Jiangyang Zhang

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.

Stereotaxic White Matter Atlas Based on Diffusion Tensor Imaging in an ICBM Template

Brain registration to a stereotaxic atlas is an effective way to report anatomic locations of interest and to perform anatomic quantification. However, existing stereotaxic atlases lack comprehensive coordinate information about white matter structures. In this paper, white matter-specific atlases in stereotaxic coordinates are introduced. As a reference template, the widely used ICBM-152 was used. The atlas contains fiber orientation maps and hand-segmented white matter parcellation maps based on diffusion tensor imaging (DTI). Registration accuracy by linear and non-linear transformation was measured, and automated template-based white matter parcellation was tested. The results showed a high correlation between the manual ROI-based and the automated approaches for normal adult populations. The atlases are freely available and believed to be a useful resource as a target template and for automated parcellation methods.

Tract Probability Maps in Stereotaxic Spaces: Analyses of White Matter Anatomy and Tract-Specific Quantification

Diffusion tensor imaging (DTI) is an exciting new MRI modality that can reveal detailed anatomy of the white matter. DTI also allows us to approximate the 3D trajectories of major white matter bundles. By combining the identified tract coordinates with various types of MR parameter maps, such as T2 and diffusion properties, we can perform tract-specific analysis of these parameters. Unfortunately, 3D tract reconstruction is marred by noise, partial volume effects, and complicated axonal structures. Furthermore, changes in diffusion anisotropy under pathological conditions could alter the results of 3D tract reconstruction. In this study, we created a white matter parcellation atlas based on probabilistic maps of 11 major white matter tracts derived from the DTI data from 28 normal subjects. Using these probabilistic maps, automated tract-specific quantification of fractional anisotropy and mean diffusivity were performed. Excellent correlation was found between the automated and the individual tractography-based results. This tool allows efficient initial screening of the status of multiple white matter tracts.

White and gray matter development in human fetal, newborn and pediatric brains

Brain anatomy is characterized by dramatic growth from the end of the second trimester through the neonatal stage. The characterization of normal axonal growth of the white matter tracts has not been well-documented to date and could provide important clues to understanding the extensive inhomogeneity of white matter injuries in cerebral palsy (CP) patients. However, anatomical studies of human brain development during this period are surprisingly scarce and histology-based atlases have become available only recently. Diffusion tensor magnetic resonance imaging (DTMRI) can reveal detailed anatomy of white matter. We acquired diffusion tensor images (DTI) of postmortem fetal brain samples and in vivo neonates and children. Neural structures were annotated in two-dimensional (2D) slices, segmented, measured, and reconstructed three-dimensionally (3D). The growth status of various white matter tracts was evaluated on cross-sections at 19-20 gestational weeks, and compared with 0-month-old neonates and 5- to 6-year-old children. Limbic, commissural, association, and projection white matter tracts and gray matter structures were illustrated in 3D and quantitatively characterized to assess their dynamic changes. The overall pattern of the time courses for the development of different white matter is that limbic fibers develop first and association fibers last and commissural and projection fibers are forming from anterior to posterior part of the brain. The resultant DTMRI-based 3D human brain data will be a valuable resource for human brain developmental study and will provide reference standards for diagnostic radiology of premature newborns.

Human Brain White Matter Atlas: Identification and Assignment of Common Anatomical Structures in Superficial White Matter

Structural delineation and assignment are the fundamental steps in understanding the anatomy of the human brain. The white matter has been structurally defined in the past only at its core regions (deep white matter). However, the most peripheral white matter areas, which are interleaved between the cortex and the deep white matter, have lacked clear anatomical definitions and parcellations. We used axonal fiber alignment information from diffusion tensor imaging (DTI) to delineate the peripheral white matter, and investigated its relationship with the cortex and the deep white matter. Using DTI data from 81 healthy subjects, we identified nine common, blade-like anatomical regions, which were further parcellated into 21 subregions based on the cortical anatomy. Four short association fiber tracts connecting adjacent gyri (U-fibers) were also identified reproducibly among the healthy population. We anticipate that this atlas will be useful resource for atlas-based white matter anatomical studies.

DTI tractography based parcellation of white matter: application to the mid-sagittal morphology of corpus callosum.

Morphology of the corpus callosum (CC) at the mid-sagittal level has been a target of extensive studies. However, the lack of internal structures and its polymorphism make it a challenging task to quantitatively analyze shape differences among subjects. In this paper, diffusion tensor Imaging (DTI) and tract tracing technique were applied to incorporate cortical connectivity information to the morphological study. The CC was parcellated into six major subdivisions based on trajectories to different cortical areas. This subdivision was performed for eight normal subjects and one stroke patient. The parcellated CCs of the normal subjects were normalized for morphological analysis. When comparing the stroke patient to the normal population, we detected significant atrophy in the motor and sensory areas of the patient CC, in line with the clinical deficits. This approach provides a new tool to investigate callosal morphology and functional relationships.

Diffusion tensor imaging of the developing mouse brain

It is shown that diffusion tensor MR imaging (DTI) can discretely delineate the microstructure of white matter and gray matter in embryonic and early postnatal mouse brains based on the existence and orientation of ordered structures. This order was found not only in white matter but also in the cortical plate and the periventricular zone, which are precursors of the cerebral cortex. This DTI‐based information could be used to accomplish the automated spatial definition of the cortical plate and various axonal tracts. The DTI studies also revealed a characteristic evolution of diffusion anisotropy in the cortex of the developing brain. This ability to detect changes in the organization of the brain during development will greatly enhance morphological studies of transgenic and knockout models of cortical dysfunction. Magn Reson Med 46:18–23, 2001.

Robo1 regulates the development of major axon tracts and interneuron migration in the forebrain

The Slit genes encode secreted ligands that regulate axon branching, commissural axon pathfinding and neuronal migration. The principal identified receptor for Slit is Robo (Roundabout in Drosophila). To investigate Slit signalling in forebrain development, we generated Robo1 knockout mice by targeted deletion of exon 5 of the Robo1 gene. Homozygote knockout mice died at birth, but prenatally displayed major defects in axon pathfinding and cortical interneuron migration. Axon pathfinding defects included dysgenesis of the corpus callosum and hippocampal commissure, and abnormalities in corticothalamic and thalamocortical targeting. Slit2 and Slit1/2 double mutants display malformations in callosal development, and in corticothalamic and thalamocortical targeting, as well as optic tract defects. In these animals, corticothalamic axons form large fasciculated bundles that aberrantly cross the midline at the level of the hippocampal and anterior commissures, and more caudally at the medial preoptic area. Such phenotypes of corticothalamic targeting were not observed in Robo1 knockout mice but, instead, both corticothalamic and thalamocortical axons aberrantly arrived at their respective targets at least 1 day earlier than controls. By contrast, in Slit mutants, fewer thalamic axons actually arrive in the cortex during development. Finally, significantly more interneurons (up to twice as many at E12.5 and E15.5) migrated into the cortex of Robo1 knockout mice, particularly in both rostral and parietal regions, but not caudal cortex. These results indicate that Robo1 mutants have distinct phenotypes, some of which are different from those described in Slit mutants, suggesting that additional ligands, receptors or receptor partners are likely to be involved in Slit/Robo signalling.

Anatomical characterization of human fetal brain development with diffusion tensor magnetic resonance imaging

The human brain is extraordinarily complex, and yet its origin is a simple tubular structure. Characterizing its anatomy at different stages of human fetal brain development not only aids in understanding this highly ordered process but also provides clues to detecting abnormalities caused by genetic or environmental factors. During the second trimester of human fetal development, neural structures in the brain undergo significant morphological changes. Diffusion tensor imaging (DTI), a novel method of magnetic resonance imaging, is capable of delineating anatomical components with high contrast and revealing structures at the microscopic level. In this study, high-resolution and high-signal-to-noise-ratio DTI data of fixed tissues of second-trimester human fetal brains were acquired and analyzed. DTI color maps and tractography revealed that important white matter tracts, such as the corpus callosum and uncinate and inferior longitudinal fasciculi, become apparent during this period. Three-dimensional reconstruction shows that major brain fissures appear while most of the cerebral surface remains smooth until the end of the second trimester. A dominant radial organization was identified at 15 gestational weeks, followed by both laminar and radial architectures in the cerebral wall throughout the remainder of the second trimester. Volumetric measurements of different structures indicate that the volumes of basal ganglia and ganglionic eminence increase along with that of the whole brain, while the ventricle size decreases in the later second trimester. The developing fetal brain DTI database presented can be used for education, as an anatomical research reference, and for data registration.

Atlas-guided tract reconstruction for automated and comprehensive examination of the white matter anatomy

Tractography based on diffusion tensor imaging (DTI) is widely used to quantitatively analyze the status of the white matter anatomy in a tract-specific manner in many types of diseases. This approach, however, involves subjective judgment in the tract-editing process to extract only the tracts of interest. This process, usually performed by manual delineation of regions of interest, is also time-consuming, and certain tracts, especially the short cortico-cortical association fibers, are difficult to reconstruct. In this paper, we propose an automated approach for reconstruction of a large number of white matter tracts. In this approach, existing anatomical knowledge about tract trajectories (called the Template ROI Set or TRS) were stored in our DTI-based brain atlas with 130 three-dimensional anatomical segmentations, which were warped non-linearly to individual DTI data. We examined the degree of matching with manual results for selected fibers. We established 30 TRSs to reconstruct 30 prominent and previously well-described fibers. In addition, TRSs were developed to delineate 29 short association fibers that were found in all normal subjects examined in this paper (N=20). Probabilistic maps of the 59 tract trajectories were created from the normal subjects and were incorporated into our image analysis tool for automated tract-specific quantification.