume. Thus, high-resolution DTI has excellent potential as a tool for 3-D characterization of murine brains.

Initial demonstration of in vivo tracing of axonal projections in the macaque brain and comparison with the human brain using diffusion tensor imaging and fast marching tractography

Diffusion tensor imaging (DTI), a magnetic resonance imaging technique, is used to infer major axonal projections in the macaque and human brain. This study investigates the feasibility of using known macaque anatomical connectivity as a "gold-standard" for the evaluation of DTI tractography methods. Connectivity information is determined from the DTI data using fast marching tractography (FMT), a novel tract-tracing (tractography) method. We show for the first time that it is possible to determine, in an entirely noninvasive manner, anatomical connection pathways and maps of an anatomical connectivity metric in the macaque brain using a standard clinical scanner and that these pathways are consistent with known anatomy. Analogous human anatomical connectivity is also presented for the first time using the FMT method, and the results are compared. The current limitations of the methodology and possibilities available for further studies are discussed.

Limitations and requirements of diffusion tensor fiber tracking: an assessment using simulations

Diffusion tensor fiber tracking potentially can give information about in vivo brain connectivity. However, this technique is difficult to validate due to the lack of a gold standard. Fiber tracking reliability will depend on the quality of the data and on the robustness of the algorithms used. Information about the effects of various anatomical and image acquisition parameters on fiber tracking reliability may be used in the design of imaging sequences and of tracking algorithms. In this study, tracking was performed on two different simulated models to study the effects on tracking quality of SNR, anisotropy, curvature, fiber cross-section, background anisotropy, step size, and interpolation. Tracking was also performed on volunteer data to assess the relevance of the simulations to real data. Our results show that, in general, tracking with high SNR and high anisotropy using interpolation and a low step size gives the most reliable results. Partial volume effects are shown to have a detrimental effect when the background is anisotropic and when tracking narrow fibers. The results derived from real data show similar trends and thus support the findings of the simulations. These simulations may therefore help to determine which structures can be tracked for a given image quality.

Brain white matter anatomy of tumor patients evaluated with diffusion tensor imaging

We applied multislice, whole-brain diffusion tensor imaging (DTI) to two patients with anaplastic astrocytoma. Data were analyzed using DTI-based, color-coded images and a 3-D tract reconstruction technique for the study of altered white matter anatomy. Each tumor was near two major white matter tracts, namely, the superior longitudinal fasciculus and the corona radiata. Those tracts were identified using the color-coded maps, and spatial relationships with the tumors were characterized. In one patient the tumor displaced adjacent white matter tracts, whereas in the other it infiltrated the superior longitudinal fasciclus without displacement of white matter. DTI provides new information regarding the detailed relationship between tumor growth and nearby white matter tracts, which may be useful for preoperative planning.

Diffusion tensor brain imaging and tractography

Diffusion-tensor MR imaging is a promising tool to evaluate white-matter integrity by quantitative and graphic maps including neural fiber tractogram. Current challenges afoot are to obtain higher quality diffusion-weighted MR images (high SNR, isotropic voxel, and high spatial resolution), to create a robust mathematical framework to process the data, to construct a user-friendly computer-based algorithm, to reveal determinants of diffusion process, and to establish analytical methodology.

Imaging cortical association tracts in the human brain using diffusion-tensor-based axonal tracking

Diffusion-tensor fiber tracking was used to identify the cores of several long-association fibers, including the anterior (ATR) and posterior (PTR) thalamic radiations, and the uncinate (UNC), superior longitudinal (SLF), inferior longitudinal (ILF), and inferior fronto-occipital (IFO) fasciculi. Tracking results were compared to existing anatomical knowledge, and showed good qualitative agreement. Guidelines were developed to reproducibly track these fibers in vivo. The interindividual variability of these reconstructions was assessed in a common spatial reference frame (Talairach space) using probabilistic mapping. As a first illustration of this technical capability, a reduction in brain connectivity in a patient with a childhood neurodegenerative disease (X-linked adrenoleukodystrophy) was demonstrated.

A continuous tensor field approximation of discrete DT-MRI data for extracting microstructural and architectural features of tissue

The effective diffusion tensor of water, D, measured by diffusion tensor MRI (DT-MRI), is inherently a discrete, noisy, voxel-averaged sample of an underlying macroscopic effective diffusion tensor field, D(x). Within fibrous tissues this field is presumed to be continuous and smooth at a gross anatomical length scale. Here a new, general mathematical framework is proposed that uses measured DT-MRI data to produce a continuous approximation to D(x). One essential finding is that the continuous tensor field representation can be constructed by repeatedly performing one-dimensional B-spline transforms of the DT-MRI data. The fidelity and noise-immunity of this approximation are tested using a set of synthetically generated tensor fields to which background noise is added via Monte Carlo methods. Generally, these tensor field templates are reproduced faithfully except at boundaries where diffusion properties change discontinuously or where the tensor field is not microscopically homogeneous. Away from such regions, the tensor field approximation does not introduce bias in useful DT-MRI parameters, such as Trace(D(x)). It also facilitates the calculation of several new parameters, particularly differential quantities obtained from the tensor of spatial gradients of D(x). As an example, we show that they can identify tissue boundaries across which diffusion properties change rapidly using in vivo human brain data. One important application of this methodology is to improve the reliability and robustness of DT-MRI fiber tractography.

Theoretical analysis of the effects of noise on diffusion tensor imaging

A theoretical framework is presented for understanding the effects of noise on estimates of the eigenvalues and eigenvectors of the diffusion tensor at moderate to high signal-to-noise ratios. Image noise produces a random perturbation of the diffusion tensor. Power series solutions to the eigenvalue equation are used to evaluate the effects of the perturbation to second order. It is shown that in anisotropic systems the expectation value of the largest eigenvalue is overestimated and the lowest eigenvalue is underestimated. Hence, diffusion anisotropy is overestimated in general. This result is independent of eigenvalue sorting bias. Furthermore, averaging eigenvalues over a region of interest produces greater bias than averaging tensors prior to diagonalization. Finally, eigenvector noise is shown to depend on the eigenvalue contrast and imposes a theoretical limit on the accuracy of simple fiber tracking schemes. The theoretical results are shown to agree with Monte Carlo simulations.

Investigating the potential neurotoxicity of Ecstasy (MDMA): an imaging approach

Human users of 3,4-methylenedioxymethamphetamine (MDMA, 'Ecstasy') users may be at risk of developing MDMA-induced neuronal injury. Previously, no methods were available for directly evaluating the neurotoxic effects of MDMA in the living human brain. However, development of in vivo neuroimaging tools has begun to provide insights into the effects of MDMA in the human brain. In this review, contributions of brain imaging studies on the potential neurotoxic effects of MDMA and functional consequences are highlighted. An overview is given of PET, SPECT and MR spectroscopy studies, most of which show evidence of neuronal injury in MDMA users. Different neuroimaging tools are discussed that have investigated potential functional consequences of MDMA-induced 5-HT neurotoxic lesions. Finally, the contribution of brain imaging in future studies is discussed, emphasising the crucial role it will play in our understanding of MDMA's short- and long-term effects in the human brain. Copyright 2001 John Wiley & Sons, Ltd.

Improving relative anisotropy measurement using directional correlation of diffusion tensors

A method employing directional correlation of the diffusion tensor, directional-correlation weighted relative anisotropy (DRA), was developed to improve the accuracy of estimated relative anisotropy (RA). The intravoxel directional correlation was established on the same voxel between two identically acquired diffusion tensor images, and the correlation coefficient derived from tensor dot product was employed as the weighting factor applied in the calculation of RA. The effect of noise influence was reduced since the random noise between repeated scans is not directionally correlated. The RA and the inter- and intravoxel DRA estimations were examined on rat brains in vivo. The background noise alters the direction of eigenvectors and the magnitude of eigenvalues. The dispersion angle between repeatedly obtained eigenvectors, representing the extent of directional alteration of eigenvectors, depends on the tissue anisotropy as well as the signal-to-noise ratio (SNR) of the source images. Current results demonstrate that the intravoxel DRA improves the accuracy of RA estimation, increases the relative contrast of gray and white matter, and avoids the partial volume effect commonly seen in the intervoxel operations.