The effect of template selection on diffusion tensor voxel-based analysis results

A Novel Registration Framework for Aligning Longitudinal Infant Brain Tensor Images

Registering longitudinal infant brain images is challenging, as the infant brain undergoes rapid changes in size, shape and tissue contrast in the first months and years of life. Diffusion tensor images (DTI) have relatively consistent tissue properties over the course of infancy compared to commonly used T1 or T2-weighted images, presenting great potential for infant brain registration. Moreover, groupwise registration has been widely used in infant neuroimaging studies to reduce bias introduced by predefined atlases that may not be well representative of samples under study. To date, however, no methods have been developed for groupwise registration of tensor-based images. Here, we propose a novel registration approach to groupwise align longitudinal infant DTI images to a sample-specific common space. Longitudinal infant DTI images are first clustered into more homogenous subgroups based on image similarity using Louvain clustering. DTI scans are then aligned within each subgroup using standard tensor-based registration. The resulting images from all subgroups are then further aligned onto a sample-specific common space. Results show that our approach significantly improved registration accuracy both globally and locally compared to standard tensor-based registration and standard fractional anisotropy-based registration. Additionally, clustering based on image similarity yielded significantly higher registration accuracy compared to no clustering, but comparable registration accuracy compared to clustering based on chronological age. By registering images groupwise to reduce registration bias and capitalizing on the consistency of features in tensor maps across early infancy, our groupwise registration framework facilitates more accurate alignment of longitudinal infant brain images.

Individual differences of white matter characteristic along the anterior insula-based fiber tract circuit for pain empathy in healthy women and women with primary dysmenorrhea

Pain empathy, defined as the ability of one person to understand another person's pain, shows large individual variations. The anterior insula is the core region of the pain empathy network. However, the relationship between white matter (WM) properties of the fiber tracts connecting the anterior insula with other cortical regions and an individual's ability to modulate pain empathy remains largely unclear. In this study, we outline an automatic seed-based fiber streamline (sFS) analysis method and multivariate pattern analysis (MVPA) to predict the levels of pain empathy in healthy women and women with primary dysmenorrhoea (PDM). Using the sFS method, the anterior insula-based fiber tract network was divided into five fiber cluster groups. In healthy women, interindividual differences in pain empathy were predicted only by the WM properties of the five fiber cluster groups, suggesting that interindividual differences in pain empathy may rely on the connectivity of the anterior insula-based fiber tract network. In women with PDM, pain empathy could be predicted by a single cluster group. The mean WM properties along the anterior insular-rostroventral area of the inferior parietal lobule further mediated the effect of pain on empathy in patients with PDM. Our results suggest that chronic periodic pain may lead to maladaptive plastic changes, which could further impair empathy by making women with PDM feel more pain when they see other people experiencing pain. Our study also addresses an important gap in the analysis of the microstructural characteristics of seed-based fiber tract network.

Diminished baseline autonomic outflow in semantic dementia relates to left-lateralized insula atrophy

In semantic dementia (SD), asymmetric degeneration of the anterior temporal lobes is associated with loss of semantic knowledge and alterations in socioemotional behavior. There are two clinical variants of SD: semantic variant primary progressive aphasia (svPPA), which is characterized by predominant atrophy in the anterior temporal lobe and insula in the left hemisphere, and semantic behavioral variant frontotemporal dementia (sbvFTD), which is characterized by predominant atrophy in those structures in the right hemisphere. Previous studies of behavioral variant frontotemporal dementia, an associated clinical syndrome that targets the frontal lobes and anterior insula, have found impairments in baseline autonomic nervous system activity that correlate with left-lateralized frontotemporal atrophy patterns and disruptions in socioemotional functioning. Here, we evaluated whether there are similar impairments in resting autonomic nervous system activity in SD that also reflect left-lateralized atrophy and relate to diminished affiliative behavior. A total of 82 participants including 33 people with SD (20 svPPA and 13 sbvFTD) and 49 healthy older controls completed a laboratory-based assessment of respiratory sinus arrhythmia (RSA; a parasympathetic measure) and skin conductance level (SCL; a sympathetic measure) during a two-minute resting baseline period. Participants also underwent structural magnetic resonance imaging, and informants rated their current affiliative behavior on the Interpersonal Adjective Scale. Results indicated that baseline RSA and SCL were lower in SD than in healthy controls, with significant impairments present in both svPPA and sbvFTD. Voxel-based morphometry analyses revealed left-greater-than-right atrophy related to diminished parasympathetic and sympathetic outflow in SD. While left-lateralized atrophy in the mid-to-posterior insula correlated with lower RSA, left-lateralized atrophy in the ventral anterior insula correlated with lower SCL. In SD, lower baseline RSA, but not lower SCL, was associated with lower gregariousness/extraversion. Neither autonomic measure related to warmth/agreeableness, however. Through the assessment of baseline autonomic nervous system physiology, the present study contributes to expanding conceptualizations of the biological basis of socioemotional alterations in svPPA and sbvFTD.

Disrupted white matter integrity in primary insomnia and major depressive disorder: relationships to sleep quality and depression severity

This study examined the integrity of white matter tracts in 25 participants with primary insomnia (PI), 50 participants with major depressive disorder (MDD), and 25 healthy controls. Seven white matter tracts, selected based on prior research, were quantified by fractional anisotropy (FA) as well as by related measures of diffusivity using diffusion tensor imaging (DTI) on a 3-T scanner. All 100 participants were free of significant medical, psychiatric (excluding the MDD group) and sleep disorders (excluding the PI group), were free of central nervous system medications, and completed an extensive clinical assessment. Subjective and objective sleep measures revealed significant sleep disruption in both the PI and MDD groups. Relative to the controls, both the PI and MDD groups demonstrated impaired integrity in three of the seven white matter tracts: the genu of the corpus callosum (GenuCC), the superior longitudinal fasciculus (SLF), and the inferior longitudinal fasciculus (ILF). We demonstrated reduced FA in the GenuCC, reduced FA and reduced axial diffusivity (AD) in the SLF, as well as reduced AD and radial diffusivity in the ILF. Finally, in an exploratory analysis of the combined cohorts, FA in the GenuCC and FA in the SLF were negatively correlated with depression severity and positively correlated with total sleep time. Abnormalities documented in the GenuCC, SLF and ILF, and present in both the PI and MDD groups may suggest some shared neurobiology.

Development of high quality T1-weighted and diffusion tensor templates of the older adult brain in a common space

High-quality T1-weighted (T1w) and diffusion tensor imaging (DTI) brain templates that are representative of the individuals under study enhance the accuracy of template-based neuroimaging investigations, and when they are also located in a common space they facilitate optimal integration of information on brain morphometry and diffusion characteristics. However, such multimodal templates have not been constructed for the brain of older adults. The purpose of this work was threefold: (A) to introduce an iterative method for construction of multimodal T1w and DTI templates that aims at maximizing the quality of each template separately as well as the spatial matching between templates, (B) to use this method to develop T1w and DTI templates of the older adult brain in a common space, and (C) to evaluate the performance of the method across iterations and compare it to the performance of state-of-the-art approaches based on multichannel registration. It was demonstrated that more iterations of the proposed method enhanced the characteristics and spatial matching of the resulting T1w and DTI templates. The templates of the older adult brain generated by the final iteration of the proposed method provided better delineation of brain structures, higher discriminability between tissues, and higher image sharpness near the cortex compared to templates generated with approaches employing multichannel registration. In addition, the spatial matching between the T1w and DTI templates constructed by the proposed method approximated the template alignment achieved with methods employing multichannel registration. Finally, when using the templates generated by the proposed method as references for spatial normalization of older adult T1w and DTI data, both the intra-modality inter-subject normalization precision and the inter-modality spatial matching were higher in most metrics than those achieved with templates constructed with other methods. Overall, the present work brought new insights into multimodal template construction, generated much-needed high quality T1w and DTI templates of the older adult brain in a common space, and conducted a thorough, quantitative evaluation of available multimodal template construction methods.

Multi sequence average templates for aging and neurodegenerative disease populations

Magnetic resonance image (MRI) processing pipelines use average templates to enable standardization of individual MRIs in a common space. MNI-ICBM152 is currently used as the standard template by most MRI processing tools. However, MNI-ICBM152 represents an average of 152 healthy young adult brains and is vastly different from brains of patients with neurodegenerative diseases. In those populations, extensive atrophy might cause inevitable registration errors when using an average template of young healthy individuals for standardization. Disease-specific templates that represent the anatomical characteristics of the populations can reduce such errors and improve downstream driven estimates. We present multi-sequence average templates for Alzheimer's Dementia (AD), Fronto-temporal Dementia (FTD), Lewy Body Dementia (LBD), Mild Cognitive Impairment (MCI), cognitively intact and impaired Parkinson's Disease patients (PD-CIE and PD-CI, respectively), individuals with Subjective Cognitive Impairment (SCI), AD with vascular contribution (V-AD), Vascular Mild Cognitive Impairment (V-MCI), Cognitively Intact Elderly (CIE) individuals, and a human phantom. We also provide separate templates for males and females to allow better representation of the diseases in each sex group.

Development and evaluation of a high resolution 0.5mm isotropic T1-weighted template of the older adult brain

Investigating the structure of the older adult brain at high spatial resolution is of high significance, and a dedicated older adult structural brain template with sub-millimeter resolution is currently lacking. Therefore, the purpose of this work was twofold: (A) to develop a 0.5mm isotropic resolution standardized T1-weighted template of the older adult brain by applying principles of super resolution to high quality MRI data from 222 older adults (65-95 years of age), and (B) to systematically compare the new template to other standardized and study-specific templates in terms of image quality and performance when used as a reference for alignment of older adult data. The new template exhibited higher spatial resolution and improved visualization of fine structural details of the older adult brain compared to a template constructed using a conventional template building approach and the same data. In addition, the new template exhibited higher image sharpness and did not contain image artifacts observed in some of the other templates considered in this work. Due to the above enhancements, the new template provided higher inter-subject spatial normalization precision for older adult data compared to the other templates, and consequently enabled detection of smaller inter-group morphometric differences in older adult data. Finally, the new template was among those that were most representative of older adult brain data. Overall, the new template constructed here is an important resource for studies of aging, and the findings of the present work have important implications in template selection for investigations on older adults.

A systematic review of diffusion tensor imaging studies in obesity

Obesity is a major global health problem leading to serious complications. It has been consistently associated with alterations in brain structure. Diffusion tensor imaging is used to examine brain white matter microstructure by assessing the dynamics of water diffusion in white matter tracts. Fractional anisotropy and mean diffusivity are two parameters measuring the directionality and rate of diffusion, respectively. Changes in these indices associated with obesity have been previously reported in numerous fiber tracts. This systematic review investigates microstructural white matter alterations in obesity using diffusion tensor imaging. A computerized search was performed in PubMed, Web of Science, and Livivo databases. Based on the inclusion/exclusion criteria, 31 cross-sectional studies comparing individuals with obesity and lean controls were identified. The studies included mixed-gender samples of children, young, middle-aged, and older adults. The majority of included studies reported decreased fractional anisotropy and increased mean diffusivity associated with elevated body mass index, suggesting white matter abnormalities. Nevertheless, a pattern of alterations is inconsistent across studies. This could be explained by several potential biases assessed by the National Institute of Health quality assessment tool. Furthermore, a direct assessment of body fat is recommended for a more accurate characterization of the brain-body relationship.

Measuring decline in white matter integrity after systemic treatment for breast cancer: omitting skeletonization enhances sensitivity

Chemotherapy for non-central nervous system cancers is associated with abnormalities in brain structure and function. Diffusion tensor imaging (DTI) allows for studying in vivo microstructural changes in brain white matter. Tract-based spatial statistics (TBSS) is a widely used processing pipeline in which DTI data are typically normalized to a generic DTI template and then 'skeletonized' to compensate for misregistration effects. However, this approach greatly reduces the overall white matter volume that is subjected to statistical analysis, leading to information loss. Here, we present a re-analysis of longitudinal data previously analyzed with standard TBSS (Menning et al., BIB 2018, 324-334). For our current approach, we constructed a pipeline with an optimized registration method in Advanced Normalization Tools (ANTs) where DTI data are registered to a study-specific, high-resolution T1 template and the skeletonization step is omitted. In a head to head comparison, we show that with our novel approach breast cancer survivors who had received chemotherapy plus or minus endocrine therapy (BC + SYST, n = 26) showed a global decline in overall FA that was not present in breast cancer survivors who did not receive systemic therapy (BC-SYST, n = 23) or women without a cancer diagnosis (no cancer controls, NC, n = 30). With the standard TBSS approach we did not find any group differences. Moreover, voxel-based analysis for our novel pipeline showed a widespread decline in FA in the BC + SYST compared to the NC group. Interestingly, the BC-SYST group also showed a decline in FA compared to the NC group, although in much less voxels. These results were not found with the standard TBSS approach. We demonstrate that a modified processing pipeline makes DTI data more sensitive to detecting changes in white matter integrity in non-CNS cancer patients after treatment, particularly chemotherapy.

DTI Atlases Evaluations

The cerebral atlas of diffusion tensor magnetic resonance image (DT-MRI, shorted as DTI) is one of the key issues in neuroimaging research. It is crucial for comparisons of neuronal structural integrity and connectivity across populations. Usually, the atlas is constructed by iteratively averaging the registered individual image. In tradition, the fuzzy group average image is easily generated in the initial stage, which is harmful to providing clear guidance for subsequent registration, to the performance of the final atlas. To solve this problem, an improved unbiased DTI atlas construction algorithm based on adaptive weights is proposed in this paper. The adaptive weighted strategy based on diffeomorphic deformable tensor registration is introduced. At the same time, the distance measure for tensors is used as a constraint condition, which ensures the unbiasedness of the atlas. Then, using 77 DTIs from the dataset in http://www.brain-development.org , three study-specific atlases, i.e. the constructed atlases of the proposed algorithm and two open-sourced algorithms (DTIAtlasBuilder and DTI-TK), are compared with two standardized atlases (IIT v. 4.1 and NTU-DSI-122-DTI). The performances of the atlases were evaluated in spatial normalization way with six region-based criteria (including Euclidean distances between diffusion tensors, Euclidean distances of the deviatoric tensors, standard deviation, overlaps of eigenvalue-eigenvector, cross-correlations and three sets angles of eigenvalue-eigenvector pairs between diffusion tensors) and three fiber-based criteria (including distances between fiber bundles, angles between fiber bundles and fiber property profile-based criteria). The experimental results showed that the overall performances of the study-specific atlases are better than those of the standardized atlases for specific datasets, and the comprehensive performance of the improved algorithm proposed in this paper is the best.

Development of brain atlases for early-to-middle adolescent collision-sport athletes

Human brains develop across the life span and largely vary in morphology. Adolescent collision-sport athletes undergo repetitive head impacts over years of practices and competitions, and therefore may exhibit a neuroanatomical trajectory different from healthy adolescents in general. However, an unbiased brain atlas targeting these individuals does not exist. Although standardized brain atlases facilitate spatial normalization and voxel-wise analysis at the group level, when the underlying neuroanatomy does not represent the study population, greater biases and errors can be introduced during spatial normalization, confounding subsequent voxel-wise analysis and statistical findings. In this work, targeting early-to-middle adolescent (EMA, ages 13-19) collision-sport athletes, we developed population-specific brain atlases that include templates (T1-weighted and diffusion tensor magnetic resonance imaging) and semantic labels (cortical and white matter parcellations). Compared to standardized adult or age-appropriate templates, our templates better characterized the neuroanatomy of the EMA collision-sport athletes, reduced biases introduced during spatial normalization, and exhibited higher sensitivity in diffusion tensor imaging analysis. In summary, these results suggest the population-specific brain atlases are more appropriate towards reproducible and meaningful statistical results, which better clarify mechanisms of traumatic brain injury and monitor brain health for EMA collision-sport athletes.

Development and evaluation of a high performance T1-weighted brain template for use in studies on older adults

Τhe accuracy of template-based neuroimaging investigations depends on the template's image quality and representativeness of the individuals under study. Yet a thorough, quantitative investigation of how available standardized and study-specific T1-weighted templates perform in studies on older adults has not been conducted. The purpose of this work was to construct a high-quality standardized T1-weighted template specifically designed for the older adult brain, and systematically compare the new template to several other standardized and study-specific templates in terms of image quality, performance in spatial normalization of older adult data and detection of small inter-group morphometric differences, and representativeness of the older adult brain. The new template was constructed with state-of-the-art spatial normalization of high-quality data from 222 older adults. It was shown that the new template (a) exhibited high image sharpness, (b) provided higher inter-subject spatial normalization accuracy and (c) allowed detection of smaller inter-group morphometric differences compared to other standardized templates, (d) had similar performance to that of study-specific templates constructed with the same methodology, and (e) was highly representative of the older adult brain.

Early limbic microstructural alterations in apathy and depression in de novo Parkinson's disease

BACKGROUND

Whether structural alterations underpin apathy and depression in de novo parkinsonian patients is unknown. The objectives of this study were to investigate whether apathy and depression in de novo parkinsonian patients are related to structural alterations and how structural abnormalities relate to serotonergic or dopaminergic dysfunction.

METHODS

We compared the morphological and microstructural architecture in gray matter using voxel-based morphometry and diffusion tensor imaging coupled with white matter tract-based spatial statistics in a multimodal imaging case-control study enrolling 14 apathetic and 13 nonapathetic patients with de novo Parkinson's disease and 15 age-matched healthy controls, paired with PET imaging of the presynaptic dopaminergic and serotonergic systems.

RESULTS

De novo parkinsonian patients with apathy had bilateral microstructural alterations in the medial corticostriatal limbic system, exhibiting decreased fractional anisotropy and increased mean diffusivity in the anterior striatum and pregenual anterior cingulate cortex in conjunction with serotonergic dysfunction. Furthermore, microstructural alterations extended to the medial frontal cortex, the subgenual anterior cingulate cortex and subcallosal gyrus, the medial thalamus, and the caudal midbrain, suggesting disruption of long-range nondopaminergic projections originating in the brainstem, in addition to microstructural alterations in callosal interhemispheric connections and frontostriatal association tracts early in the disease course. In addition, microstructural abnormalities related to depressive symptoms in apathetic and nonapathetic patients revealed a distinct, mainly right-sided limbic subnetwork involving limbic and frontal association tracts.

CONCLUSIONS

Early limbic microstructural alterations specifically related to apathy and depression emphasize the role of early disruption of ascending nondopaminergic projections and related corticocortical and corticosubcortical networks which underpin the variable expression of nonmotor and neuropsychiatric symptoms in Parkinson's disease. © 2019 International Parkinson and Movement Disorder Society.

Diffusion Tensor Imaging Biomarkers to Predict Motor Outcomes in Stroke: A Narrative Review

Stroke is a leading cause of disability worldwide. Motor impairments occur in most of the patients with stroke in the acute phase and contribute substantially to disability. Diffusion tensor imaging (DTI) biomarkers such as fractional anisotropy (FA) measured at an early phase after stroke have emerged as potential predictors of motor recovery. In this narrative review, we: (1) review key concepts of diffusion MRI (dMRI); (2) present an overview of state-of-art methodological aspects of data collection, analysis and reporting; and (3) critically review challenges of DTI in stroke as well as results of studies that investigated the correlation between DTI metrics within the corticospinal tract and motor outcomes at different stages after stroke. We reviewed studies published between January, 2008 and December, 2018, that reported correlations between DTI metrics collected within the first 24 h (hyperacute), 2-7 days (acute), and >7-90 days (early subacute) after stroke. Nineteen studies were included. Our review shows that there is no consensus about gold standards for DTI data collection or processing. We found great methodological differences across studies that evaluated DTI metrics within the corticospinal tract. Despite heterogeneity in stroke lesions and analysis approaches, the majority of studies reported significant correlations between DTI biomarkers and motor impairments. It remains to be determined whether DTI results could enhance the predictive value of motor disability models based on clinical and neurophysiological variables.

A framework for multi-component analysis of diffusion MRI data over the neonatal period

We describe a framework for creating a time-resolved group average template of the developing brain using advanced multi-shell high angular resolution diffusion imaging data, for use in group voxel or fixel-wise analysis, atlas-building, and related applications. This relies on the recently proposed multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) technique. We decompose the signal into one isotropic component and two anisotropic components, with response functions estimated from cerebrospinal fluid and white matter in the youngest and oldest participant groups, respectively. We build an orientationally-resolved template of those tissue components from data acquired from 113 babies between 33 and 44 weeks postmenstrual age, imaged as part of the Developing Human Connectome Project. These data were split into weekly groups, and registered to the corresponding group average templates using a previously-proposed non-linear diffeomorphic registration framework, designed to align orientation density functions (ODF). This framework was extended to allow the use of the multiple contrasts provided by the multi-tissue decomposition, and shown to provide superior alignment. Finally, the weekly templates were registered to the same common template to facilitate investigations into the evolution of the different components as a function of age. The resulting multi-tissue atlas provides insights into brain development and accompanying changes in microstructure, and forms the basis for future longitudinal investigations into healthy and pathological white matter maturation.

Preliminary mapping of the structural effects of age in pediatric bipolar disorder with multimodal MR imaging

This study investigates multimodal structural MR imaging biomarkers of development trajectories in pediatric bipolar disorder. T1-weighted and diffusion-weighted MR imaging was conducted to investigate cross-sectional group differences with age between typically developing controls (N = 26) and youths diagnosed with bipolar disorder (N = 26). Region-based analysis was used to examine cortical thickness of gray matter and diffusion tensor parameters in superficial white matter, and tractography-based analysis was used to examine deep white matter fiber bundles. Patients and controls showed significantly different maturation trajectories across brain areas; however, the magnitude of differences varied by region. The rate of cortical thinning with age was greater in patients than controls in the left frontal pole. While controls showed increasing fractional anisotropy (FA) and axial diffusivity (AD) with age, patients showed an opposite trend of decreasing FA and AD with age in fronto-temporal-striatal regions located in both superficial and deep white matter. The findings support fronto-temporal-striatal alterations in the developmental trajectories of youths diagnosed with bipolar disorder, and further, show the value of multimodal computational techniques in the assessment of neuropsychiatric disorders. These preliminary results warrant further investigation into longitudinal changes and the effects of treatment in the brain areas identified in this study.

Evaluation of standardized and study-specific diffusion tensor imaging templates of the adult human brain: Template characteristics, spatial normalization accuracy, and detection of small inter-group FA differences

Digital diffusion tensor imaging (DTI) templates of the adult human brain are commonly used in neuroimaging research, and their characteristics influence the accuracy of the application. However, a systematic evaluation of the characteristics and performance of standardized and study-specific DTI templates has not been conducted. The purpose of this work was to compare eight available standardized DTI templates to each other (ICBM81, ENIGMA, FMRIB58, SRI24, IIT2, NTU-DSI-122-DTI, IIT v.3.0, Eve), as well as to study-specific templates, in terms of template characteristics (image sharpness, ability to identify small brain structures, artifacts, mean values, noise properties) and performance in spatial normalization and detection of small inter-group FA differences. The IIT v.3.0 template was shown to combine a number of desirable characteristics: includes full-tensor information, is population-based, has high image sharpness, shows no visible artifacts, has low noise levels, has diffusion tensor properties and spatial features representative of data from the average individual adult brain. Furthermore, the IIT v.3.0 template was shown to allow higher inter-subject DTI spatial normalization accuracy, and detection of smaller inter-group FA differences, compared to all other templates, including study-specific templates. These findings were consistent when evaluating the templates in younger as well as older adult cohorts.

A tract-specific approach to assessing white matter in preterm infants

Diffusion-weighted imaging (DWI) is becoming an increasingly important tool for studying brain development. DWI analyses relying on manually-drawn regions of interest and tractography using manually-placed waypoints are considered to provide the most accurate characterisation of the underlying brain structure. However, these methods are labour-intensive and become impractical for studies with large cohorts and numerous white matter (WM) tracts. Tract-specific analysis (TSA) is an alternative WM analysis method applicable to large-scale studies that offers potential benefits. TSA produces a skeleton representation of WM tracts and projects the group's diffusion data onto the skeleton for statistical analysis. In this work we evaluate the performance of TSA in analysing preterm infant data against results obtained from native space tractography and tract-based spatial statistics. We evaluate TSA's registration accuracy of WM tracts and assess the agreement between native space data and template space data projected onto WM skeletons, in 12 tracts across 48 preterm neonates. We show that TSA registration provides better WM tract alignment than a previous protocol optimised for neonatal spatial normalisation, and that TSA projects FA values that match well with values derived from native space tractography. We apply TSA for the first time to a preterm neonatal population to study the effects of age at scan on WM tracts around term equivalent age. We demonstrate the effects of age at scan on DTI metrics in commissural, projection and association fibres. We demonstrate the potential of TSA for WM analysis and its suitability for infant studies involving multiple tracts.

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Evaluation of tract-specific analysis (TSA) for white matter studies in infants.

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TSA improves white matter tract alignment over scalar-based registration.

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TSA closely approximates native space tractography DTI values.

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The first application of TSA to a neonatal population.

A Comparative evaluation of voxel-based spatial mapping in diffusion tensor imaging

This paper presents a comparative evaluation of methods for automated voxel-based spatial mapping in diffusion tensor imaging studies. Such methods are an essential step in computational pipelines and provide anatomically comparable measurements across a population in atlas-based studies. To better understand their strengths and weaknesses, we tested a total of eight methods for voxel-based spatial mapping in two types of diffusion tensor templates. The methods were evaluated with respect to scan-rescan reliability and an application to normal aging. The methods included voxel-based analysis with and without smoothing, two types of region-based analysis, and combinations thereof with skeletonization. The templates included a study-specific template created with DTI-TK and the IIT template serving as a standard template. To control for other factors in the pipeline, the experiments used a common dataset, acquired at 1.5T with a single shell high angular resolution diffusion MR imaging protocol, and tensor-based spatial normalization with DTI-TK. Scan-rescan reliability was assessed using the coefficient of variation (CV) and intraclass correlation (ICC) in eight subjects with three scans each. Sensitivity to normal aging was assessed in a population of 80 subjects aged 25-65 years old, and methods were compared with respect to the anatomical agreement of significant findings and the R2 of the associated models of fractional anisotropy. The results show that reliability depended greatly on the method used for spatial mapping. The largest differences in reliability were found when adding smoothing and comparing voxel-based and region-based analyses. Skeletonization and template type were found to have either a small or negligible effect on reliability. The aging results showed agreement among the methods in nine brain areas, with some methods showing more sensitivity than others. Skeletonization and smoothing were not major factors affecting sensitivity to aging, but the standard template showed higher R2 in several conditions. A structural comparison of the templates showed that large deformations between them may be related to observed differences in patterns of significant voxels. Most areas showed significantly higher R2 with voxel-based analysis, particularly when clusters were smaller than the available regions-of-interest. Looking forward, these results can potentially help to interpret results from existing white matter imaging studies, as well as provide a resource to help in planning future studies to maximize reliability and sensitivity with regard to the scientific goals at hand.

Investigating white matter fibre density and morphology using fixel-based analysis

Voxel-based analysis of diffusion MRI data is increasingly popular. However, most white matter voxels contain contributions from multiple fibre populations (often referred to as crossing fibres), and therefore voxel-averaged quantitative measures (e.g. fractional anisotropy) are not fibre-specific and have poor interpretability. Using higher-order diffusion models, parameters related to fibre density can be extracted for individual fibre populations within each voxel ('fixels'), and recent advances in statistics enable the multi-subject analysis of such data. However, investigating within-voxel microscopic fibre density alone does not account for macroscopic differences in the white matter morphology (e.g. the calibre of a fibre bundle). In this work, we introduce a novel method to investigate the latter, which we call fixel-based morphometry (FBM). To obtain a more complete measure related to the total number of white matter axons, information from both within-voxel microscopic fibre density and macroscopic morphology must be combined. We therefore present the FBM method as an integral piece within a comprehensive fixel-based analysis framework to investigate measures of fibre density, fibre-bundle morphology (cross-section), and a combined measure of fibre density and cross-section. We performed simulations to demonstrate the proposed measures using various transformations of a numerical fibre bundle phantom. Finally, we provide an example of such an analysis by comparing a clinical patient group to a healthy control group, which demonstrates that all three measures provide distinct and complementary information. By capturing information from both sources, the combined fibre density and cross-section measure is likely to be more sensitive to certain pathologies and more directly interpretable.

Diffusion Kurtosis Imaging: A Possible MRI Biomarker for AD Diagnosis?

The purpose of this explorative study was to investigate whether diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) parameter changes are reliable measures of white matter integrity changes in Alzheimer's disease (AD) patients using a whole brain voxel-based analysis (VBA). Therefore, age- and gender-matched patients with mild cognitive impairment (MCI) due to AD (n = 18), dementia due to AD (n = 19), and age-matched cognitively healthy controls (n = 14) were prospectively included. The magnetic resonance imaging protocol included routine structural brain imaging and DKI. Datasets were transformed to a population-specific atlas space. Groups were compared using VBA. Differences in diffusion and mean kurtosis measures between MCI and AD patients and controls were shown, and were mainly found in the splenium of the corpus callosum and the corona radiata. Hence, DTI and DKI parameter changes are suggestive of white matter changes in AD.

NTU-DSI-122: A diffusion spectrum imaging template with high anatomical matching to the ICBM-152 space

A diffusion-weighted (DW) template in a standard coordinate system is often necessary for the analysis of white matter (WM) structures using DW images. Although several DW templates have been constructed in the ICBM-152 space, a template for diffusion spectrum imaging (DSI) is still lacking. In this study, we developed a DSI template in the ICBM-152 space from 122 healthy adults. This high quality template, NTU-DSI-122, was built through incorporating the macroscopic anatomical information using high-resolution T1 -weighted images and the microscopic structural information obtained from DSI datasets. Two evaluations were conducted to examine the quality of NTU-DSI-122. The first evaluation examined the anatomical consistency of NTU-DSI-122 in matching to the ICBM-152 coordinate system. The results showed that this template matched to the ICBM-152 templates very well across the whole brain, not only in the deep white matter regions as other DW templates but also in the superficial white matter regions. In the second evaluation, a large number of independent diffusion tensor imaging (DTI) datasets were registered to the DTI template derived from NTU-DSI-122. The examination was performed by quantifying the anatomical consistency among the registered DTI datasets. The results showed that using NTU-DSI-122 as the registration template the registered DTI datasets can achieve high anatomical alignment. Both evaluations demonstrate that NTU-DSI-122 is a useful high quality DW template. Therefore, NTU-DSI-122 can serve as a representative DSI dataset for a healthy adult population, and will be of potential value for brain research and clinical applications. The NTU-DSI-122 template is available at http://www.nitrc.org/projects/ntu-dsi-122/.

Connectivity-based fixel enhancement: Whole-brain statistical analysis of diffusion MRI measures in the presence of crossing fibres

In brain regions containing crossing fibre bundles, voxel-average diffusion MRI measures such as fractional anisotropy (FA) are difficult to interpret, and lack within-voxel single fibre population specificity. Recent work has focused on the development of more interpretable quantitative measures that can be associated with a specific fibre population within a voxel containing crossing fibres (herein we use fixel to refer to a specific fibre population within a single voxel). Unfortunately, traditional 3D methods for smoothing and cluster-based statistical inference cannot be used for voxel-based analysis of these measures, since the local neighbourhood for smoothing and cluster formation can be ambiguous when adjacent voxels may have different numbers of fixels, or ill-defined when they belong to different tracts. Here we introduce a novel statistical method to perform whole-brain fixel-based analysis called connectivity-based fixel enhancement (CFE). CFE uses probabilistic tractography to identify structurally connected fixels that are likely to share underlying anatomy and pathology. Probabilistic connectivity information is then used for tract-specific smoothing (prior to the statistical analysis) and enhancement of the statistical map (using a threshold-free cluster enhancement-like approach). To investigate the characteristics of the CFE method, we assessed sensitivity and specificity using a large number of combinations of CFE enhancement parameters and smoothing extents, using simulated pathology generated with a range of test-statistic signal-to-noise ratios in five different white matter regions (chosen to cover a broad range of fibre bundle features). The results suggest that CFE input parameters are relatively insensitive to the characteristics of the simulated pathology. We therefore recommend a single set of CFE parameters that should give near optimal results in future studies where the group effect is unknown. We then demonstrate the proposed method by comparing apparent fibre density between motor neurone disease (MND) patients with control subjects. The MND results illustrate the benefit of fixel-specific statistical inference in white matter regions that contain crossing fibres.

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We introduce the fixel—a specific fibre population within a voxel.

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A novel method for whole-brain fixel-based analysis of diffusion MRI is presented.

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Structural connectivity between fixels is derived from template-based tractography.

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Connectivity information is used for tract-specific smoothing and enhancement.

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Quantitative assessment and an in vivo demonstration is performed.

The papez circuit in first-episode, treatment-naive adults with major depressive disorder: combined atlas-based tract-specific quantification analysis and voxel-based analysis

Previous findings suggest that the Papez Circuit may have a role in major depressive disorders. We used atlas-based tract-specific quantification analysis and voxel-based analysis to examine the integrity of white matter tracts involved in mood regulation (including tracts in the Papez Circuit). Diffusion tensor imaging acquired from 35 first-episode, treatment-naive adults with major depressive disorders and 34 healthy adult controls were compared. Our statistical approach compared structural integrity of 11 major white matter tracts between the major depressive disorder and adult controls, as well as illness duration influence in patients. Fractional anisotropy was decreased in the hippocampal cingulum and in the anterior thalamic radiation according to both analytical approaches, all of which were important tracts included in the Papez Circuit. Our results support the role of the Papez Circuit in major depressive disorders with the minimal probability of false positive due to similar findings in both analyses that have complementary advantages. Dysfunction of the Papez Circuit may be a potential marker for studying the pathogenesis of major depressive disorders.

Statistical Instability of TBSS Analysis Based on DTI Fitting Algorithm

Voxel-based DTI analysis is an important approach in the comparison of subject groups by detecting and localizing gray and white matter changes in the brain. One of the principal problems for intersubject comparison is the absence of a "gold standard" processing pipeline. As a result, contradictory results may be obtained from identical data using different data processing pipelines, for example, in the data normalization or smoothing procedures. Tract-based spatial statistics (TBSS) shows potential to overcome this problem by automatic detection of white matter changes and decreasing variation in the performed analysis. However, skeleton projection approaches, such as TBSS, critically depend on the accuracy of the diffusion scalar metric estimations. In this work, we demonstrate that the agreement and reliability of TBSS results depend on the applied DTI data processing algorithm. Statistical tests have been performed using two in vivo measured datasets and compared with different implementations of the least squares algorithm. As a result, we recommend repeating TBSS analysis using different fitting algorithms, in particular, using on iteratively-assessed robust estimators, as accurate and more reliable approach in voxel-based analysis, particularly, for TBSS. Repeating TBSS analysis allows one to detect and localize suspicious regions in white matter which were estimated as the regions with significant difference. Finally, we did not find a favorite fitting algorithm (or class of them) which can be marked as more reliable for group comparison.

Constrained spherical deconvolution-based tractography and tract-based spatial statistics show abnormal microstructural organization in Asperger syndrome

BACKGROUND

The aim of this study was to investigate potential differences in neural structure in individuals with Asperger syndrome (AS), high-functioning individuals with autism spectrum disorder (ASD). The main symptoms of AS are severe impairments in social interactions and restricted or repetitive patterns of behaviors, interests or activities.

METHODS

Diffusion weighted magnetic resonance imaging data were acquired for 14 adult males with AS and 19 age, sex and IQ-matched controls. Voxelwise group differences in fractional anisotropy (FA) were studied with tract-based spatial statistics (TBSS). Based on the results of TBSS, a tract-level comparison was performed with constrained spherical deconvolution (CSD)-based tractography, which is able to detect complex (for example, crossing) fiber configurations. In addition, to investigate the relationship between the microstructural changes and the severity of symptoms, we looked for correlations between FA and the Autism Spectrum Quotient (AQ), Empathy Quotient and Systemizing Quotient.

RESULTS

TBSS revealed widely distributed local increases in FA bilaterally in individuals with AS, most prominent in the temporal part of the superior longitudinal fasciculus, corticospinal tract, splenium of corpus callosum, anterior thalamic radiation, inferior fronto-occipital fasciculus (IFO), posterior thalamic radiation, uncinate fasciculus and inferior longitudinal fasciculus (ILF). CSD-based tractography also showed increases in the FA in multiple tracts. However, only the difference in the left ILF was significant after a Bonferroni correction. These results were not explained by the complexity of microstructural organization, measured using the planar diffusion coefficient. In addition, we found a correlation between AQ and FA in the right IFO in the whole group.

CONCLUSIONS

Our results suggest that there are local and tract-level abnormalities in white matter (WM) microstructure in our homogenous and carefully characterized group of adults with AS, most prominent in the left ILF.

Methodological considerations on tract-based spatial statistics (TBSS)

Having gained a tremendous amount of popularity since its introduction in 2006, tract-based spatial statistics (TBSS) can now be considered as the standard approach for voxel-based analysis (VBA) of diffusion tensor imaging (DTI) data. Aiming to improve the sensitivity, objectivity, and interpretability of multi-subject DTI studies, TBSS includes a skeletonization step that alleviates residual image misalignment and obviates the need for data smoothing. Although TBSS represents an elegant and user-friendly framework that tackles numerous concerns existing in conventional VBA methods, it has limitations of its own, some of which have already been detailed in recent literature. In this work, we present general methodological considerations on TBSS and report on pitfalls that have not been described previously. In particular, we have identified specific assumptions of TBSS that may not be satisfied under typical conditions. Moreover, we demonstrate that the existence of such violations can severely affect the reliability of TBSS results. With TBSS being used increasingly, it is of paramount importance to acquaint TBSS users with these concerns, such that a well-informed decision can be made as to whether and how to pursue a TBSS analysis. Finally, in addition to raising awareness by providing our new insights, we provide constructive suggestions that could improve the validity and increase the impact of TBSS drastically.

Diffusion tensor MRI of chemotherapy-induced cognitive impairment in non-CNS cancer patients: a review

Patients with non-central nervous system cancers often experience subtle cognitive deficits after treatment with cytotoxic agents. Therapy-induced structural changes to the brain could be one of the possible causes underlying these reported cognitive deficits. In this review, we evaluate the use of diffusion tensor imaging (DTI) for assessing possible therapy-induced changes in the microstructure of the cerebral white matter (WM) and provide a critical overview of the published DTI research on therapy-induced cognitive impairment. Both cross-sectional and longitudinal DTI studies have demonstrated abnormal microstructural properties in WM regions involved in cognition. These findings correlated with cognitive performance, suggesting that there is a link between reduced "WM integrity" and chemotherapy-induced impaired cognition. In this paper, we will also introduce the basics of diffusion tensor imaging and how it can be applied to evaluate effects of therapy on structural changes in cerebral WM. The review concludes with considerations and discussion regarding DTI data interpretation and possible future directions for investigating therapy-induced WM changes in cancer patients. This review article is part of a Special Issue entitled: Neuroimaging Studies of Cancer and Cancer Treatment.

White matter microstructural abnormalities in families multiply affected with bipolar I disorder: a diffusion tensor tractography study

BACKGROUND

White matter (WM) abnormalities are proposed as potential endophenotypic markers of bipolar disorder (BD). In a diffusion tensor imaging (DTI) voxel-based analysis (VBA) study of families multiply affected with BD, we previously reported that widespread abnormalities of fractional anisotropy (FA) are associated with both BD and genetic liability for illness. In the present study, we further investigated the endophenotypic potential of WM abnormalities by applying DTI tractography to specifically investigate tracts implicated in the pathophysiology of BD.

METHOD

Diffusion magnetic resonance imaging (MRI) data were acquired from 19 patients with BD type I from multiply affected families, 21 of their unaffected first-degree relatives and 18 healthy volunteers. DTI tractography was used to identify the cingulum, uncinate fasciculus (UF), arcuate portion of the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), corpus callosum, and the anterior limb of the internal capsule (ALIC). Regression analyses were conducted to investigate the effect of participant group and genetic liability on FA and radial diffusivity (RD) in each tract.

RESULTS

We detected a significant effect of group on both FA and RD in the cingulum, SLF, callosal splenium and ILF driven by reduced FA and increased RD in patients compared to controls and relatives. Increasing genetic liability was associated with decreased FA and increased RD in the UF, and decreased FA in the SLF, among patients.

CONCLUSIONS

WM microstructural abnormalities in limbic, temporal and callosal pathways represent microstructural abnormalities associated with BD whereas alterations in the SLF and UF may represent potential markers of endophenotypic risk.

Increased coherence of white matter fiber tract organization in adults with Asperger syndrome: a diffusion tensor imaging study

To investigate whether there are global white matter (WM) differences between autistic and healthy adults, we performed diffusion tensor imaging (DTI) in 14 male adults with Asperger syndrome (AS) and 19 gender-, age-, and intelligence quotient-matched controls. We focused on individuals with high-functioning autism spectrum disorder (ASD), AS, to decrease heterogeneity caused by large variation in the cognitive profile. Previous DTI studies of ASD have mainly focused on finding local changes in fractional anisotropy (FA) and mean diffusivity (MD), two indexes used to characterize microstructural properties of WM. Although the local or voxel-based approaches may be able to provide detailed information in terms of location of the observed differences, such results are known to be highly sensitive to partial volume effects, registration errors, or placement of the regions of interest. Therefore, we performed global histogram analyses of (a) whole-brain tractography results and (b) skeletonized WM masks. In addition to the FA and MD, the planar diffusion coefficient (CP) was computed as it can provide more specific information of the complexity of the neural structure. Our main finding indicated that adults with AS had higher mean FA values than controls. A less complex neural structure in adults with AS could have explained the results, but no significant difference in CP was found. Our results suggest that there are global abnormalities in the WM tissue of adults with AS.

Anatomical MRI templates of tree shrew brain for volumetric analysis and voxel-based morphometry

BACKGROUND

Tree shrews are close relatives of primates, and are increasingly used as models in the research of vision, social stress and neurological/psychiatric diseases. However, neuroimaging techniques, for example magnetic resonance (MR) imaging, are only rarely applied to this species to study the structure and function of the brain. A template MR image set, which is essential for morphometry/volumetric analysis, of tree shrew brain has been lacking in the literature.

NEW METHOD

High-resolution anatomical MR images and diffusion tensor images of the brain were acquired from male Chinese tree shrews (Tupaia belangeri chinensis), and resampled to an isotropic resolution of 200 μm × 200 μm × 200 μm. Population-based image templates of tree shrew brain, including gray matter/white matter/cerebrospinal fluid probability maps and a fractional anisotropy template, were constructed at this spatial resolution, all in a reference space. Digital masks of representative anatomical structures, including hippocampus, amygdala and cingulum bundle, were created.

RESULT

With the templates constructed, the volumes of bilateral hippocampus and amygdala were measured using a template-facilitated semi-automated approach to be 59.8 ± 8.3 and 64.3 ± 3.4 mm(3), respectively.

COMPARISON WITH EXISTING METHOD(S)

For the first time, high-resolution MR image templates of tree shrew brain were reported. The average volume of bilateral hippocampus measured with the template-facilitated semi-automated approach was found to be similar to the result obtained by the much more labor-intensive manual approach.

CONCLUSIONS

The MR image templates obtained in this study are useful for analyzing neuroimage data of tree shrew brain. The templates are freely available to the scientific community upon request.

Accelerated aging, decreased white matter integrity, and associated neuropsychological dysfunction 25 years after pediatric lymphoid malignancies

PURPOSE

CNS-directed chemotherapy (CT) and cranial radiotherapy (CRT) for childhood acute lymphoblastic leukemia or lymphoma have various neurotoxic properties. This study aimed to assess their impact on the maturing brain 20 to 30 years after diagnosis, providing a much stronger perspective on long-term quality of life than previous studies.

PATIENTS AND METHODS

Ninety-three patients treated between 1978 and 1990 at various intensities, with and without CRT, and 49 healthy controls were assessed with magnetic resonance diffusion tensor imaging (DTI) and neuropsychological tests. Differences in fractional anisotropy (FA)-a DTI measure describing white matter (WM) microstructure-were analyzed by using whole brain voxel-based analysis.

RESULTS

CRT-treated survivors demonstrated significantly decreased FA compared with controls in frontal, parietal, and temporal WM tracts. Trends for lower FA were seen in the CT-treated survivors. Decreases in FA correlated well with neuropsychological dysfunction. In contrast to the CT group and controls, the CRT group showed a steep decline of FA with age at assessment. Younger age at cranial irradiation and higher dosage were associated with worse outcome of WM integrity.

CONCLUSION

CRT-treated survivors show decreased WM integrity reflected by significantly decreased FA and associated neuropsychological dysfunction 25 years after treatment, although effects of CT alone seem mild. Accelerated aging of the brain and increased risk of early onset dementia are suspected after CRT, but not after CT.

White matter differences in euthymic bipolar I disorder: a combined magnetic resonance imaging and diffusion tensor imaging voxel-based study

OBJECTIVES

A broad range of subtle and markedly heterogenous neuroanatomical abnormalities of grey matter and white matter have been reported in bipolar disorder. Euthymic bipolar disorder patients represent a clinically homogenous group in which to identify trait-based biomarkers of bipolar disorder. In this study, we sought to clarify the nature and extent of neuroanatomical differences in a large, clinically homogeneous group of euthymic bipolar disorder patients.

METHODS

Structural magnetic resonance imaging (sMRI) was obtained for 60 patients with prospectively confirmed euthymic bipolar I disorder and 60 individually age- and gender-matched healthy volunteers. High angular resolution diffusion tensor imaging (DTI) scans were obtained for a subset of this sample comprising 35 patients and 43 controls. Voxel-based analysis of both sMRI and DTI data sets was performed.

RESULTS

Bipolar disorder patients displayed global reductions in white matter volume and fractional anisotropy reductions in the corpus callosum, posterior cingulum, and prefrontal white matter compared with controls. There were corresponding increases in radial diffusivity in the callosal splenium in patients compared with controls. No significant group differences were detected in grey matter. In patients, lithium was associated with a bilateral increase in grey matter volume in the temporal lobes, but not with any DTI parameter.

CONCLUSIONS

Euthymic bipolar I disorder is characterized by both diffuse global white matter deficits and potential regional disorganization in interhemispheric and longitudinal tracts, while grey matter appears to be preserved.

White matter structural connectivity is associated with sensorimotor function in stroke survivors

Purpose

Diffusion tensor imaging (DTI) provides functionally relevant information about white matter structure. Local anatomical connectivity information combined with fractional anisotropy (FA) and mean diffusivity (MD) may predict functional outcomes in stroke survivors. Imaging methods for predicting functional outcomes in stroke survivors are not well established. This work uses DTI to objectively assess the effects of a stroke lesion on white matter structure and sensorimotor function.

Methods

A voxel-based approach is introduced to assess a stroke lesion's global impact on motor function. Anatomical T1-weighted and diffusion tensor images of the brain were acquired for nineteen subjects (10 post-stroke and 9 age-matched controls). A manually selected volume of interest was used to alleviate the effects of stroke lesions on image registration. Images from all subjects were registered to the images of the control subject that was anatomically closest to Talairach space. Each subject's transformed image was uniformly seeded for DTI tractography. Each seed was inversely transformed into the individual subject space, where DTI tractography was conducted and then the results were transformed back to the reference space. A voxel-wise connectivity matrix was constructed from the fibers, which was then used to calculate the number of directly and indirectly connected neighbors of each voxel. A novel voxel-wise indirect structural connectivity (VISC) index was computed as the average number of direct connections to a voxel's indirect neighbors. Voxel-based analyses (VBA) were performed to compare VISC, FA, and MD for the detection of lesion-induced changes in sensorimotor function. For each voxel, a t-value was computed from the differences between each stroke brain and the 9 controls. A series of linear regressions was performed between Fugl-Meyer (FM) assessment scores of sensorimotor impairment and each DTI metric's log number of voxels that differed from the control group.

Results

Correlation between the logarithm of the number of significant voxels in the ipsilesional hemisphere and total Fugl-Meyer score was moderate for MD (R2 = 0.512), and greater for VISC (R2 = 0.796) and FA (R2 = 0.674). The slopes of FA (p = 0.0036), VISC (p = 0.0005), and MD (p = 0.0199) versus the total FM score were significant. However, these correlations were driven by the upper extremity motor component of the FM score (VISC: R2 = 0.879) with little influence of the lower extremity motor component (FA: R2 = 0.177).

Conclusion

The results suggest that a voxel-wise metric based on DTI tractography can predict upper extremity sensorimotor function of stroke survivors, and that supraspinal intraconnectivity may have a less dominant role in lower extremity function.

•

An intrinsic voxel-based structural connectivity metric is proposed.

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The metric enhances the impact of stroke lesions on the distant voxels.

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Whole-brain extralesional anatomical connectivity predicts functional outcome.

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Functional impact of a lesion is determined by residual anatomical connectivity.

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Connectivity to the posterior parietal cortex is a key to sensorimotor function.

Acquisition guidelines and quality assessment tools for analyzing neonatal diffusion tensor MRI data

Diffusion tensor imaging is a valuable measure in clinical settings to assess diagnosis and prognosis of neonatal brain development. However, obtaining reliable images is not straightforward because of the tissue characteristics of the neonatal brain and the high likelihood of motion artifacts. In this review, we present guidelines on how to acquire DTI data of the neonatal brain and recommend high-quality data acquisition and processing as an essential means to obtain accurate and robust parametric maps. Sudden head movements are problematic for DTI in neonates, and these may lead to incorrect values. We describe strategies to minimize the corrupting effects both in terms of acquisition (eg, more gradient directions) and postprocessing (eg, tensor estimation methods). In addition, tools are described that can help assess whether a dataset is of sufficient quality for further assessment.

Limbic and callosal white matter changes in euthymic bipolar I disorder: an advanced diffusion magnetic resonance imaging tractography study

BACKGROUND

White matter microstructural changes detected using diffusion tensor imaging have been reported in bipolar disorder. However, findings are heterogeneous, which may be related to the use of analysis techniques that cannot adequately model crossing fibers in the brain. We therefore sought to identify altered diffusion anisotropy and diffusivity changes using an improved high angular resolution fiber-tracking technique.

METHODS

Diffusion magnetic resonance imaging data was obtained from 35 prospectively confirmed euthymic bipolar disorder type 1 patients (age 22-59) and 43 control subjects (age 22-59) drawn from a sample of 120 age- and gender-matched demographically similar case-control pairs. Tractography using a constrained spherical deconvolution approach to account for crossing fibers was implemented. Changes in fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity between patient and control groups in subdivisions of the corpus callosum, cingulum, and fornix were measured as indicators of trait differences in white matter microstructural organization in bipolar disorder.

RESULTS

Patients had significantly reduced fractional anisotropy and increased mean diffusivity and radial diffusivity in all divisions of the corpus callosum, left fornix, and subgenual cingulum compared with control subjects. Axial diffusivity was increased in the fornix bilaterally and right dorsal-anterior cingulum.

CONCLUSIONS

By using an improved fiber-tracking method in a clinically homogeneous population, we were able to localize trait diffusivity changes to specific subdivisions of limbic fiber pathways, including the fornix. Our findings extend previous reports of altered limbic system microstructural disorganization as a trait feature of bipolar disorder.

Logical circularity in voxel-based analysis: normalization strategy may induce statistical bias

Recent discussions within the neuroimaging community have highlighted the problematic presence of selection bias in experimental design. Although initially centering on the selection of voxels during the course of fMRI studies, we demonstrate how this bias can potentially corrupt voxel-based analyses. For such studies, template-based registration plays a critical role in which a representative template serves as the normalized space for group alignment. A standard approach maps each subject's image to a representative template before performing statistical comparisons between different groups. We analytically demonstrate that in these scenarios the popular sum of squared difference (SSD) intensity metric, implicitly surrogating as a quantification of anatomical alignment, instead explicitly maximizes effect size--an experimental design flaw referred to as "circularity bias." We illustrate how this selection bias varies in strength with the similarity metric used during registration under the hypothesis that while SSD-related metrics, such as Demons, will manifest similar effects, other metrics which are not formulated based on absolute intensity differences will produce less of an effect. Consequently, given the variability in voxel-based analysis outcomes with similarity metric choice, we caution researchers specifically in the use of SSD and SSD-related measures where normalization and statistical analysis involve the same image set. Instead, we advocate a more cautious approach where normalization of the individual subject images to the reference space occurs through corresponding image sets which are independent of statistical testing. Alternatively, one can use similarity terms that are less sensitive to this bias.

Role of standardized and study-specific human brain diffusion tensor templates in inter-subject spatial normalization

PURPOSE

To investigate the effect of standardized and study-specific human brain diffusion tensor templates on the accuracy of spatial normalization, without ignoring the important roles of data quality and registration algorithm effectiveness.

MATERIALS AND METHODS

Two groups of diffusion tensor imaging (DTI) datasets, with and without visible artifacts, were normalized to two standardized diffusion tensor templates (IIT2, ICBM81) as well as study-specific templates, using three registration approaches. The accuracy of inter-subject spatial normalization was compared across templates, using the most effective registration technique for each template and group of data.

RESULTS

It was demonstrated that, for DTI data with visible artifacts, the study-specific template resulted in significantly higher spatial normalization accuracy than standardized templates. However, for data without visible artifacts, the study-specific template and the standardized template of higher quality (IIT2) resulted in similar normalization accuracy.

CONCLUSION

For DTI data with visible artifacts, a carefully constructed study-specific template may achieve higher normalization accuracy than that of standardized templates. However, as DTI data quality improves, a high-quality standardized template may be more advantageous than a study-specific template, because in addition to high normalization accuracy, it provides a standard reference across studies, as well as automated localization/segmentation when accompanied by anatomical labels.

Abnormalities in the brain of streptozotocin-induced type 1 diabetic rats revealed by diffusion tensor imaging

Diabetes mellitus affects the brain. Both type 1 and type 2 diabetic patients are associated with white matter (WM) damage observable to diffusion tensor imaging (DTI). The underlying histopathological mechanisms, however, are poorly understood. The objectives of this study are 1) to determine whether streptozotocin (STZ)-induced type 1 diabetes is associated with WM damage observable to DTI; and 2) to understand the pathophysiological aspects underlying STZ-induced brain injuries. Male Sprague–Dawley rats received a single intraperitoneal injection of STZ (62 mg/kg). DTI was used to assess brain abnormalities at 4 weeks after induction, combined with histological assessments and ultrastructural analysis. Compared to controls, the STZ-induced rats showed significantly reduced fractional anisotropy (FA) in the motor/somatosensory cortex and striatum. Histologically, the cortex and striatum of the diabetic animals are characterized by demyelination and axonal degradation. In conclusion, STZ-induced diabetes is associated with striatal/cortical injuries observable to DTI. The DTI abnormalities are likely manifestations of demyelination and axonal degradation in the affected brain regions, and can potentially be used as surrogates for evaluating diabetic brain injuries.

Improved sensitivity to cerebral white matter abnormalities in Alzheimer's disease with spherical deconvolution based tractography

Diffusion tensor imaging (DTI) based fiber tractography (FT) is the most popular approach for investigating white matter tracts in vivo, despite its inability to reconstruct fiber pathways in regions with "crossing fibers." Recently, constrained spherical deconvolution (CSD) has been developed to mitigate the adverse effects of "crossing fibers" on DTI based FT. Notwithstanding the methodological benefit, the clinical relevance of CSD based FT for the assessment of white matter abnormalities remains unclear. In this work, we evaluated the applicability of a hybrid framework, in which CSD based FT is combined with conventional DTI metrics to assess white matter abnormalities in 25 patients with early Alzheimer's disease. Both CSD and DTI based FT were used to reconstruct two white matter tracts: one with regions of "crossing fibers," i.e., the superior longitudinal fasciculus (SLF) and one which contains only one fiber orientation, i.e. the midsagittal section of the corpus callosum (CC). The DTI metrics, fractional anisotropy (FA) and mean diffusivity (MD), obtained from these tracts were related to memory function. Our results show that in the tract with "crossing fibers" the relation between FA/MD and memory was stronger with CSD than with DTI based FT. By contrast, in the fiber bundle where one fiber population predominates, the relation between FA/MD and memory was comparable between both tractography methods. Importantly, these associations were most pronounced after adjustment for the planar diffusion coefficient, a measure reflecting the degree of fiber organization complexity. These findings indicate that compared to conventionally applied DTI based FT, CSD based FT combined with DTI metrics can increase the sensitivity to detect functionally significant white matter abnormalities in tracts with complex white matter architecture.

Reduced fractional anisotropy in the uncinate fasciculus in patients with major depression carrying the met-allele of the Val66Met brain-derived neurotrophic factor genotype

Experimental studies support a neurotrophic hypothesis of major depressive disorder (MDD). The aim of this study was to determine the effect of Val66Met brain-derived neurotrophic factor (BDNF) polymorphism on the white matter fiber tracts connecting hippocampus and amygdala with the prefrontal lobe in a sample of patients with MDD and healthy controls. Thirty-seven patients with MDD and 42 healthy volunteers were recruited. Diffusion tensor imaging (DTI) data with 61 diffusion directions were obtained with MRI 3 Tesla scanner. Deterministic tractography was applied with ExploreDTI and Val66Met BDNF SNP (rs6265) was genotyped. Fiber tracts connecting the hippocampus and amygdala with the prefrontal lobe, namely uncinate fasciculus (UF), fornix, and cingulum were analyzed. A significant interaction was found in the UF between BDNF alleles and diagnosis. Patients carrying the BDNF met-allele had smaller fractional anisotropy (FA) in the UF compared to those patients homozygous for val-allele and compared to healthy subjects carrying the met-allele. A significant three-way interaction was detected between region of the cingulum (dorsal, rostral, and parahippocampal regions), brain hemisphere and BDNF genotype. Larger FA was detectable in the left rostral cingulum for met-allele carriers when compared to val/val alelle carriers. We provide evidence for the importance of the neurotrophic involvement in limbic and prefrontal connections. The met-allele of the BDNF polymorphism seems to render subjects more vulnerable for dysfunctions associated with the UF, a tract known to be related to negative emotional-cognitive processing bias, declarative memory problems, and autonoetic self awareness.

Diffusion tensor imaging in attention deficit/hyperactivity disorder: a systematic review and meta-analysis

Diffusion tensor imaging (DTI) allows in vivo examination of the microstructural integrity of white matter brain tissue. A systematic review and quantitative meta-analysis using GingerALE were undertaken to compare current DTI findings in patients with ADHD and healthy controls to further unravel the neurobiological underpinnings of the disorder. Online databases were searched for DTI studies comparing white matter integrity between ADHD patients and healthy controls. Fifteen studies met inclusion criteria. Alterations in white matter integrity were found in widespread areas, most consistently so in the right anterior corona radiata, right forceps minor, bilateral internal capsule, and left cerebellum, areas previously implicated in the pathophysiology of the disorder. Current literature is critically discussed in terms of its important methodological limitations and challenges, and guidelines for future DTI research are provided. While more research is needed, DTI proves to be a promising technique, providing new prospects and challenges for future research into the pathophysiology of ADHD.

Longitudinal assessment of chemotherapy-induced structural changes in cerebral white matter and its correlation with impaired cognitive functioning

PURPOSE

To uncover the neural substrate of cognitive impairment related to adjuvant chemotherapy, we studied cerebral white matter (WM) integrity before and after chemotherapy by using magnetic resonance diffusion tensor imaging (DTI) in combination with detailed cognitive assessment.

PATIENTS AND METHODS

Thirty-four young premenopausal women with early-stage breast cancer who were exposed to chemotherapy underwent neuropsychologic testing and DTI before the start of chemotherapy (t1) and 3 to 4 months after treatment (t2). Sixteen patients not exposed to chemotherapy and 19 age-matched healthy controls underwent the same assessment at matched intervals. In all groups, we used paired t tests to study changes in neuropsychologic test scores and whole-brain voxel-based paired t tests to study changes in WM fractional anisotropy (FA; a DTI measure that reflects WM tissue organization), with depression scores and intelligence quotient as included covariates. We correlated changes of neuropsychologic test scores with the mean change of FA for regions that survived the paired t tests in patients treated with chemotherapy.

RESULTS

In contrast to controls, the chemotherapy-treated group performed significantly worse on attention tests, psychomotor speed, and memory at t2 compared with t1 (P < .05). In the chemotherapy-treated group, we found significant decreases of FA in frontal, parietal, and occipital WM tracts after treatment (familywise error P < .05), whereas for both control groups, FA values were the same between t1 and t2. Furthermore, performance changes in attention and verbal memory correlated with mean regional FA changes in chemotherapy-treated patients (P < .05).

CONCLUSION

We report evidence of longitudinal changes in cognitive functioning and cerebral WM integrity after chemotherapy as well as an association between both.