Diffusion tensor imaging-based tissue segmentation: validation and application to the developing child and adolescent brain

Diffusion Tensor Imaging Correlates of Concussion Related Cognitive Impairment

Introduction: Cognitive impairment after concussion has been widely reported, but there is no reliable imaging biomarker that predicts the severity of cognitive decline post-concussion. This study tests the hypothesis that patients with a history of concussion and persistent cognitive impairment have fractional anisotropy (FA) and mean diffusivity (MD) values from diffusion tensor imaging (DTI) that are specifically associated with poor performance on the Montreal Cognitive Assessment (MoCA). Methods: Fifty-three subjects (19 females) with concussions and persistent cognitive symptoms had MR imaging and the MoCA. Imaging was analyzed by atlas-based, whole-brain DTI segmentation and FLAIR lesion segmentation. Then, we conducted a random forest-based recursive feature elimination (RFE) with 10-fold cross-validation on the entire dataset, and with partial correlation adjustment for age and lesion load. Results: RFE showed that 11 DTI variables were found to be important predictors of MoCA scores. Partial correlation analyses, corrected for age and lesion load, showed significant correlations between MoCA scores and right fronto-temporal regions: inferior temporal gyrus MD (r = -0.62, p = 0.00001), middle temporal gyrus MD (r = -0.54, p = 0.0001), angular gyrus MD (r = -0.48, p = 0.0008), and inferior frontal gyrus FA (r = 0.44, p = 0.002). Discussion: This is the first study to demonstrate a correlation between MoCA scores and DTI variables in patients with a history of concussion and persistent cognitive impairment. This kind of research will significantly increase our understanding of why certain persons have persistent cognitive changes after concussion which, in turn, may allow us to predict persistent impairment after concussion and suggest new interventions.

White matter microstructure in trauma-exposed children: Associations with pubertal stage

Puberty represents a critical period in maturation during which major changes in neural architecture emerge; these changes are shaped, in part, by environmental experiences, including exposure to psychological trauma. However, little is known about how trauma exposure affects white matter microstructure across pubertal stages. This was the goal of the present cross-sectional study. Forty-one male and female African-American children between ages 8-13 were recruited as part of a study of developmental trauma and received assessments of trauma exposure, including violence, and pubertal development as well as diffusion tensor imaging (DTI). Significant interactions of pubertal stage and violent trauma exposure were observed in association with a marker of white matter integrity (mean diffusivity, MD) in the corpus callosum, cingulum bundle and uncinate fasciculus. Greater violent trauma exposure was associated with lower MD in the hippocampal cingulum and uncinate fasciculus in girls, but not boys. These data from a sample of trauma-exposed children may reflect a pattern of accelerated maturation in pathways that are critical for emotion regulation as well as attention and memory processes. It appears that fronto-limbic and callosal connections are particularly sensitive to the effects of violent trauma, revealing a potential pathway through which trauma creates vulnerability for later psychiatric and neurological disorders.

Automated cerebral cortex segmentation based solely on diffusion tensor imaging for investigating cortical anisotropy

To extract Diffusion Tensor Imaging (DTI) parameters from the human cortex, the inner and outer boundaries of the cortex are usually defined on 3D-T1-weighted images and then applied to the co-registered DTI. However, this analysis requires the acquisition of an additional high-resolution structural image that may not be practical in various imaging studies. Here an automatic cortical boundary segmentation method was developed to work directly only on the native DTI images by using fractional anisotropy (FA) maps and mean diffusion weighted images (DWI), the latter with acceptable gray-white matter image contrast. This new method was compared to the conventional cortical segmentations generated from high-resolution T1 structural images in 5 participants. In addition, the proposed method was applied to 15 healthy young adults (10 cross-sectional, 5 test-retest) to measure FA, MD, and radiality of the primary eigenvector across the cortex on whole-brain 1.5 mm isotropic images acquired in 3.5 min at 3T. The proposed method generated reasonable segmentations of the cortical boundaries for all individuals and large proportions of the proposed method segmentations (more than 85%) were within ±1 mm from those generated with the conventional approach on higher resolution T1 structural images. Both FA (~0.15) and MD (~0.77 × 10^-3 mm²/s) extracted halfway between the cortical boundaries were relatively stable across the cortex, although focal regions such as the posterior bank of the central sulcus, anterior insula, and medial temporal lobe showed higher FA. The primary eigenvectors were primarily oriented radially to the middle cortical surface, but there were tangential orientations in the sulcal fundi as well as in the posterior bank of the central sulcus. The proposed method demonstrates the feasibility and accuracy of cortical analysis in native DTI space while avoiding the acquisition of other imaging contrasts like 3D T1-weighted scans.

Tissue Probability Based Registration of Diffusion-Weighted Magnetic Resonance Imaging

BACKGROUND

Current registration methods for diffusion-MRI (dMRI) data mostly focus on white matter (WM) areas. Recently, dMRI has been employed for the characterization of gray matter (GM) microstructure, emphasizing the need for registration methods that consider all tissue types.

PURPOSE

To develop a dMRI registration method based on GM, WM, and cerebrospinal fluid (CSF) tissue probability maps (TPMs).

STUDY TYPE

Retrospective longitudinal study.

POPULATION

Thirty-two healthy participants were scanned twice (legacy data), divided into a training-set (n = 16) and a test-set (n = 16), and 35 randomly-selected participants from the Human Connectome Project.

FIELD STRENGTH/SEQUENCE

3.0T, diffusion-weighted spin-echo echo-planar sequence; T1-weighted spoiled gradient-recalled echo (SPGR) sequence.

ASSESSMENT

A joint segmentation-registration approach was implemented: Diffusion tensor imaging (DTI) maps were classified into TPMs using machine-learning approaches. The resulting GM, WM, and CSF probability maps were employed as features for image alignment. Validation was performed on the test dataset and the HCP dataset. Registration performance was compared with current mainstream registration tools.

STATISTICAL TESTS

Classifiers used for segmentation were evaluated using leave-one-out cross-validation and scored using Dice-index. Registration success was evaluated by voxel-wise variance, normalized cross-correlation of registered DTI maps, intra- and inter-subject similarity of the registered TPMs, and region-based intra-subject similarity using an anatomical atlas. One-way ANOVAs were performed to compare between our method and other registration tools.

RESULTS

The proposed method outperformed mainstream registration tools as indicated by lower voxel-wise variance of registered DTI maps (SD decrease of 10%) and higher similarity between registered TPMs within and across participants, for all tissue types (Dice increase of 0.1-0.2; P < 0.05).

DATA CONCLUSION

A joint segmentation-registration approach based on diffusion-driven TPMs provides a more accurate registration of dMRI data, outperforming other registration tools. Our method offers a "translation" of diffusion data into structural information in the form of TPMs, allowing to directly align diffusion and structural images.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 1.

Multiple b-values improve discrimination of cortical gray matter regions using diffusion MRI: an experimental validation with a data-driven approach

Objective

To investigate whether varied or repeated b-values provide better diffusion MRI data for discriminating cortical areas with a data-driven approach.

Methods

Data were acquired from three volunteers at 1.5T with b-values of 800, 1400, 2000 s/mm² along 64 diffusion-encoding directions. The diffusion signal was sampled from gray matter in seven regions of interest (ROIs). Rotational invariants of the local diffusion profile were extracted as features that characterize local tissue properties. Random forest classification experiments assessed whether classification accuracy improved when data with multiple b-values were used over repeated acquisition of the same (1400 s/mm²) b-value to compare all possible pairs of the seven ROIs. Three data sets from the Human Connectome Project were subjected to similar processing and analysis pipelines in eight ROIs.

Results

Three different b-values showed an average improvement in correct classification rates of 5.6% and 4.6%, respectively, in the local and HCP data over repeated measurements of the same b-value. The improvement in correct classification rate reached as high as 16% for individual binary classification experiments between two ROIs. Often using only two of the available three b-values were adequate to make such an improvement in classification rates.

Conclusion

Acquisitions with varying b-values are more suitable for discriminating cortical areas.

Yakovlev's Basolateral Limbic Circuit in Multiple Sclerosis Related Cognitive Impairment

BACKGROUND AND PURPOSE

In 1948, Paul Yakovlev described an additional limbic circuit located basolateral to James Papez's circuit (1937) and included orbitofrontal cortex, amygdala, and dorsomedial nucleus of thalamus. This circuit is shown to be an important component of subcortical cognitive abilities. We aimed to demonstrate this circuit in a multiple sclerosis (MS) cohort using diffusion tensor imaging (DTI) and evaluate its role in MS-related cognitive impairment (CI).

METHODS

We enrolled cognitively intact (n = 10) and impaired (n = 36) MS patients who underwent a comprehensive cognitive assessment; the minimal assessment of cognitive function in MS (MACFIMS) and structural magnetic resonance imaging. Correlation analyses between volumetric and DTI-derived values of the orbitofrontothalamic (OFT), amygdalothalamic tracts (ATTs), and dorsomedial nucleus of thalamus and CI index derived from MACFIMS were computed after adjustment for age, education, and lesion load.

RESULTS

We observed a consistent trend between CI index and bilateral dorsomedial nucleus' mean diffusivity (MD) (r = .316; P = .02), left OFT Fractional anisotropy (FA) (r = -.302; P = .02), MD (r = .380; .006), and radial diffusivities (RDs) (r = .432; P = .002), also with right ATT FA (r = -.475; P = .0006) and left ATT FA ( = -.487; P = .0005). After Bonferroni correction, correlations of left OFT RD and right and left ATT FA with CI were found to be significant.

CONCLUSIONS

Our study provides in vivo DTI delineation of Yakovlev's historical basolateral limbic circuit and establishes a role in MS-related CI. These findings may potentially pave the way for future clinical studies using targeted invasive and noninvasive neurostimulation modalities for CI in MS.

Quantitative Limbic System Mapping of Main Cognitive Domains in Multiple Sclerosis

Background and objective

Cognitive impairment (CI) is common in multiple sclerosis (MS), but underlying mechanisms and their imaging correlates are not completely understood. The gray and white matter structures of the limbic system (LS) play crucial roles in different aspects of cognition. To investigate their role in MS related CI, and since a detailed evaluations are lacking in the literature, we used a comprehensive neuroimaging approach to evaluate CI’s correlations with the main components of the LS.

Methods

Ten non-cognitively impaired MS patients and 30 MS patients with diagnosed CI, who underwent a comprehensive neuropsychological evaluation were included in the analysis. Microstructural integrity, volumetry of main limbic gray and white matter structures and cortical thickness were assessed for associations with CI.

Results

Fornix and cingulum/cingulate cortices were found to be the strongest correlates of CI in MS. As expected, LS’ gray and white matter structures were involved in various cognitive functions. Uncinate fasciculi showed significant correlation with verbal and visuospatial learning and memory, phonemic and semantic fluency; hippocampi with visuospatial skills, phonemic and semantic fluency, executive functions, and processing speed; thalami with verbal learning, visuospatial skills, semantic fluency; and amygdala with verbal recognition discrimination.

Conclusion

This comprehensive neuroimaging approach elucidated the role of the main limbic structures in cognitive functions associated with MS-related CI.

White matter microstructure integrity in relation to reading proficiency☆

Components of reading proficiency such asaccuracy, fluency, and comprehension require the successful coordination of numerous, yet distinct, cortical regions. Underlying white matter tracts allow for communication among these regions. This study utilized unique residualized tract - based spatial statistics methodology to identify the relations of white matter microstructure integrity to three components of reading proficiency in 49 school - aged children with typically developing phonological decoding skills and 27 readers with poor decoders. Results indicated that measures of white matter integrity were differentially associated with components of reading proficiency. In both typical and poor decoders, reading comprehension correlated with measures of integrity of the right uncinate fasciculus; reading comprehension was also related to the left inferior longitudinal fasciculus in poor decoders. Also in poor decoders, word reading fluency was related to the right uncinate and left inferior fronto - occipital fasciculi. Word reading was unrelated to white matter integrity in either group. These findings expand our knowledge of the association between white matter integrity and different elements of reading proficiency.

Diffusion Tensor Imaging-Defined Sulcal Enlargement Is Related to Cognitive Impairment in Multiple Sclerosis

BACKGROUND AND PURPOSE

Cerebrospinal fluid (CSF) in the brain can be compartmentalized into two main divisions: ventricular CSF and subarachnoid space (sulcal CSF). Changes in CSF volumetry are seen in many neurological conditions including multiple sclerosis (MS) and found to correlate with clinical outcomes. We aimed to test the relation between the volumetry of sulcal and ventricular CSF and cognitive impairment (CI) based on the minimal assessment of cognitive function in MS (MACFIMS) in patients with MS.

MATERIAL AND METHODS

Forty-six patients with MS underwent the MACFIMS battery and classified as nonimpaired (MSNI) (n = 10) and cognitively impaired (MSCI) (n = 30) and borderline (MSBD) MS patients (n = 6). Volumes of sulcal and ventricular CSF along with global gray and white matter volumes and cortical thickness were obtained by diffusion tensor imaging (DTI) and T1-weighted (T1w)-based segmentation. These measures were statistically analyzed for associations with CI after adjusting for the age, education in years, lesion load, and disease duration.

RESULTS

Sulcal CSF showed the strongest correlation with CI (r = .51, P = .001) in our cohort, whereas ventricular CSF (P = .28, P = .19) along with cortical thickness and gray matter volume failed to show a significant correlation. Group analyses unadjusted for multiple comparisons showed significant difference in volumes of sulcal CSF and ventricular CSF between MSNI and MSCI groups (P < .05).

CONCLUSION

Sulcal CSF correlates with CI in patients with MS, possibly explained by cortical atrophy. DTI/T1w-based sulcal CSF segmentation method might be used as an indirect and simple neuroimaging marker to monitor CI in MS patients.

Limbic Pathway Correlates of Cognitive Impairment in Multiple Sclerosis

BACKGROUND AND PURPOSE

Distinct injuries to various limbic white matter pathways have been reported to be associated with different aspects of cognitive dysfunction in multiple sclerosis (MS). Diffusion tensor imaging (DTI) offers a noninvasive method to map tissue microstructural organization. We utilized quantitative magnetic resonance imaging methods to analyze the main limbic system-white matter structures in MS patients with cognitive impairment (CI).

METHODS

Ten cognitively nonimpaired MS (MSNI) patients and 36 patients with diagnosed CI (MSCI) underwent the minimal assessment of Cognitive Function in MS (MACFIMS) battery. DTI measures of fornix, cingulum, uncinate fasciculus (UF) included tract volume and corresponding fractional anisotropy (FA), mean (MD), axial (AD), and radial (AD) diffusivities. These were statistically analyzed for associations with CI after adjusting for the confounders.

RESULTS

Fornix FA and RD, left cingulum FA, MD, and RD, right cingulum FA, MD, and RD, and left UF FA showed significant differences between MSNI and MSCI (P < .001). Fornix FA (r = -.6) and RD (r = .52), and right cingulum FA (r = -.54) and RD (r = .5) correlated significantly with CI in regression analyses.

CONCLUSIONS

The extent of disruption of microstructural disorganization in the main limbic pathways using DTI impacts the extent of CI seen in subjects with MS.

Mild Cognitive Impairment is Associated With White Matter Integrity Changes in Late-Myelinating Regions Within the Corpus Callosum

Degenerative brain changes in Alzheimer's disease may occur in reverse order of normal brain development based on the retrogenesis model. This study tested whether evidence of reverse myelination was observed in mild cognitive impairment (MCI) using a data-driven analytic approach based on life span developmental data. Whole-brain high-resolution diffusion tensor imaging scans were obtained for 31 patients with MCI and 79 demographically matched healthy older adults. Comparisons across corpus callosum (CC) regions of interest (ROIs) showed decreased fractional anisotropy (FA) in the body but not in the genu or splenium; early-, middle-, and late-myelinating ROIs restricted to the CC revealed decreased FA in late- but not early- or middle-myelinating ROIs. Voxelwise group differences revealed areas of lower FA in MCI, but whole-brain differences were equally distributed across early-, middle-, and late-myelinating regions. Overall, results within the CC support the retrogenesis model, although caution is needed when generalizing these results beyond the CC.

Brain extraction in pediatric ADC maps, toward characterizing neuro-development in multi-platform and multi-institution clinical images

Apparent Diffusion Coefficient (ADC) maps can be used to characterize myelination and to detect abnormalities in the developing brain. However, given the normal variation in regional ADC with myelination, detection of abnormalities is difficult when based on visual assessment. Quantitative and automated analysis of pediatric ADC maps is thus desired but requires accurate brain extraction as the first step. Currently, most existing brain extraction methods are optimized for structural T1-weighted MR images of fully myelinated brains. Due to differences in age and image contrast, these approaches do not translate well to pediatric ADC maps. To address this problem, we present a multi-atlas brain extraction framework that has 1) specificity: designed and optimized specifically for pediatric ADC maps; 2) generality: applicable to multi-platform and multi-institution data, and to subjects at various neuro-developmental stages across the first 6 years of life; 3) accuracy: highly accurate compared to expert annotations; and 4) consistency: consistently accurate regardless of sources of data and ages of subjects. We show how we achieve these goals, via optimizing major components in a multi-atlas brain extraction framework, and via developing and evaluating new criteria for its atlas ranking component. Moreover, we demonstrate that these goals can be achieved with a fixed set of atlases and a fixed set of parameters, which opens doors for our optimized framework to be used in large-scale and multi-institution neuro-developmental and clinical studies. In a pilot study, we use this framework in a dataset containing scanner-generated ADC maps from 308 pediatric patients collected during the course of routine clinical care. Our framework leads to successful quantifications of the changes in whole-brain volumes and mean ADC values across the first 6 years of life.

Diffusion tensor imaging of the human cerebellar pathways and their interplay with cerebral macrostructure

Cerebellar white matter (WM) connections to the central nervous system are classified functionally into the Spinocerebellar (SC), vestibulocerebellar (VC), and cerebrocerebellar subdivisions. The SC pathways project from spinal cord to cerebellum, whereas the VC pathways project from vestibular organs of the inner ear. Cerebrocerebellar connections are composed of feed forward and feedback connections between cerebrum and cerebellum including the cortico-ponto-cerebellar (CPC) pathways being of cortical origin and the dentate-rubro-thalamo-cortical (DRTC) pathway being of cerebellar origin. In this study we systematically quantified the whole cerebellar system connections using diffusion tensor magnetic resonance imaging (DT-MRI). Ten right-handed healthy subjects (7 males and 3 females, age range 20–51 years) were studied. DT-MRI data were acquired with a voxel size = 2 mm × 2 mm × 2 mm at a 3.0 Tesla clinical MRI scanner. The DT-MRI data were prepared and analyzed using anatomically-guided deterministic tractography methods to reconstruct the SC, DRTC, fronto-ponto-cerebellar (FPC), parieto-ponto-cerebellar (PPC), temporo-ponto-cerebellar (TPC) and occipito-ponto-cerebellar (OPC). The DTI-attributes or the cerebellar tracts along with their cortical representation (Brodmann areas) were presented in standard Montréal Neurological Institute space. All cerebellar tract volumes were quantified and correlated with volumes of cerebral cortical, subcortical gray matter (GM), cerebral WM and cerebellar GM, and cerebellar WM. On our healthy cohort, the ratio of total cerebellar GM-to-WM was ~3.29 ± 0.24, whereas the ratio of cerebral GM-to-WM was approximately 1.10 ± 0.11. The sum of all cerebellar tract volumes is ~25.8 ± 7.3 mL, or a percentage of 1.6 ± 0.45 of the total intracranial volume (ICV).

Application of advanced neuroimaging modalities in pediatric traumatic brain injury

Neuroimaging is commonly used for the assessment of children with traumatic brain injury and has greatly advanced how children are acutely evaluated. More recently, emphasis has focused on how advanced magnetic resonance imaging methods can detect subtler injuries that could relate to the structural underpinnings of the neuropsychological and behavioral alterations that frequently occur. We examine several methods used for the assessment of pediatric brain injury. Susceptibility-weighted imaging is a sensitive 3-dimensional high-resolution technique in detecting hemorrhagic lesions associated with diffuse axonal injury. Magnetic resonance spectroscopy acquires metabolite information, which serves as a proxy for neuronal (and glial, lipid, etc) structural integrity and provides sensitive assessment of neurochemical alterations. Diffusion-weighted imaging is useful for the early detection of ischemic and shearing injury. Diffusion tensor imaging allows better structural evaluation of white matter tracts. These methods are more sensitive than conventional imaging in demonstrating subtle injury that underlies a child's clinical symptoms. There also is an increasing desire to develop computational methods to fuse imaging data to provide a more integrated analysis of the extent to which components of the neurovascular unit are affected. The future of traumatic brain injury neuroimaging research is promising and will lead to novel approaches to predict and improve outcomes.

Visualization and unsupervised predictive clustering of high-dimensional multimodal neuroimaging data

BACKGROUND

Neuroimaging machine learning studies have largely utilized supervised algorithms - meaning they require both neuroimaging scan data and corresponding target variables (e.g. healthy vs. diseased) to be successfully 'trained' for a prediction task. Noticeably, this approach may not be optimal or possible when the global structure of the data is not well known and the researcher does not have an a priori model to fit the data.

NEW METHOD

We set out to investigate the utility of an unsupervised machine learning technique; t-distributed stochastic neighbour embedding (t-SNE) in identifying 'unseen' sample population patterns that may exist in high-dimensional neuroimaging data. Multimodal neuroimaging scans from 92 healthy subjects were pre-processed using atlas-based methods, integrated and input into the t-SNE algorithm. Patterns and clusters discovered by the algorithm were visualized using a 2D scatter plot and further analyzed using the K-means clustering algorithm.

COMPARISON WITH EXISTING METHODS

t-SNE was evaluated against classical principal component analysis.

CONCLUSION

Remarkably, based on unlabelled multimodal scan data, t-SNE separated study subjects into two very distinct clusters which corresponded to subjects' gender labels (cluster silhouette index value=0.79). The resulting clusters were used to develop an unsupervised minimum distance clustering model which identified 93.5% of subjects' gender. Notably, from a neuropsychiatric perspective this method may allow discovery of data-driven disease phenotypes or sub-types of treatment responders.

Distinguishing and quantification of the human visual pathways using high-spatial-resolution diffusion tensor tractography

Quantification of the living human visual system using MRI methods has been challenging, but several applications demand a reliable and time-efficient data acquisition protocol. In this study, we demonstrate the utility of high-spatial-resolution diffusion tensor fiber tractography (DTT) in reconstructing and quantifying the human visual pathways. Five healthy males, age range 24-37years, were studied after approval of the institutional review board (IRB) at The University of Texas Health Science Center at Houston. We acquired diffusion tensor imaging (DTI) data with 1-mm slice thickness on a 3.0-Tesla clinical MRI scanner and analyzed the data using DTT with the fiber assignment by continuous tractography (FACT) algorithm. By utilizing the high-spatial-resolution DTI protocol with FACT algorithm, we were able to reconstruct and quantify bilateral optic pathways including the optic chiasm, optic tract, optic radiations free of contamination from neighboring white matter tracts.

Semi-automated 3D segmentation of major tracts in the rat brain: comparing DTI with standard histological methods

Researchers working with rodent models of neurological disease often require an accurate map of the anatomical organization of the white matter of the rodent brain. With the increasing popularity of small animal MRI techniques, including diffusion tensor imaging (DTI), there is considerable interest in rapid segmentation methods of neurological structures for quantitative comparisons. DTI-derived tractography allows simple and rapid segmentation of major white matter tracts, but the anatomic accuracy of these computer-generated fibers is open to question and has not been rigorously evaluated in the rat brain. In this study, we examine the anatomic accuracy of tractography-based segmentation in the adult rat brain. We analysed 12 major white matter pathways using semi-automated tractography-based segmentation alongside manual segmentation of Gallyas silver-stained histology sections. We applied four fiber-tracking algorithms to the DTI data-two integration methods and two deflection methods. In many cases, tractography-based segmentation closely matched histology-based segmentation; however different tractography algorithms produced dramatically different results. Results suggest that certain white matter pathways are more amenable to tractography-based segmentation than others. We believe that these data will help researchers decide whether it is appropriate to use tractography-based segmentation of white matter structures for quantitative DTI-based analysis of neurologic disease models.

DTI-based segmentation and quantification of human brain lateral ventricular CSF volumetry and mean diffusivity: validation, age, gender effects and biophysical implications

The human brain lateral ventricular (LV) cerebrospinal fluid (CSF) volume has been used as a neuroimaging marker of brain changes in health and disease. The LV CSF diffusivity may offer a useful quality assurance measure and become a potential noninvasive marker of deep brain temperature. In this work we sought to validate a method for human brain lateral ventricular (LV) cerebrospinal fluid (CSF) using diffusion tensor imaging (DTI) contrast to provide LV volume and corresponding DTI metrics. We compared LV volume obtained using DTI with that obtained using validated segmentations of the LV on T1-weighted data. DTI and T1-weighted data were acquired at 3T on 49 healthy males and 56 age-matched females aged 18-59 years. We showed histogram distributions of LV DTI metrics to establish quality assurance measures. We also analyzed the age and gender effects of LV volume and diffusivity. LV volumes estimated using both T1-weighted and DTI correlated strongly in males and females (ICC=0.99; median Dice index ~80%). The LV-to-intracranial volume percentage increased significantly with age only in males, using the DTI-based approach (r=0.39; p=0.005). LV CSF Mean diffusivity was greater in males than females ((~1.2%; p=0.03). Mean diffusivity of lateral ventricular CSF decreased significantly with age in healthy adults (r=-0.30; p=0.02). Our results highlight the importance of age and gender-based analyses and the potential of LV diffusivity measures as a quantitative marker.

Superficial white matter: effects of age, sex, and hemisphere

Structural and diffusion imaging studies demonstrate effects of age, sex, and asymmetry in many brain structures. However, few studies have addressed how individual differences might influence the structural integrity of the superficial white matter (SWM), comprised of short-range association (U-fibers), and intracortical axons. This study thus applied a sophisticated computational analysis approach to structural and diffusion imaging data obtained from healthy individuals selected from the International Consortium for Brain Mapping (ICBM) database across a wide adult age range (n=65, age: 18-74 years, all Caucasian). Fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD) were sampled and compared at thousands of spatially matched SWM locations and within regions-of-interest to examine global and local variations in SWM integrity across age, sex, and hemisphere. Results showed age-related reductions in FA that were more pronounced in the frontal SWM than in the posterior and ventral brain regions, whereas increases in RD and AD were observed across large areas of the SWM. FA was significantly greater in left temporoparietal regions in men and in the posterior callosum in women. Prominent leftward FA and rightward AD and RD asymmetries were observed in the temporal, parietal, and frontal regions. Results extend previous findings restricted to the deep white matter pathways to demonstrate regional changes in the SWM microstructure relating to processes of demyelination and/or to the number, coherence, or integrity of axons with increasing age. SWM fiber organization/coherence appears greater in the left hemisphere regions spanning language and other networks, while more localized sex effects could possibly reflect sex-specific advantages in information strategies.

Maturational differences in thalamocortical white matter microstructure and auditory evoked response latencies in autism spectrum disorders

White matter diffusion anisotropy in the acoustic radiations was characterized as a function of development in autistic and typically developing children. Auditory-evoked neuromagnetic fields were also recorded from the same individuals and the latency of the left and right middle latency superior temporal gyrus auditory ~50ms response (M50)(1) was measured. Group differences in structural and functional auditory measures were examined, as were group differences in associations between white matter pathways, M50 latency, and age. Acoustic radiation white matter fractional anisotropy did not differ between groups. Individuals with autism displayed a significant M50 latency delay. Only in typically developing controls, white matter fractional anisotropy increased with age and increased white matter anisotropy was associated with earlier M50 responses. M50 latency, however, decreased with age in both groups. Present findings thus indicate that although there is loss of a relationship between white matter structure and auditory cortex function in autism spectrum disorders, and although there are delayed auditory responses in individuals with autism than compared with age-matched controls, M50 latency nevertheless decreases as a function of age in autism, parallel to the observation in typically developing controls (although with an overall latency delay). To understand auditory latency delays in autism and changes in auditory responses as a function of age in controls and autism, studies examining white matter as well as other factors that influence auditory latency, such as synaptic transmission, are of interest.

A robust variational approach for simultaneous smoothing and estimation of DTI

Estimating diffusion tensors is an essential step in many applications - such as diffusion tensor image (DTI) registration, segmentation and fiber tractography. Most of the methods proposed in the literature for this task are not simultaneously statistically robust and feature preserving techniques. In this paper, we propose a novel and robust variational framework for simultaneous smoothing and estimation of diffusion tensors from diffusion MRI. Our variational principle makes use of a recently introduced total Kullback-Leibler (tKL) divergence for DTI regularization. tKL is a statistically robust dissimilarity measure for diffusion tensors, and regularization by using tKL ensures the symmetric positive definiteness of tensors automatically. Further, the regularization is weighted by a non-local factor adapted from the conventional non-local means filters. Finally, for the data fidelity, we use the nonlinear least-squares term derived from the Stejskal-Tanner model. We present experimental results depicting the positive performance of our method in comparison to competing methods on synthetic and real data examples.

Diffusion tensor imaging of normal brain development

Diffusion tensor imaging (DTI) is an MRI technique that can measure the macroscopic structural organization in brain tissues. DTI has been shown to provide information complementary to relaxation-based MRI about the changes in the brain's microstructure. In the pediatric population, DTI enables quantitative observation of the maturation process of white matter structures. Its ability to delineate various brain structures during developmental stages makes it an effective tool with which to characterize both the normal and abnormal anatomy of the developing brain. This review will highlight the advantages, as well as the common technical pitfalls of pediatric DTI. In addition, image quantification strategies for various DTI-derived parameters and the normal brain developmental changes associated with these parameters are discussed.

Diffusion tensor quantification of the relations between microstructural and macrostructural indices of white matter and reading

Few researchers agree about the relationship between fronto-temporo-parietal white matter microstructure and reading skills. Unlike many previous reports, which only measured fractional anisotropy, we have also measured macroscopic volume (regional white matter tract volume) and three microstructural indices (axial, radial, and mean diffusivity) to increase interpretability of our findings. We examined the reading-related skills and white matter structure in 10 adolescents and adults with a history of poor reading and 20 age-matched typical readers. We applied a diffusion tensor imaging atlas-based algorithm to major white matter pathways. The relation of white matter structural indices to reading group, hemisphere, and reading-related skill was analyzed using linear models. White matter microstructural indices were related to performance on a sublexical decoding task, but the relations between particular microstructural indices and sublexical decoding ability and reading group were different for association (i.e., cortical-cortical) and projection (i.e., subcortical-cortical) white matter pathways. Changes in projection pathways were consistent with alterations in white matter organization and axonal size, whereas changes in association pathways were consistent with alternations in pathway complexity. Changes in macrostructure paralleled changes in microstructure. We conclude that the relations between several microstructural indices and factors related to reading ability are different for association and projection pathways.

Diffusion based abnormality markers of pathology: toward learned diagnostic prediction of ASD

This paper presents a paradigm for generating a quantifiable marker of pathology that supports diagnosis and provides a potential biomarker of neuropsychiatric disorders, such as autism spectrum disorder (ASD). This is achieved by creating high-dimensional nonlinear pattern classifiers using support vector machines (SVM), that learn the underlying pattern of pathology using numerous atlas-based regional features extracted from diffusion tensor imaging (DTI) data. These classifiers, in addition to providing insight into the group separation between patients and controls, are applicable on a single subject basis and have the potential to aid in diagnosis by assigning a probabilistic abnormality score to each subject that quantifies the degree of pathology and can be used in combination with other clinical scores to aid in diagnostic decision. They also produce a ranking of regions that contribute most to the group classification and separation, thereby providing a neurobiological insight into the pathology. As an illustrative application of the general framework for creating diffusion based abnormality classifiers we create classifiers for a dataset consisting of 45 children with ASD (mean age 10.5 ± 2.5 yr) as compared to 30 typically developing (TD) controls (mean age 10.3 ± 2.5 yr). Based on the abnormality scores, a distinction between the ASD population and TD controls was achieved with 80% leave one out (LOO) cross-validation accuracy with high significance of p<0.001, ~84% specificity and ~74% sensitivity. Regions that contributed to this abnormality score involved fractional anisotropy (FA) differences mainly in right occipital regions as well as in left superior longitudinal fasciculus, external and internal capsule while mean diffusivity (MD) discriminates were observed primarily in right occipital gyrus and right temporal white matter.

Diffusion tensor-based regional gray matter tissue segmentation using the international consortium for brain mapping atlases

In this communication, we extended a previously described and validated diffusion tensor imaging (DTI) method for segmenting whole brain cerebrospinal fluid (CSF) and gray and white matter (WM) tissue to provide regional volume and DTI metrics of WM tract and cortical and subcortical gray matter. This DTI-based regional segmentation was implemented using the statistical parametric mapping (SPM) toolbox and used the international consortium for brain mapping atlases and Montreal Neurological Institute brain templates. We used our DTI-based segmentation approach to calculate the left putamen volume in a cohort of 136 healthy right-handed males and females aged 15.8-62.8 years. We validated our approach by demonstrating its sensitivity to age-related changes of the putamen. Indeed, our method found that the putamen volume decreased with age (r = -0.30; P < 0.001) while the corresponding fractional anisotropy (FA) increased with advancing age (r = 0.5; P < 0.00001). It is then demonstrated, on a subset of our cohort (n = 31), that the putamen volume obtained by our method correlated with measurements obtained from FreeSurfer (r = 0.396, P < 0.05). Our novel approach increases the information obtained with a DTI examination by providing routine volumetry measure, thereby eliminating separate scans to obtain volumetry data. In addition, the labeled volumes obtained with our method have the potential to increase the accuracy of fiber tracking. In the future, this new approach can be automated to analyze large data sets to help discover noninvasive neuroimaging markers for clinical trials and brain-function studies in both health and disease.

Autologous Bone Marrow Mononuclear Cell Therapy for Severe Traumatic Brain Injury in Children

BACKGROUND:

Severe traumatic brain injury (TBI) in children is associated with substantial long-term morbidity and mortality. Currently, there are no successful neuroprotective/neuroreparative treatments for TBI. Numerous preclinical studies suggest that bone marrow-derived mononuclear cells (BMMNCs), their derivative cells (marrow stromal cells), or similar cells (umbilical cord blood cells) offer neuroprotection.

OBJECTIVE:

To determine whether autologous BMMNCs are a safe treatment for severe TBI in children.

METHODS:

Ten children aged 5 to 14 years with a postresuscitation Glasgow Coma Scale of 5 to 8 were treated with 6 × 106 autologous BMMNCs/kg body weight delivered intravenously within 48 hours after TBI. To determine the safety of the procedure, systemic and cerebral hemodynamics were monitored during bone marrow harvest; infusion-related toxicity was determined by pediatric logistic organ dysfunction (PELOD) scores, hepatic enzymes, Murray lung injury scores, and renal function. Conventional magnetic resonance imaging (cMRI) data were obtained at 1 and 6 months postinjury, as were neuropsychological and functional outcome measures.

RESULTS:

All patients survived. There were no episodes of harvest-related depression of systemic or cerebral hemodynamics. There was no detectable infusion-related toxicity as determined by PELOD score, hepatic enzymes, Murray lung injury scores, or renal function. cMRI imaging comparing gray matter, white matter, and CSF volumes showed no reduction from 1 to 6 months postinjury. Dichotomized Glasgow Outcome Score at 6 months showed 70% with good outcomes and 30% with moderate to severe disability.

CONCLUSION:

Bone marrow harvest and intravenous mononuclear cell infusion as treatment for severe TBI in children is logistically feasible and safe.

Superior longitudinal fasciculus and cognitive dysfunction in adolescents born preterm and at term

AIM

To understand the relationship between cognition and white-matter structure in adolescents born preterm without obvious brain injury.

METHODS

Thirty-two adolescents from a longitudinal study of child development were selected according to risk of developmental disorders at birth (born at term: eight males, five females; median age 16y 1mo, interquartile range 10mo; low risk preterm: four males, five females, median age 16y, range 4mo; high risk preterm: three males, seven females, median age 16y 2mo, range 1y 2mo) and reading ability (good: three males, eight females, median age 16y, range 7mo; average: six males, three females, median age 16y 10mo, range 1y; poor: six males, six females, median age 16y, range 6mo). Preterm birth was defined as a gestational age of 36 weeks or less and a birthweight of 1600g or less. All participants had normal clinical neuroimaging findings. We examined fractional anisotropy, radial diffusivity, and volume of three major white-matter fasciculi. The relationship between structural measures and birth risk, hemisphere, and cognitive ability (attention, lexical and sublexical decoding, auditory phonological awareness, and processing speed) were analysed using mixed-model regression.

RESULTS

Left-hemisphere superior longitudinal fasciculus (SLF) fractional anisotropy and radial diffusivity were linked to reading-related skills (fractional anisotropy vs letter-word identification, r((30))=-0.37, p<0.05; fractional anisotropy vs phoneme reversal, r((30))=-0.34, p=0.05; radial diffusivity vs letter-word identification, r((30))=0.31, p<0.10; radial diffusivity vs phoneme reversal, r((30))=0.40, p<0.05), whereas right-hemisphere SLF fractional anisotropy was related to attention skills (fractional anisotropy vs inattentiveness, r((30))=-0.38, p<0.05). SLF volume decreased as these skills declined for adolescents born preterm (volume vs phoneme reversal, r((17))=0.58, p<0.01; volume vs inattentiveness, r((17))=-0.69, p<0.01), but not for those born at term.

INTERPRETATION

The relationship between cognitive skills and SLF volume suggests that in adolescents born preterm, cryptic white-matter injury may exist, possibly related to oligodendrocyte or axonal loss, despite normal clinical neuroimaging.

Diffusion tensor quantification of the relations between microstructural and macrostructural indices of white matter and reading

Few researchers agree about the relationship between fronto-temporo-parietal white matter microstructure and reading skills. Unlike many previous reports, which only measured fractional anisotropy, we have also measured macroscopic volume (regional white matter tract volume) and three microstructural indices (axial, radial, and mean diffusivity) to increase interpretability of our findings. We examined the reading-related skills and white matter structure in 10 adolescents and adults with a history of poor reading and 20 age-matched typical readers. We applied a diffusion tensor imaging atlas-based algorithm to major white matter pathways. The relation of white matter structural indices to reading group, hemisphere, and reading-related skill was analyzed using linear models. White matter microstructural indices were related to performance on a sublexical decoding task, but the relations between particular microstructural indices and sublexical decoding ability and reading group were different for association (i.e., cortical-cortical) and projection (i.e., subcortical-cortical) white matter pathways. Changes in projection pathways were consistent with alterations in white matter organization and axonal size, whereas changes in association pathways were consistent with alternations in pathway complexity. Changes in macrostructure paralleled changes in microstructure. We conclude that the relations between several microstructural indices and factors related to reading ability are different for association and projection pathways.

Atlas-based analysis of neurodevelopment from infancy to adulthood using diffusion tensor imaging and applications for automated abnormality detection

Quantification of normal brain maturation is a crucial step in understanding developmental abnormalities in brain anatomy and function. The aim of this study was to develop atlas-based tools for time-dependent quantitative image analysis, and to characterize the anatomical changes that occur from 2years of age to adulthood. We used large deformation diffeomorphic metric mapping to register diffusion tensor images of normal participants into the common coordinates and used a pre-segmented atlas to segment the entire brain into 176 structures. Both voxel- and atlas-based analyses reported a structure that showed distinctive changes in terms of its volume and diffusivity measures. In the white matter, fractional anisotropy (FA) linearly increased with age in logarithmic scale, while diffusivity indices, such as apparent diffusion coefficient (ADC), and axial and radial diffusivity, decreased at a different rate in several regions. The average, variability, and the time course of each measured parameter are incorporated into the atlas, which can be used for automated detection of developmental abnormalities. As a demonstration of future application studies, the brainstem anatomy of cerebral palsy patients was evaluated and the altered anatomy was delineated.

Microstructural correlations of white matter tracts in the human brain

The purpose of this study is to investigate whether specific patterns of correlation exist in diffusion tensor imaging (DTI) parameters across different white matter tracts in the normal human brain, and whether the relative strengths of these putative microstructural correlations might reflect phylogenetic and functional similarities between tracts. We performed quantitative DTI fiber tracking on 44 healthy adult volunteers to obtain tract-based measures of mean diffusivity (MD), fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) from four homologous pairs of neocortical association pathways (arcuate fasciculi, inferior fronto-occipital fasciculi, inferior longitudinal fasciculi, and uncinate fasciculi bilaterally), a homologous pair of limbic association pathways (left and right dorsal cingulum bundles), and a homologous pair of cortical-subcortical projection pathways (left and right corticospinal tracts). From the resulting inter-tract correlation matrices, we show that there are statistically significant correlations of DTI parameters between tracts, and that there are statistically significant variations among these inter-tract correlations. Furthermore, we observe that many, but by no means all, of the strongest correlations are between homologous tracts in the left and right hemispheres. Even among homologous pairs of tracts, there are wide variations in the degree of coupling. Finally, we generate a data-driven hierarchical clustering of the fiber pathways based on pairwise FA correlations to demonstrate that the neocortical association pathways tend to group separately from the limbic pathways at trend-level statistical significance, and that the projection pathways of the left and right corticospinal tracts comprise the most distant outgroup with high confidence (p<0.01). Hence, specific patterns of microstructural correlation exist between tracts and may reflect phylogenetic and functional similarities between tracts. The study of these microstructural relationships between white matter pathways might aid research on the genetic basis and on the behavioral effects of axonal connectivity, as well as provide a revealing new perspective with which to investigate neurological and psychiatric disorders.

Developmental correlation of diffusion anisotropy with auditory-evoked response

White matter diffusion anisotropy in the acoustic radiations of the auditory pathway was characterized as a function of development in children and adolescents. Auditory-evoked neuromagnetic fields were also recorded from the same individuals, and the latency of the left and right superior temporal gyrus auditory response of approximately 100 ms was also obtained. White matter diffusion anisotropy increased with age. There was a commensurate shortening of the auditory-evoked response latency with increased age as well as with increased white matter diffusion anisotropy. The significant negative correlation between structural integrity of white matter pathways and electrophysiological function (response timing) of distal cortex supports a biophysical model of developmental changes in white matter myelination, conduction velocity, and cortical response timing.

Diffusion tensor imaging in cocaine dependence: regional effects of cocaine on corpus callosum and effect of cocaine administration route

Recent studies demonstrated that diffusion tensor imaging (DTI) can provide information regarding white matter integrity of the corpus callosum (CC). In this study, DTI parameters were compared between cocaine dependent subjects (CDs) and non-drug using controls (NCs) in midsagittal CC. DTI images were acquired from 19 CDs and 18 age-matched NCs. The midsagittal CC was segmented into: genu, rostral body, anterior midbody, posterior midbody, isthmus, and splenium. Linear mixed models analyses showed that, relative to NCs, CDs had lower fractional anisotropy (FA), higher radial diffusivity (lambda(perpendicular)), and higher mean diffusivity (D(av)) in the isthmus; higher lambda(perpendicular) and D(av) in the rostral body; and lower FA in the splenium. After including mass of lifetime alcohol use in the mixed model analysis of covariance (ANCOVA) as a covariate, significant between group differences in lambda(perpendicular) in the rostral body and isthmus remained. These results suggest that alterations in lambda(perpendicular) in the rostral body and isthmus were mainly due to cocaine use, consistent with previous studies showing that cocaine may alter myelin integrity. Between group differences in FA in the isthmus and splenium, and D(av) in the rostral body and isthmus became non-significant after inclusion of alcohol use as a covariate. This is suggestive of alcohol influencing these values, or may be related to the decreased degrees of freedom for these effects. Consistent with clinical data of greater severity of drug use in smoked versus intranasal cocaine, subjects who smoked cocaine showed lower FA and higher lambda(perpendicular) compared to intranasal CDs.

Longitudinal changes in grey and white matter during adolescence

Brain development continues actively during adolescence. Previous MRI studies have shown complex patterns of apparent loss of grey matter (GM) volume and increases in white matter (WM) volume and fractional anisotropy (FA), an index of WM microstructure. In this longitudinal study (mean follow-up=2.5+/-0.5 years) of 24 adolescents, we used a voxel-based morphometry (VBM)-style analysis with conventional T1-weighted images to test for age-related changes in GM and WM volumes. We also performed tract-based spatial statistics (TBSS) analysis of diffusion tensor imaging (DTI) data to test for age-related WM changes across the whole brain. Probabilistic tractography was used to carry out quantitative comparisons across subjects in measures of WM microstructure in two fiber tracts important for supporting speech and motor functions (arcuate fasciculus [AF] and corticospinal tract [CST]). The whole-brain analyses identified age-related increases in WM volume and FA bilaterally in many fiber tracts, including AF and many parts of the CST. FA changes were mainly driven by increases in parallel diffusivity, probably reflecting increases in the diameter of the axons forming the fiber tracts. FA values of both left and right AF (but not of the CST) were significantly higher at the end of the follow-up than at baseline. Over the same period, widespread reductions in the cortical GM volume were found. These findings provide imaging-based anatomical data suggesting that brain maturation in adolescence is associated with structural changes enhancing long-distance connectivities in different WM tracts, specifically in the AF and CST, at the same time that cortical GM exhibits synaptic "pruning".

Mapping the human brain white matter tracts relative to cortical and deep gray matter using diffusion tensor imaging at high spatial resolution

The mapping of the human brain white matter fiber networks relative to deep subcortical and cortical gray matter requires high spatial resolution which is challenged by the low signal-to-noise ratio. The purpose of this short report was to introduce a whole brain high spatial resolution diffusion tensor imaging (DTI) protocol that enabled for the first time the mapping of corticopontocerebellar, frontostriatal and thalamofrontal fiber pathways in addition to other limbic, commissural, association and projection white matter pathways relative to the segmented deep gray (e.g., caudate nuclei) and the cortical lobes. Our DTI acquisition protocol and analysis strategy provide important template for brain-behavior research and for teaching brain mapping and are clinically affordable for patient comfort.

Splenium microstructure is related to two dimensions of reading skill

Inconsistent differences in the corpus callosum (CC) structure between dyslexic readers (DRs) and typical readers (TRs) have been reported. We examine differences in CC splenium microstructure and the association of splenium microstructure with reading-related skills. Nine DRs and 18 TRs completed a reading skills battery and diffusion tensor imaging. DRs had higher splenium fractional anisotropy (FA) and axial diffusivity (LA) as compared with TRs. Retrieval of orthographic information from the language lexicon was negatively associated with FA and LA within both reading groups. Phonological awareness was positively associated with splenium FA and LA in TRs but not DRs. This study suggests two white matter pathways that may be differentially associated with reading skills in the CC splenium.

Diffusion tensor quantification of the macrostructure and microstructure of human midsagittal corpus callosum across the lifespan

The midsagittal cross-sectional area of the human corpus callosum (CC) has been used by many researchers as a marker of development, natural aging, and neurodegenerative and acquired pathologies. The availability of non-invasive MRI methods for quantifying the macrostructural and microstructural organization of the CC would help to clarify the CC contribution to behavior and cognition in both health and disease. In this report, we extended and validated the ability of a recently described semi-automated diffusion tensor imaging tissue segmentation method to utilize the high orientation contrast of the CC on diffusion tensor imaging. Using a cohort of healthy right-handed children and adults aged 7-59 years, we show gender-independent non-linear (quadratic) and strongly correlated growth trends in the CC area and the corresponding diffusion tensor fractional anisotropy (r = 0.67; P < 1 x 10(-10)). Our results provide preliminary evidence that diffusion tensor anisotropy in the living CC may be related to the number of small myelinated fibers.

Diffusion tensor tractography quantification of the human corpus callosum fiber pathways across the lifespan

Several anatomical attributes of the human corpus callosum (CC) including the midsagittal cross-sectional area, thickness, and volume, have been used to assess CC integrity. We extended our previous lifespan quantitative diffusion tensor imaging (DTI) study of the regional CC midsagittal areas to include the CC volumes obtained from DTI fiber tracking. In addition to the entire CC tracked subvolumes we normalized volume with respect to each subject's intracranial volume (ICV) and the corresponding DTI metrics of the different specialized fiber pathways of the CC on a cohort of 99 right-handed children and adults aged 7-59 years. Results indicated that the CC absolute volume, the normalized volume fraction, and the fractional anisotropy followed inverted U-shaped curves, while the radial diffusivities followed a U-shaped curve reflecting white matter progressive and regressive myelination dynamics that continue into young adulthood. Our study provides for the first time normative baseline macro- and microstructural age trajectories of the human CC subvolumes across the lifespan that can be helpful for normative behavioral and clinical studies.

Arrested development and disrupted callosal microstructure following pediatric traumatic brain injury: relation to neurobehavioral outcomes

Chronic pediatric traumatic brain injury (TBI) is associated with significant and persistent neurobehavioral deficits. Using diffusion tensor imaging (DTI), we examined area, fractional anisotropy (FA), radial diffusion, and axial diffusion from six regions of the corpus callosum (CC) in 41 children and adolescents with TBI and 31 comparison children. Midsagittal cross-sectional area of the posterior body and isthmus was similar in younger children irrespective of injury status; however, increased area was evident in the older comparison children but was obviated in older children with TBI, suggesting arrested development. Similarly, age was correlated significantly with indices of tissue microstructure only for the comparison group. TBI was associated with significant reduction in FA and increased radial diffusivity in the posterior third of the CC and in the genu. The axial diffusivity did not differ by either age or group. Logistic regression analyses revealed that FA and radial diffusivity were equally sensitive to post-traumatic changes in 4 of 6 callosal regions; radial diffusivity was more sensitive for the rostral midbody and splenium. IQ, working memory, motor, and academic skills were correlated significantly with radial diffusion and/or FA from the isthmus and splenium only in the TBI group. Reduced size and microstructural changes in posterior callosal regions after TBI suggest arrested development, decreased organization, and disrupted myelination. Increased radial diffusivity was the most sensitive DTI-based surrogate marker of the extent of neuronal damage following TBI; FA was most strongly correlated with neuropsychological outcomes.

Relationship between white matter volume and cognitive performance during adolescence: effects of age, sex and risk for drug use

AIM

Familial drug abuse history has been shown to have an impact on cognitive development during adolescence. The present study examined the relationship between white matter volume and cognitive processing speed in adolescents with and without a familial substance abuse history.

PARTICIPANTS

The sample comprised 33 female and male adolescents stratified by risk (family history positive, FH+) and low-risk (FH-) groups.

MEASUREMENTS

Gray and white matter volumes were measured by segmenting magnetic resonance imaging (MRI) data. The neurocognitive test battery included tests that assessed processing speed, verbal ability and mental flexibility.

FINDINGS

Age-related differences in neuropsychological functioning were seen but did not differ by risk group status, although there was some evidence for an age x gender effect. Information processing speed (digit symbol and Stroop word color naming) was correlated significantly with white matter volume; however, this pattern was observed only in FH- females. Cognitive performance and tissue volumes did not differ significantly between risk groups.

CONCLUSIONS

Age-related differences in neuropsychological functioning were seen that might, in larger samples, prove to be related to risk for substance abuse in adolescents who have not yet initiated drug use.

Quantitative diffusion tensor imaging and intellectual outcomes in spina bifida: laboratory investigation

OBJECT

Patients with spina bifida (SB) have variable intellectual outcomes. The authors used diffusion tensor (DT) imaging to quantify whole-brain volumes of gray matter, white matter, and cerebrospinal fluid (CSF), and perform regional quantitative microstructural assessments of gray matter nuclei and white matter tracts in relation to intellectual outcomes in patients with SB.

METHODS

Twenty-nine children with myelomeningoceles and 20 age- and sex-matched children with normal neural tube development underwent MR imaging with DT image acquisition and assessments of intelligence. The DT imaging-derived metrics were the fractional anisotropy (FA), axial (parallel), and transverse (perpendicular) diffusivities. These metrics were also used to segment the brain into white matter, gray matter, and CSF. A region-of-interest analysis was conducted of the white and gray matter structures implicated in hydrocephalus.

RESULTS

The amount of whole-brain gray matter was decreased in patients with SB, with a corresponding increase in CSF (p < 0.0001). Regional transverse diffusivity in the caudate nucleus was decreased (p < 0.0001), and the corresponding FA was increased (p < 0.0001), suggesting reduced dendritic branching and connectivity. Fractional anisotropy in the posterior limb of the internal capsule increased in the myelomeningocele group (p = 0.02), suggesting elimination of some divergent fascicles; in contrast, the FA in several white matter structures (such as the corpus callosum genu [p < 0.001] and arcuate fasciculus) was reduced, suggesting disruption of myelination. Diffusion tensor imaging-metrics involving gray matter volume and the caudate nucleus, but not other structures, predicted variations in IQ (r = 0.37-0.50; p < 0.05).

CONCLUSIONS

Diffusion tensor imaging-derived metrics provide noninvasive neuronal surrogate markers of the pathogenesis of SB and predict variations in general intellectual outcomes in children with this condition.

Diffusion tensor quantification of the human midsagittal corpus callosum subdivisions across the lifespan

The midsagittal corpus callosum (CC) cross-sectional area subdivisions have been used as early and sensitive markers of human brain white matter connectivity, development, natural aging and disease. Despite the simplicity and conspicuity of the appearance of the CC on anatomical magnetic resonance imaging (MRI), the published quantitative MRI literature on its regional sex and age trajectories are contradictory. The availability of noninvasive quantitative methods to assess the CC regions across the human lifespan would help clarify its contribution to behavior and cognition. In this report, we extended the utility of a recently described semi-automated diffusion tensor imaging (DTI) tissue segmentation method to utilize the high orientation contrast of the CC on DTI. Using optimized DTI methods on a cohort of 121 right-handed children and adults aged 6-68 years, we examined the CC areas and corresponding DTI metrics of the different functionally specialized sectors of the CC. Both the area and fractional anisotropy metrics followed inverted U-shaped curves, while the mean and radial diffusivities followed U-curves reflecting white matter progressive and regressive myelination dynamics that continue into young adulthood.

Prematurely born children demonstrate white matter microstructural differences at 12 years of age, relative to term control subjects: an investigation of group and gender effects

OBJECTIVE

The goal was to use diffusion tensor imaging to test the hypothesis that prematurely born children demonstrate long-term, white matter, microstructural differences, relative to term control subjects.

METHODS

Twenty-nine preterm subjects (birth weight: 600-1250 g) without neonatal brain injury and 22 matched, term, control subjects were evaluated at 12 years of age with MRI studies, including diffusion tensor imaging and volumetric imaging; voxel-based morphometric strategies were used to corroborate regional diffusion tensor imaging results. Subjects also underwent neurodevelopmental assessments.

RESULTS

Neurodevelopmental assessments showed significant differences in full-scale, verbal, and performance IQ and Developmental Test of Visual Motor Integration scores between the preterm and term control subjects. Diffusion tensor imaging studies demonstrated widespread decreases in fractional anisotropy (a measure of fiber tract organization) in the preterm children, compared with the control subjects. Regions included both intrahemispheric association fibers subserving language skills, namely, the right inferior frontooccipital fasciculus and anterior portions of the uncinate fasciculi bilaterally, and the deep white matter regions to which they project, as well as the splenium of the corpus callosum. These changes in fractional anisotropy occurred in subjects with significant differences in frontal, temporal, parietal, and deep white matter volumes. Fractional anisotropy values in the left anterior uncinate correlated with verbal IQ, full-scale IQ, and Peabody Picture Vocabulary Test-Revised scores for preterm male subjects. In addition, preterm male subjects were found to have the lowest values for fractional anisotropy in the right anterior uncinate fasciculus, and fractional anisotropy values in that region correlated with both verbal IQ and Peabody Picture Vocabulary Test-Revised scores for the preterm groups; these findings were supported by changes identified with voxel-based morphometric analyses.

CONCLUSIONS

Compared with term control subjects, prematurely born children with no neonatal ultrasound evidence of white matter injury manifest changes in neural connectivity at 12 years of age.

Development and organization of the human brain tissue compartments across the lifespan using diffusion tensor imaging

We used a diffusion tensor imaging-based whole-brain tissue segmentation to characterize age-related changes in (a) whole-brain grey matter, white matter, and cerebrospinal fluid relative to intracranial volume and (b) the corresponding brain tissue microstructure using measures of diffusion tensor anisotropy and mean diffusivity. The sample, a healthy cohort of 119 right-handed males and females aged 7-68 years. Our results demonstrate that white matter and grey matter volumes and their corresponding diffusion tensor anisotropy and mean diffusivity follow nonlinear trajectories with advancing age. In contrast, cerebrospinal fluid volume increases linearly with age.

Quantitative diffusion tensor imaging detects dopaminergic neuronal degeneration in a murine model of Parkinson's disease

Early diagnosis of Parkinson's disease (PD) is required to improve therapeutic responses. Indeed, a clinical diagnosis of resting tremor, rigidity, movement and postural deficiencies usually reflect >50% loss of the nigrostriatal system in disease. In a step to address this, quantitative diffusion tensor magnetic resonance imaging (DTI) was used to assess nigrostriatal degeneration in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) intoxication model of dopaminergic nigral degeneration. We now demonstrate increased average diffusion (p<0.005) and decreased fractional anisotropy (p<0.03) in the substantia nigra (SN) of 5- to 7-day MPTP-treated animals when compared to saline controls. Transverse diffusivity demonstrated the most significant differences (p < or = 0.002) and correlated with the numbers of SN dopaminergic neurons (r=-0.75, p=0.012). No differences were found in the striatum, corpus callosum, cerebral cortex, or ventricles. These results demonstrate that DTI may be used as a surrogate biomarker of nigral dopaminergic neuronal degeneration.

Quantitative diffusion tensor tractography of association and projection fibers in normally developing children and adolescents

Whole-brain diffusion tensor tractography (DTT) at high signal-to-noise ratio and angular and spatial resolutions were utilized to study the effects of age, sex differences, and lateral asymmetries of 6 white matter pathways (arcuate fasciculus [AF], inferior longitudinal fasciculus, inferior fronto-occipital fasciculus [IFOF], uncinate fasciculus [UF], corticospinal tract [CST], and somatosensory pathway [SS]) in 31 right-handed children (6-17 years). Fractional anisotropy (FA), a measure of the orientational variance in water molecular diffusivity, and the magnitude of water diffusivity (parallel, perpendicular, and mean diffusivity) along the pathways were quantified. Three major patterns of maturation were observed: 1) significant increase in FA with age, accompanied by significant decreases in all 3 diffusivities (e.g., left IFOF); 2) significant decreases in all three diffusivities with age without significant changes in FA (e.g., left CST); and 3) no significant age-related changes in FA or diffusivity (e.g., SS). Sex differences were minimal. Many pathways showed lateral asymmetries. In the right hemisphere, the frontotemporal (FT) segment of AF was not visualized in a substantial (29%) number of participants. FA was higher in the left hemisphere in the FT segment of AF, UF, and CST, whereas it was lower in the frontoparietal segment of AF. This study provides normative data essential for the interpretation of pediatric brain DTT measurements in both health and disease.