Voxel based versus region of interest analysis in diffusion tensor imaging of neurodevelopment

Development of the uncinate fasciculus: Implications for theory and developmental disorders

The uncinate fasciculus (UF) is a long-range white matter tract that connects limbic regions in the temporal lobe to the frontal lobe. The UF is one of the latest developing tracts, and continues maturing into the third decade of life. As such, individual differences in the maturational profile of the UF may serve to explain differences in behavior. Indeed, atypical macrostructure and microstructure of the UF have been reported in numerous studies of individuals with developmental and psychiatric disorders such as social deprivation and maltreatment, autism spectrum disorders, conduct disorder, risk taking, and substance abuse. The present review evaluates what we currently know about the UF's developmental trajectory and reviews the literature relating UF abnormalities to specific disorders. Additionally, we take a dimensional approach and critically examine symptoms and behavioral impairments that have been demonstrated to cluster with UF aberrations, in an effort to relate these impairments to our speculations regarding the functionality of the UF. We suggest that developmental disorders with core problems relating to memory retrieval, reward and valuation computation, and impulsive decision making may be linked to aberrations in uncinate microstructure.

Emotion regulation and trait anxiety are predicted by the microstructure of fibers between amygdala and prefrontal cortex

Diffusion tensor imaging revealed that trait anxiety predicts the microstructural properties of a prespecified fiber tract between the amygdala and the perigenual anterior cingulate cortex. Besides this particular pathway, it is likely that other pathways are also affected. We investigated white matter differences in persons featuring an anxious or a nonanxious personality, taking into account all potential pathway connections between amygdala and anxiety-related regions of the prefrontal cortex (PFC). Diffusion-weighted images, measures of trait anxiety and of reappraisal use (an effective emotion-regulation style), were collected in 48 females. With probabilistic tractography, pathways between the amygdala and the dorsolateral PFC, dorsomedial PFC, ventromedial PFC, and orbitofrontal cortex (OFC) were delineated. The resulting network showed a direct ventral connection between amygdala and PFC and a second limbic connection following the fornix and the anterior limb of the internal capsule. Reappraisal use predicted the microstructure of pathways to all calculated PFC regions in the left hemisphere, indicating stronger pathways for persons with high reappraisal use. Trait anxiety predicted the microstructure in pathways to the ventromedial PFC and OFC, indexing weaker connections in trait-anxious persons. These effects appeared in the right hemisphere, supporting lateralization and top-down inhibition theories of emotion processing. Whereas a specific microstructure is associated with an anxious personality, a different structure subserves emotion regulation. Both are part of a broad fiber tract network between amygdala and PFC.

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.

Conventional 3T brain MRI and diffusion tensor imaging in the diagnostic workup of early stage parkinsonism

Introduction

The aim of this study is to evaluate whether the diagnostic accuracy of 3 T brain MRI is improved by region of interest (ROI) measures of diffusion tensor imaging (DTI), to differentiate between neurodegenerative atypical parkinsonism (AP) and Parkinson’s disease (PD) in early stage parkinsonism.

Methods

We performed a prospective observational cohort study of 60 patients presenting with early stage parkinsonism and initial uncertain diagnosis. At baseline, patients underwent a 3 T brain MRI including DTI. After clinical follow-up (mean 28.3 months), diagnoses could be made in 49 patients (30 PD and 19 AP). Conventional brain MRI was evaluated for regions of atrophy and signal intensity changes. Tract-based spatial statistics and ROI analyses of DTI were performed to analyze group differences in mean diffusivity (MD) and fractional anisotropy (FA), and diagnostic thresholds were determined. Diagnostic accuracy of conventional brain MRI and DTI was assessed with the receiver operating characteristic (ROC).

Results

Significantly higher MD of the centrum semiovale, body corpus callosum, putamen, external capsule, midbrain, superior cerebellum, and superior cerebellar peduncles was found in AP. Significantly increased MD of the putamen was found in multiple system atrophy–parkinsonian form (MSA-P) and increased MD in the midbrain and superior cerebellar peduncles in progressive supranuclear palsy (PSP). The diagnostic accuracy of brain MRI to identify AP as a group was not improved by ROI measures of MD, though the diagnostic accuracy to identify MSA-P was slightly increased (AUC 0.82 to 0.85).

Conclusion

The diagnostic accuracy of brain MRI to identify AP as a group was not improved by the current analysis approach to DTI, though DTI measures could be of added value to identify AP subgroups.

Microstructural abnormalities in children with post-traumatic stress disorder: a diffusion tensor imaging study at 3.0T

Posttraumatic stress disorder (PTSD) is a severe anxiety disorder characterized by re-experiencing, avoidance and hyperarousal. Brain microstructure abnormalities in PTSD, especially in children, are not yet well characterized. The aim of this study was to use MR diffusion tensor imaging (DTI) to identify brain microstructure alterations in children with PTSD compared to non-PTSD controls who experienced the same time-limited trauma. We studied 27 children with PTSD and 24 age- and gender-matched traumatized controls without PTSD, who all experienced the 2008 Sichuan major earthquake. DTI data were acquired and analyzed in terms of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). Children with PTSD showed an abnormal pattern, not only of FA, but also of the diffusivity measures MD, AD and RD. Most of the abnormal brain regions belonged to two important networks: the default-mode network, including precuneus and angular gyrus, and the salience network, including insula, putamen and thalamus. This DTI study identifies microstructural abnormalities of children with PTSD after a major earthquake, our results are consistent with the suggestion that pediatric PTSD is accompanied by a connectivity disequilibrium between the salience and default-mode networks, a finding of potential pathophysiological significance.

Multimodal analysis of functional and structural disconnection in Alzheimer's disease using multiple kernel SVM

Alzheimer's disease (AD) patients exhibit alterations in the functional connectivity between spatially segregated brain regions which may be related to both local gray matter (GM) atrophy as well as a decline in the fiber integrity of the underlying white matter tracts. Machine learning algorithms are able to automatically detect the patterns of the disease in image data, and therefore, constitute a suitable basis for automated image diagnostic systems. The question of which magnetic resonance imaging (MRI) modalities are most useful in a clinical context is as yet unresolved. We examined multimodal MRI data acquired from 28 subjects with clinically probable AD and 25 healthy controls. Specifically, we used fiber tract integrity as measured by diffusion tensor imaging (DTI), GM volume derived from structural MRI, and the graph-theoretical measures 'local clustering coefficient' and 'shortest path length' derived from resting-state functional MRI (rs-fMRI) to evaluate the utility of the three imaging methods in automated multimodal image diagnostics, to assess their individual performance, and the level of concordance between them. We ran the support vector machine (SVM) algorithm and validated the results using leave-one-out cross-validation. For the single imaging modalities, we obtained an area under the curve (AUC) of 80% for rs-fMRI, 87% for DTI, and 86% for GM volume. When it came to the multimodal SVM, we obtained an AUC of 82% using all three modalities, and 89% using only DTI measures and GM volume. Combined multimodal imaging data did not significantly improve classification accuracy compared to the best single measures alone.

Association between the common functional FKBP5 variant (rs1360780) and brain structure in a non-clinical population

FK506 binding protein 5 (FKBP5) is induced by stress and regulates glucocorticoid receptor sensitivity. The T allele of the single nucleotide polymorphism (SNP) FKBP5 rs1360780 (C/T) is associated with an increased risk of post-traumatic stress disorder (PTSD) and reduced hippocampal volume in traumatized or depressed subjects. To examine whether this SNP affects brain structures that regulate stress response, we obtained magnetic resonance imaging data of the brain in 162 healthy subjects using a 1.5 T system. Gray matter volumes and diffusion tensor imaging data were compared between individuals with and without the T allele, using optimized voxel-based morphometry. We found that the dorsal anterior cingulate cortex (dACC) volume was smaller in T carriers than in non-T carriers (P < 0.001). T carriers also showed significantly higher mean diffusivity values in the dACC and posterior cingulate cortex (PCC) compared with non-T carriers (P < 0.001). Our results suggest that carrying the T allele of FKBP5 rs1360780 is associated with smaller gray matter volumes in the dACC and altered white matter integrity in the dACC and PCC in the non-clinical population, which might constitute the structural basis of stress-related psychiatric disorders including PTSD.

Hypothalamic-pituitary-adrenal axis hyperactivity and brain differences in healthy women

BACKGROUND

Previous studies have suggested that dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis leads to brain changes. However, few studies have examined the whole brain configuration for an association with HPA axis activity. We examined the relationship between HPA axis activity and the whole brain configuration.

METHODS

The subjects in this study were 34 healthy female volunteers. HPA axis activity was assessed by the dexamethasone/corticotropin-releasing hormone test. Structural volumes of the brain and diffusion tensor images were obtained, and correlations were evaluated voxel-wise.

RESULTS

There was a significantly negative correlation between fractional anisotropy value and cortisol levels at 16:00 h (CL-2) in the anterior cingulum, left parahippocampus and right occipital region. There were significantly positive correlations between mean diffusivity value and CL-2 in the left hippocampus and bilateral parahippocampal regions.

CONCLUSIONS

Our data suggest that reduced feedback of the HPA axis is associated with reduced neural connectivity throughout the brain, and such an association may be strong in the anterior cingulate, the hippocampus and the parahippocampal regions.

Structure, integrity, and function of the hypoplastic corpus callosum in spina bifida myelomeningocele

Although there are many studies of people with complete or partial hypogenesis of the corpus callosum (CC), little is understood about the hypoplastic CC in which all structures are present but thinned. Spina bifida myelomeningocele (SBM) is a model organism for such studies because many have either a hypogenetic or hypoplastic CC. We used diffusion tensor tractography (DTT) to evaluate the hypoplastic CC in SBM and its relation to interhemispheric functions and intelligence quotient (IQ). Participants were individuals with SBM and an intact or hypoplastic CC (n=28), who were compared to a typically developing comparison group (n=32). Total and regional DTT volume and integrity measures (fractional anisotropy, axial diffusivity, and radial diffusivity) of the CC were related to measures of intelligence (IQ), bimanual motor functioning, and dichotic auditory performance. As predicted, DTT showed variations in volume and integrity that were maximized in the entire CC and the posterior CC. IQ correlated with entire CC volume, anterior and posterior regional CC volumes, and also with measures of integrity. Bimanual motor functioning correlated with the anterior and posterior volumes of the CC but not with any integrity measures. Axial diffusivity in the posterior CC was negatively correlated with right ear dichotic listening performance. The hypoplastic CC is not macrostructurally or microstructurally intact in SBM, even when it appears radiologically intact. Both volume and integrity of the posterior regions were related to reductions in IQ and to interhemispheric processing. These findings may transfer to other disorders characterized by a hypoplastic CC.

Brain imaging of mild cognitive impairment and Alzheimer's disease

The rapidly increasing prevalence of cognitive impairment and Alzheimer's disease has the potential to create a major worldwide healthcare crisis. Structural MRI studies in patients with Alzheimer's disease and mild cognitive impairment are currently attracting considerable interest. It is extremely important to study early structural and metabolic changes, such as those in the hippocampus, entorhinal cortex, and gray matter structures in the medial temporal lobe, to allow the early detection of mild cognitive impairment and Alzheimer's disease. The microstructural integrity of white matter can be studied with diffusion tensor imaging. Increased mean diffusivity and decreased fractional anisotropy are found in subjects with white matter damage. Functional imaging studies with positron emission tomography tracer compounds enable detection of amyloid plaques in the living brain in patients with Alzheimer's disease. In this review, we will focus on key findings from brain imaging studies in mild cognitive impairment and Alzheimer's disease, including structural brain changes studied with MRI and white matter changes seen with diffusion tensor imaging, and other specific imaging methodologies will also be discussed.

Automated tract extraction via atlas based Adaptive Clustering

Advancements in imaging protocols such as the high angular resolution diffusion-weighted imaging (HARDI) and in tractography techniques are expected to cause an increase in the tract-based analyses. Statistical analyses over white matter tracts can contribute greatly towards understanding structural mechanisms of the brain since tracts are representative of connectivity pathways. The main challenge with tract-based studies is the extraction of the tracts of interest in a consistent and comparable manner over a large group of individuals without drawing the inclusion and exclusion regions of interest. In this work, we design a framework for automated extraction of white matter tracts. The framework introduces three main components, namely a connectivity based fiber representation, a fiber bundle atlas, and a clustering approach called Adaptive Clustering. The fiber representation relies on the connectivity signatures of fibers to establish an easy correspondence between different subjects. A group-wise clustering of these fibers that are represented by the connectivity signatures is then used to generate a fiber bundle atlas. Finally, Adaptive Clustering incorporates the previously generated clustering atlas as a prior, to cluster the fibers of a new subject automatically. Experiments on the HARDI scans of healthy individuals acquired repeatedly, demonstrate the applicability, reliability and the repeatability of our approach in extracting white matter tracts. By alleviating the seed region selection and the inclusion/exclusion ROI drawing requirements that are usually handled by trained radiologists, the proposed framework expands the range of possible clinical applications and establishes the ability to perform tract-based analyses with large samples.

Can musical training influence brain connectivity? Evidence from diffusion tensor MRI

In recent years, musicians have been increasingly recruited to investigate grey and white matter neuroplasticity induced by skill acquisition. The development of Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) has allowed more detailed investigation of white matter connections within the brain, addressing questions about the effect of musical training on connectivity between specific brain regions. Here, current DT-MRI analysis techniques are discussed and the available evidence from DT-MRI studies into differences in white matter architecture between musicians and non-musicians is reviewed. Collectively, the existing literature tends to support the hypothesis that musical training can induce changes in cross-hemispheric connections, with significant differences frequently reported in various regions of the corpus callosum of musicians compared with non-musicians. However, differences found in intra-hemispheric fibres have not always been replicated, while findings regarding the internal capsule and corticospinal tracts appear to be contradictory. There is also recent evidence to suggest that variances in white matter structure in non-musicians may correlate with their ability to learn musical skills, offering an alternative explanation for the structural differences observed between musicians and non-musicians. Considering the inconsistencies in the current literature, possible reasons for conflicting results are offered, along with suggestions for future research in this area.

Response inhibition deficits in children with Fetal Alcohol Spectrum Disorder: relationship between diffusion tensor imaging of the corpus callosum and eye movement control

Response inhibition is the ability to suppress irrelevant impulses to enable goal-directed behavior. The underlying neural mechanisms of inhibition deficits are not clearly understood, but may be related to white matter connectivity, which can be assessed using diffusion tensor imaging (DTI). The goal of this study was to investigate the relationship between response inhibition during the performance of saccadic eye movement tasks and DTI measures of the corpus callosum in children with or without Fetal Alcohol Spectrum Disorder (FASD). Participants included 43 children with an FASD diagnosis (12.3 ± 3.1 years old) and 35 typically developing children (12.5 ± 3.0 years old) both aged 7-18, assessed at three sites across Canada. Response inhibition was measured by direction errors in an antisaccade task and timing errors in a delayed memory-guided saccade task. Manual deterministic tractography was used to delineate six regions of the corpus callosum and calculate fractional anisotropy (FA), mean diffusivity (MD), parallel diffusivity, and perpendicular diffusivity. Group differences in saccade measures were assessed using t-tests, followed by partial correlations between eye movement inhibition scores and corpus callosum FA and MD, controlling for age. Children with FASD made more saccade direction errors and more timing errors, which indicates a deficit in response inhibition. The only group difference in DTI metrics was significantly higher MD of the splenium in FASD compared to controls. Notably, direction errors in the antisaccade task were correlated negatively to FA and positively to MD of the splenium in the control, but not the FASD group, which suggests that alterations in connectivity between the two hemispheres of the brain may contribute to inhibition deficits in children with FASD.

Characterizing longitudinal white matter development during early childhood

Post-mortem studies have shown the maturation of the brain’s myelinated white matter, crucial for efficient and coordinated brain communication, follows a nonlinear spatio-temporal pattern that corresponds with the onset and refinement of cognitive functions and behaviors. Unfortunately, investigation of myelination in vivo is challenging and, thus, little is known about the normative pattern of myelination, or its association with functional development. Using a novel quantitative magnetic resonance imaging technique sensitive to myelin we examined longitudinal white matter development in 108 typically developing children ranging in age from 2.5 months to 5.5 years. Using nonlinear mixed effects modeling, we provide the first in vivo longitudinal description of myelin water fraction development. Moreover, we show distinct male and female developmental patterns, and demonstrate significant relationships between myelin content and measures of cognitive function. These findings advance a new understanding of healthy brain development and provide a foundation from which to assess atypical development.

Interactions between brain structure and behavior: the corpus callosum and bimanual coordination

Bimanual coordination skills are required for countless everyday activities, such as typing, preparing food, and driving. The corpus callosum (CC) is the major collection of white matter bundles connecting both hemispheres that enables the coordination between the two sides of the body. Principal evidence for this brain-behavior relationship in humans was first provided by research on callosotomy patients, showing that sectioning (parts of) the CC affected interactions between both hands directly. Later, new noninvasive in vivo imaging techniques, such as diffusion tensor imaging, have energized the study of the link between microstructural properties of the CC and bimanual performance in normal volunteers. Here we discuss the principal factors (such as age, pathology and training) that mediate the relationship between specific bimanual functions and distinct anatomical CC subdivisions. More specifically, the question is whether different bimanual task characteristics can be mapped onto functionally distinct CC subregions. We review the current status of this mapping endeavor, and propose future perspectives to inspire research on this unique link between brain structure and behavior.

Plausibility Tracking: a method to evaluate anatomical connectivity and microstructural properties along fiber pathways

Diffusion MRI is a non-invasive method that potentially gives insight into the brain's white matter structure regarding the pathway of connections and properties of the axons. Here, we propose a novel global tractography method named Plausibility Tracking that provides the most plausible pathway, modeled as a smooth spline curve, between two locations in the brain. Compared to other tractography methods, plausibility tracking combines the more complete connectivity pattern of probabilistic tractography with smooth tracks that are globally optimized using the fiber orientation density function and hence is relatively robust against local noise and error propagation. It has been tested on phantom and biological data and compared to other methods of tractography. Plausibility tracking provides reliable local directions all along the fiber pathways which makes it especially interesting for tract-based analysis in combination with direction dependent indices of diffusion MRI. In order to demonstrate this potential of plausibility tracking, we propose a framework for the assessment and comparison of diffusion derived tissue properties. This framework comprises atlas-guided parameterization of tract representation and advanced bundle-specific indices describing fiber density, fiber spread and white matter complexity. We explore the new method using real data and show that it allows for a more specific interpretation of the white matter's microstructure compared to rotationally invariant indices derived from the diffusion tensor.

Left hemisphere fractional anisotropy increase in noise-induced tinnitus: a diffusion tensor imaging (DTI) study of white matter tracts in the brain

Diffusion tensor imaging (DTI) is a contemporary neuroimaging modality used to study connectivity patterns and microstructure of white matter tracts in the brain. The use of DTI in the study of tinnitus is a relatively unexplored methodology with no studies focusing specifically on tinnitus induced by noise exposure. In this investigation, participants were two groups of adults matched for etiology, age, and degree of peripheral hearing loss, but differed by the presence or absence (+/-) of tinnitus. It is assumed that matching individuals on the basis of peripheral hearing loss, allows for differentiating changes in white matter microstructure due to hearing loss from changes due to the effects of chronic tinnitus. Alterations in white matter tracts, using the fractional anisotropy (FA) metric, which measures directional diffusion of water, were quantified using tract-based spatial statistics (TBSS) with additional details provided by in vivo probabilistic tractography. Our results indicate that 10 voxel clusters differentiated the two groups, including 9 with higher FA in the group with tinnitus. A decrease in FA was found for a single cluster in the group with tinnitus. However, seven of the 9 clusters with higher FA were in left hemisphere thalamic, frontal, and parietal white matter. These foci were localized to the anterior thalamic radiations and the inferior and superior longitudinal fasciculi. The two right-sided clusters with increased FA were located in the inferior fronto-occipital fasciculus and superior longitudinal fasciculus. The only decrease in FA for the tinnitus-positive group was found in the superior longitudinal fasciculus of the left parietal lobe.

Hemispheric lateralization of microstructural white matter abnormalities in children with active benign childhood epilepsy with centrotemporal spikes (BECTS): a preliminary DTI study

PURPOSE

The deficit of white matter is reported to be involved during the disease progression in patients with benign childhood epilepsy with centrotemporal spikes (BECTS). The aim of this study is to investigate patterns of white matter damage in children with BECTS with left- or right-hemispheric focus by using diffusion tensor imaging (DTI), and its relationship with the cofactors such duration, seizure frequency and handedness.

METHODS

Diffusion tensor imaging (DTI) was performed in twenty-eight children with BECTS and eighteen healthy controls. The data were analyzed using both tract-based spatial statistics (TBSS) and region of interest (ROI) analyses. Correlations were investigated between the fractional anisotropy (FA) values of the identified altered regions and clinical features such as age, age of onset and seizure frequency.

RESULTS

The TBSS analysis revealed that white matter impairment in children with rolandic spikes on the ipsilateral hemisphere was much wider. The FA value was significantly lower in the body of the corpus callosum and forceps minor in BECTS patients with spikes on the ipsilateral hemisphere. The seizure frequency correlated positively with the FA values of body of corpus callosum (CC), bilateral cingulate gyrus and left uncinate fasciculi (UA).

CONCLUSION

The impaired WM integrity in patients with BECTS was greater in patients with spikes on the dominant hemisphere, possibly due to the greater vulnerability of the left hemisphere and excitotoxic effects of seizures.

Long-term functional outcomes and correlation with regional brain connectivity by MRI diffusion tractography metrics in a near-term rabbit model of intrauterine growth restriction

BACKGROUND

Intrauterine growth restriction (IUGR) affects 5-10% of all newborns and is associated with increased risk of memory, attention and anxiety problems in late childhood and adolescence. The neurostructural correlates of long-term abnormal neurodevelopment associated with IUGR are unknown. Thus, the aim of this study was to provide a comprehensive description of the long-term functional and neurostructural correlates of abnormal neurodevelopment associated with IUGR in a near-term rabbit model (delivered at 30 days of gestation) and evaluate the development of quantitative imaging biomarkers of abnormal neurodevelopment based on diffusion magnetic resonance imaging (MRI) parameters and connectivity.

METHODOLOGY

At +70 postnatal days, 10 cases and 11 controls were functionally evaluated with the Open Field Behavioral Test which evaluates anxiety and attention and the Object Recognition Task that evaluates short-term memory and attention. Subsequently, brains were collected, fixed and a high resolution MRI was performed. Differences in diffusion parameters were analyzed by means of voxel-based and connectivity analysis measuring the number of fibers reconstructed within anxiety, attention and short-term memory networks over the total fibers.

PRINCIPAL FINDINGS

The results of the neurobehavioral and cognitive assessment showed a significant higher degree of anxiety, attention and memory problems in cases compared to controls in most of the variables explored. Voxel-based analysis (VBA) revealed significant differences between groups in multiple brain regions mainly in grey matter structures, whereas connectivity analysis demonstrated lower ratios of fibers within the networks in cases, reaching the statistical significance only in the left hemisphere for both networks. Finally, VBA and connectivity results were also correlated with functional outcome.

CONCLUSIONS

The rabbit model used reproduced long-term functional impairments and their neurostructural correlates of abnormal neurodevelopment associated with IUGR. The description of the pattern of microstructural changes underlying functional defects may help to develop biomarkers based in diffusion MRI and connectivity analysis.

FMEM: functional mixed effects modeling for the analysis of longitudinal white matter Tract data

Many longitudinal imaging studies have collected repeated diffusion tensor magnetic resonance imaging data to understand white matter maturation and structural connectivity pattern in normal controls and diseased subjects. There is an urgent demand for the development of statistical methods for the analysis of diffusion properties along fiber tracts and clinical data obtained from longitudinal studies. Jointly analyzing repeated fiber-tract diffusion properties and covariates (e.g., age or gender) raises several major challenges including (i) infinite-dimensional functional response data, (ii) complex spatial-temporal correlation structure, and (iii) complex spatial smoothness. To address these challenges, this article is to develop a functional mixed effects modeling (FMEM) framework to delineate the dynamic changes of diffusion properties along major fiber tracts and their association with a set of covariates of interest and the structure of the variability of these white matter tract properties in various longitudinal studies. Our FMEM consists of a functional mixed effects model for addressing all three challenges, an efficient method for spatially smoothing varying coefficient functions, an estimation method for estimating the spatial-temporal correlation structure, a test procedure with local and global test statistics for testing hypotheses of interest associated with functional response, and a simultaneous confidence band for quantifying the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of FMEM and to demonstrate that FMEM significantly outperforms the standard pointwise mixed effects modeling approach. We apply FMEM to study the spatial-temporal dynamics of white-matter fiber tracts in a clinical study of neurodevelopment.

New non-linear color look-up table for visualization of brain fractional anisotropy based on normative measurements - principals and first clinical use

Fractional anisotropy (FA) is the most commonly used quantitative measure of diffusion in the brain. Changes in FA have been reported in many neurological disorders, but the implementation of diffusion tensor imaging (DTI) in daily clinical practice remains challenging. We propose a novel color look-up table (LUT) based on normative data as a tool for screening FA changes. FA was calculated for 76 healthy volunteers using 12 motion-probing gradient directions (MPG), a subset of 59 subjects was additionally scanned using 30 MPG. Population means and 95% prediction intervals for FA in the corpus callosum, frontal gray matter, thalamus and basal ganglia were used to create the LUT. Unique colors were assigned to inflection points with continuous ramps between them. Clinical use was demonstrated on 17 multiple system atrophy (MSA) patients compared to 13 patients with Parkinson disease (PD) and 17 healthy subjects. Four blinded radiologists classified subjects as MSA/non-MSA. Using only the LUT, high sensitivity (80%) and specificity (84%) were achieved in differentiating MSA subjects from PD subjects and controls. The LUTs generated from 12 and 30 MPG were comparable and accentuate FA abnormalities.

Update on diffusion MRI in Parkinson's disease and atypical parkinsonism

Differentiating Parkinson's disease (PD) from other types of neurodegenerative atypical parkinsonism (AP) can be challenging, especially in early disease stages. Routine brain magnetic resonance imaging (MRI) can show atrophy or signal changes in several parts of the brain with fairly high specificity for particular forms of AP, but the overall diagnostic value of routine brain MRI is limited. In recent years, various advanced MRI sequences have become available, including diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI). Here, we review available literature on the value of diffusion MRI for identifying and quantifying different patterns of neurodegeneration in PD and AP, in relation to what is known of underlying histopathologic changes and clinical presentation of these diseases. Next, we evaluate the value of diffusion MRI to differentiate between PD and AP and the potential value of serial diffusion MRI to monitor disease progression. We conclude that diffusion MRI may quantify patterns of neurodegeneration which could be of additional value in clinical use. Future prospective clinical cohort studies are warranted to assess the added diagnostic value of diffusion MRI.

Widespread white matter alterations in patients with end-stage renal disease: a voxelwise diffusion tensor imaging study

BACKGROUND AND PURPOSE

ESRD results in excessive accumulation of urea and toxic metabolites. Hemodialysis is usually performed to maintain health in patients with ESRD; however, it may cause silent white matter alterations in the earlier stages. Hence, this study aimed to perform voxelwise diffusion tensor analysis for global detection of subtle white matter alterations in patients with ESRD.

MATERIALS AND METHODS

Twenty-eight patients with ESRD and 25 age-matched control subjects were enrolled in this study. Each subject underwent CASI assessment and DTI. After spatial normalization of DTI images, voxelwise statistical analyses were performed to compare DTI parameters between the 2 groups.

RESULTS

In patients with ESRD, AD, RD, and MD values were significantly increased, whereas the FA value was significantly decreased, mostly in the corpus callosum, bilateral sagittal stratum, and pons. Multiple regression analysis further revealed that both RD and MD were positively correlated with the duration of hemodialysis in the pons; however, no significant correlation was observed with FA. Negative correlations of RD and MD and a positive correlation of FA with the CASI score were observed in the corona radiata.

CONCLUSIONS

We concluded that voxelwise DTI analysis is helpful in the detection of white matter alterations caused by hemodialysis.

Emerging structure-function relations in the developing face processing system

To evaluate emerging structure-function relations in a neural circuit that mediates complex behavior, we investigated age-related differences among cortical regions that support face recognition behavior and the fiber tracts through which they transmit and receive signals using functional neuroimaging and diffusion tensor imaging. In a large sample of human participants (aged 6-23 years), we derived the microstructural and volumetric properties of the inferior longitudinal fasciculus (ILF), the inferior fronto-occipital fasciculus, and control tracts, using independently defined anatomical markers. We also determined the functional characteristics of core face- and place-selective regions that are distributed along the trajectory of the pathways of interest. We observed disproportionately large age-related differences in the volume, fractional anisotropy, and mean and radial, but not axial, diffusivities of the ILF. Critically, these differences in the structural properties of the ILF were tightly and specifically linked with an age-related increase in the size of a key face-selective functional region, the fusiform face area. This dynamic association between emerging structural and functional architecture in the developing brain may provide important clues about the mechanisms by which neural circuits become organized and optimized in the human cortex.

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.

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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.

Diffusion tensor imaging in idiopathic Parkinson's disease and multisystem atrophy (Parkinsonian type)

BACKGROUND

Differentiation between Parkinson's disease (PD) and atypical Parkinson syndromes (AP) is usually based on clinical examination, but can be challenging especially at early stages of the diseases. Diffusion tensor imaging (DTI) allows for differentiation between PD and AP with good specificity. It is a promising tool for clinical application, but has not been elaborated completely with respect to methodology and validity.

OBJECTIVE

In this study we evaluated differences of the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) within white brain matter between patients with PD and multisystem atrophy of the parkinsonian type (MSAp).

MATERIALS AND METHODS

DTI data of 9 PD and 9 MSAp patients were compared by means of a hypothesis-free whole-brain analysis algorithm (TBSS) focusing on changes within white matter.

RESULTS

We found significantly higher values of the ADC in the MSAp group in the anterior limb of the inner capsule, superior parts of the corona radiata, and lateral periputaminal white matter. Group differences in FA values were not significant.

CONCLUSION

Changes of the ADC close to the putamen proved most consistent and seem to be promising for the ongoing clinical implementation of DTI for the differentiation of hypokinetic-rigid movement disorders.

Reproducibility and biases in high field brain diffusion MRI: An evaluation of acquisition and analysis variables

Diffusion tensor imaging (DTI) of in-vivo human brain provides insights into white matter anatomical connectivity, but little is known about measurement difference biases and reliability of data obtained with last generation high field scanners (>3T) as function of MRI acquisition and analyses variables. Here we assess the impact of acquisition (voxel size: 1.8×1.8×1.8, 2×2×2 and 2.5×2.5×2.5mm(3), b-value: 700, 1000 and 1300s/mm(2)) and analysis variables (within-session averaging and co-registration methods) on biases and test-retest reproducibility of some common tensor derived quantities like fractional anisotropy (FA), mean diffusivity (MD), axial and radial diffusivity in a group of healthy subjects at 4T in three regions: arcuate fasciculus, corpus callosum and cingulum. Averaging effects are also evaluated on a full-brain voxel based approach. The main results are: i) group FA and MD reproducibility errors across scan sessions are on average double of those found in within-session repetitions (≈1.3 %), regardless of acquisition protocol and region; ii) within-session averaging of two DTI acquisitions does not improve reproducibility of any of the quantities across sessions at the group level, regardless of acquisition protocol; iii) increasing voxel size biased MD, axial and radial diffusivities to higher values and FA to lower values; iv) increasing b-value biased all quantities to lower values, axial diffusivity showing the strongest effects; v) the two co-registration methods evaluated gave similar bias and reproducibility results. Altogether these results show that reproducibility of FA and MD is comparable to that found at lower fields, not significantly dependent on pre-processing and acquisition protocol manipulations, but that the specific choice of acquisition parameters can significantly bias the group measures of FA, MD, axial and radial diffusivities.

A hitchhiker's guide to diffusion tensor imaging

Diffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity. However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. Herein, we provide a straightforward hitchhiker's guide, covering all of the workflow's major stages. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.

Tracking cerebral white matter changes across the lifespan: insights from diffusion tensor imaging studies

Delineating the normal development of brain white matter (WM) over the human lifespan is crucial to improved understanding of underlying WM pathology in neuropsychiatric and neurological conditions. We review the extant literature concerning diffusion tensor imaging studies of brain WM development in healthy individuals available until October 2012, summarise trends of normal development of human brain WM and suggest possible future research directions. Temporally, brain WM maturation follows a curvilinear pattern with an increase in fractional anisotropy (FA) from newborn to adolescence, decelerating in adulthood till a plateau around mid-adulthood, and a more rapid decrease of FA from old age onwards. Spatially, brain WM tracts develop from central to peripheral regions, with evidence of anterior-to-posterior maturation in commissural and projection fibres. The corpus callosum and fornix develop first and decline earlier, whilst fronto-temporal WM tracts like cingulum and uncinate fasciculus have protracted maturation and decline later. Prefrontal WM is most vulnerable with greater age-related FA reduction compared with posterior WM. Future large scale studies adopting longitudinal design will better clarify human brain WM changes over time.

Multimodal image analysis of sensorimotor gating in healthy women

Prepulse inhibition (PPI) deficits have been reported in individuals with schizophrenia and other psychiatric disorders with dysfunction of the cortico-striato-pallido-thalamic circuit. The purpose of this study was to investigate the structural neural correlates of PPI by using magnetic resonance imaging (MRI) metrics. The subjects were 53 healthy women (mean age; 40.7±11.3 years). We examined the possible relationships between PPI and diffusion tensor imaging (DTI) metrics to estimate white matter integrity and gray matter volume analyzed using the DARTEL (diffeomorphic anatomical registration through exponentiated lie) algebra method. There were significant correlations between DTI metrics and PPI in the parahippocampal region, the anterior limb of the internal capsule, the ventral tegmental area, the thalamus and anterior thalamic radiations, the left prefrontal region, the callosal commissural fiber, and various white matter regions. There were also positive correlations between PPI and gray matter volume in the bilateral parietal gyri and the left inferior prefrontal gyrus at a trend level. The present study revealed evidence of a relationship between PPI and the integrity of white matter. This result was compatible with the previous suggestion that PPI would be modulated by the cortico-striato-thalamic-pallido-pontine circuit.

The physical and biological basis of quantitative parameters derived from diffusion MRI

Diffusion magnetic resonance imaging is a quantitative imaging technique that measures the underlying molecular diffusion of protons. Diffusion-weighted imaging (DWI) quantifies the apparent diffusion coefficient (ADC) which was first used to detect early ischemic stroke. However this does not take account of the directional dependence of diffusion seen in biological systems (anisotropy).Diffusion tensor imaging (DTI) provides a mathematical model of diffusion anisotropy and is widely used. Parameters, including fractional anisotropy (FA), mean diffusivity (MD), parallel and perpendicular diffusivity can be derived to provide sensitive, but non-specific, measures of altered tissue structure. They are typically assessed in clinical studies by voxel-based or region-of-interest based analyses.The increasing recognition of the limitations of the diffusion tensor model has led to more complex multi-compartment models such as CHARMED, AxCaliber or NODDI being developed to estimate microstructural parameters including axonal diameter, axonal density and fiber orientations. However these are not yet in routine clinical use due to lengthy acquisition times.In this review, I discuss how molecular diffusion may be measured using diffusion MRI, the biological and physical bases for the parameters derived from DWI and DTI, how these are used in clinical studies and the prospect of more complex tissue models providing helpful micro-structural information.

Diffusion tensor metrics as biomarkers in Alzheimer's disease

Background

Although diffusion tensor imaging has been a major research focus for Alzheimer’s disease in recent years, it remains unclear whether it has sufficient stability to have biomarker potential. To date, frequently inconsistent results have been reported, though lack of standardisation in acquisition and analysis make such discrepancies difficult to interpret. There is also, at present, little knowledge of how the biometric properties of diffusion tensor imaging might evolve in the course of Alzheimer’s disease.

Methods

The biomarker question was addressed in this study by adopting a standardised protocol both for the whole brain (tract-based spatial statistics), and for a region of interest: the midline corpus callosum. In order to study the evolution of tensor changes, cross-sectional data from very mild (N = 21) and mild (N = 22) Alzheimer’s disease patients were examined as well as a longitudinal cohort (N = 16) that had been rescanned at 12 months.

Findings and Significance

The results revealed that increased axial and mean diffusivity are the first abnormalities to occur and that the first region to develop such significant differences was mesial parietal/splenial white matter; these metrics, however, remained relatively static with advancing disease indicating they are suitable as ‘state-specific’ markers. In contrast, increased radial diffusivity, and therefore decreased fractional anisotropy–though less detectable early–became increasingly abnormal with disease progression, and, in the splenium of the corpus callosum, correlated significantly with dementia severity; these metrics therefore appear ‘stage-specific’ and would be ideal for monitoring disease progression. In addition, the cross-sectional and longitudinal analyses showed that the progressive abnormalities in radial diffusivity and fractional anisotropy always occurred in areas that had first shown an increase in axial and mean diffusivity. Given that the former two metrics correlate with dementia severity, but the latter two did not, it would appear that increased axial diffusivity represents an upstream event that precedes neuronal loss.

White matter development in adolescence: diffusion tensor imaging and meta-analytic results

BACKGROUND

In light of the evidence for brain white matter (WM) abnormalities in schizophrenia, study of normal WM maturation in adolescence may provide critical insights relevant to the neurodevelopment of the disorder. Voxel-wise diffusion tensor imaging (DTI) studies have consistently demonstrated increases in fractional anisotropy (FA), a putative measure of WM integrity, from childhood into adolescence. However, the WM tracts that show FA increases have been variable across studies. Here, we aimed to assess which WM tracts show the most pronounced changes across adolescence.

METHODS

DTI was performed in 78 healthy subjects aged 8-21 years, and voxel-wise analysis conducted using tract-based spatial statistics (TBSS). In addition, we performed the first meta-analysis of TBSS studies on WM development in adolescence.

RESULTS

In our sample, we observed bilateral increases in FA with age, which were most significant in the left superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and anterior thalamic radiation. These findings were confirmed by the meta-analysis, and FA increase in the bilateral SLF was the most consistent finding across studies. Moreover, in our sample, FA of the bilateral SLF showed a positive association with verbal working memory performance and partially mediated increases in verbal fluency as a function of increasing age.

CONCLUSIONS

These data highlight increasing connectivity in the SLF during adolescence. In light of evidence for compromised SLF integrity in high-risk and first-episode patients, these data suggest that abnormal maturation of the SLF during adolescence may be a key target in the neurodevelopment of schizophrenia.

Diffusion tensor imaging studies in vascular disease: A review of the literature

Cerebrovascular disease (CVD) is often present in old age and may be associated with microstructural pathology of white matter (WM) and cognitive dysfunction. The current review investigated the relationship between CVD, cognitive status and WM integrity as assessed by diffusion tensor imaging (DTI).

Association of microstructural white matter abnormalities with cognitive dysfunction in geriatric patients with major depression

Major depression disorder (MDD) is one of the most common causes of disability in people over 60years of age. Previous studies have linked affective and cognitive symptoms of MDD to white matter (WM) disruption in limbic-cortical circuits. However, the relationship between clinical cognitive deficits and loss of integrity in particular WM tracts is poorly understood. Fractional anisotropy (FA) as a measure of WM integrity was investigated in 17 elderly MDD subjects in comparison with 18 age-matched controls using tract-based spatial statistics (TBSS) and correlated with clinical and cognitive parameters. MDD patients revealed significantly reduced FA in the right posterior cingulate cluster (PCC) compared with controls. FA in the right PCC (but not in the left PCC) showed a significant positive correlation with performance in a verbal naming task, and showed a non-significant trend toward a correlation with verbal fluency and episodic memory performance. In control subjects, no correlations were found between cognitive tasks and FA values either in the right or left PCC. Results provide additional evidence supporting the neuronal disconnection hypothesis in MDD and suggest that cognitive deficits are related to the loss of integrity in WM tracts associated with the disorder.

Relationship between apathy and diffusion tensor imaging metrics of the brain in Alzheimer's disease

OBJECTIVE

Alzheimer's disease (AD) research has largely concentrated on the study of cognitive decline, but the associated behavioral and neuropsychiatric symptoms are of equal importance in the clinical profile of the disease. Apathy is the most common neuropsychiatric manifestation in AD. Clinical, multimodal neuroimaging studies and pathologic studies of apathy in AD have suggested an association with frontal dysfunction but without a definitive localization. In this study, we examined the association between apathy and white matter integrity using diffusion tensor imaging (DTI).

METHODS

Twenty-one AD patients underwent DTI and neuropsychiatric and cognitive assessments. All fractional anisotropy (FA) maps were normalized to the standard space, and the association between the apathy scale and DTI metrics were evaluated voxel basically.

RESULTS

Statistical parametric mapping analysis showed that there were statistically negative correlations between the apathy scale and FA values in the right anterior cingulate, right thalamus, and bilateral parietal regions using age, Mini-Mental State Examination score and sex as nuisance variables.

CONCLUSIONS

Apathy in AD is associated with impaired white matter integrity in the anterior cingulate and medial thalamus. These results reinforce the confluence of evidence from other investigational modalities in implicating limbic dysfunction and related neuronal circuits in the neurobiology of apathy in AD.

Semiparametric Bayesian local functional models for diffusion tensor tract statistics

We propose a semiparametric Bayesian local functional model (BFM) for the analysis of multiple diffusion properties (e.g., fractional anisotropy) along white matter fiber bundles with a set of covariates of interest, such as age and gender. BFM accounts for heterogeneity in the shape of the fiber bundle diffusion properties among subjects, while allowing the impact of the covariates to vary across subjects. A nonparametric Bayesian LPP2 prior facilitates global and local borrowings of information among subjects, while an infinite factor model flexibly represents low-dimensional structure. Local hypothesis testing and credible bands are developed to identify fiber segments, along which multiple diffusion properties are significantly associated with covariates of interest, while controlling for multiple comparisons. Moreover, BFM naturally group subjects into more homogeneous clusters. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFM. We apply BFM to investigate the development of white matter diffusivities along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment in new born infants.

Nonlinear microstructural changes in the right superior temporal sulcus and lateral occipitotemporal gyrus between 35 and 43 weeks in the preterm brain

Using diffusion tensor imaging (DTI), we explored microstructural brain maturation in a population of 65 preterm neonates who underwent magnetic resonance imaging between 35 and 43 weeks of corrected gestational age. A voxel-based analysis approach, statistical parametric mapping (SPM8), was used to evidence the nonlinear changes with the corrected gestational age in the regional distribution of mean diffusivity (MD), fractional anisotropy (FA), longitudinal and transverse diffusivities (λ//and λ⊥). We found that FA changes nonlinearly with age around the right superior temporal sulcus and in the right lateral occipitotemporal gyrus, with FA decrease between 34 and 39 weeks followed by FA increase from 40 weeks to 43 weeks. Considering the key role of these brain areas in verbal and non-verbal communicative behaviors, the effect of these microstructural changes in terms of early social network functional maturation needs to be assessed by joint functional and anatomical studies.

Magnetic resonance fiber density mapping of age-related white matter changes

OBJECTIVES

To introduce fiber density mapping (FDM) for investigation of age-related white matter (WM) changes and to compare its capabilities with conventional diffusion tensor imaging (DTI) post-processing.

METHODS

DTI data with 1.9 mm(3) isotropic voxels were acquired from 44 healthy volunteers (18-88 years) at 3T. FDM is a 3-step approach which includes diagonalization of the diffusion tensor, fiber reconstruction for the whole brain, and calculation of fiber density (FD) values. Maps of fractional anisotropy (FA) and mean diffusivity (MD) were additionally calculated. Voxel-based analyses were performed to determine volume clusters of significant correlation with age. Bivariate linear regression models and Hotelling-Williams tests were used to detect significant differences between correlations.

RESULTS

FDM detected a larger WM volume affected by age-related changes concomitant with fewer significant clusters compared to FA and MD. This indicates that WM alterations due to normal aging occur rather globally than locally. FD values showed a significant stronger correlation with age in frontal lobes (prefrontal and precentral gyrus), limbic lobes (cingulate and parahippocampal gyrus), the corpus callosum (genu) and temporal lobes.

CONCLUSIONS

FDM shows higher sensitivity for detection of age-related WM changes because it includes all surrounding fiber structures into the evaluation of each DTI data voxel.

Development of white matter pathways in typically developing preadolescent children

The first phase of major neuronal rearrangements in the brain takes place during the prenatal period. While the brain continues maturation throughout childhood, a critical second phase of synaptic overproduction and elimination takes place during the preadolescent period. Despite the importance of this developmental phase, few studies have evaluated neural changes taking place during this period. In this study, MRI diffusion tensor imaging data from a normative sample of 126 preadolescent children (59 girls and 67 boys) between the ages of 6 and 10 years were analyzed in order to characterize age-relationships in the white matter microstructure. Tract Based Spatial Statistics (TBSS) method was used for whole brain analysis of white matter tracts without a priori assumption about the location of age associated differences. Our results demonstrate significant age-associated differences in most of the major fiber tracts bilaterally and along the whole body of the tracts. In contrast, developmental differences in the cingulum at the level of the parahippocampal region were only observed in the right hemisphere. We suggest that these age-relationships with a widespread distribution seen during the preadolescent years maybe relevant for the implementation of cognitive and social behaviors needed for a normal development into adulthood.

Diffusion tensor imaging findings of white matter changes in first episode schizophrenia: a systematic review

Earlier structural magnetic resonance imaging in schizophrenia have noted smaller white matter volumes in diverse brain regions and recent diffusion tensor imaging (DTI) studies have allowed better elucidation of changes in brain white matter integrity within the illness. As white matter abnormalities have been reported to occur early in the course of schizophrenia, we systematically review extant DTI studies of anomalies of white matter integrity in first episode schizophrenia (FES) up till October 2011. Overall, disruptions of white matter integrity were found in the cortical, subcortical brain regions and white matter associative and commissural tracts, suggesting that changes of cortical-subcortical white matter integrity were found at an early stage of the disorder. These changes in white matter integrity were correlated with specific cognitive deficits (verbal and spatial working memory) as well as psychopathology (positive more than negative symptoms) in patients with FES. The correlation of these white matter integrity changes with cognitive and phenomenological factors may shed light on neurobiological substrates underlying these clinical manifestations. Future studies need to validate these findings in larger samples of subjects and in different populations as well as chart the progress of these cerebral white matter changes over time so as to better appreciate their trajectory with illness course, treatment and chronicity.

Changes in the brain microstructure of children with primary monosymptomatic nocturnal enuresis: a diffusion tensor imaging study

BACKGROUND

Primary monosymptomatic nocturnal enuresis (PMNE) is a common disorder in school-aged children. Previous studies have suggested that a developmental delay might play a role in the pathology of children with PMNE. However, microstructural abnormalities in the brains of these children have not been thoroughly investigated.

METHODOLOGY/PRINCIPAL FINDINGS

In this work, we evaluated structural changes in the brains of children with PMNE using diffusion tensor imaging (DTI). Two groups consisting of 26 children with PMNE and 26 healthy controls were scanned using magnetic resonance DTI. The diffusion parameters of fractional anisotropy (FA) and mean diffusivity (MD) were subjected to whole-brain, voxel-wise group comparisons using statistical parametric mapping (SPM). When compared to healthy subjects, children with PMNE showed both a decrease in FA and an increase in MD in the thalamus. MD also increased in the frontal lobe, the anterior cingulate cortex and the insula; these areas are all involved in controlling micturition. The significant changes seen in the thalamus could affect both urine storage and arousal from sleep.

CONCLUSIONS/SIGNIFICANCE

The microstructure abnormalities were observed in the thalamus, the medial frontal gyrus, the anterior cingulate cortex and the insula, which are involved in micturition control network. This indicates developmental delay in these areas may be the cause of PMNE.

Neonatal neurobehavior and diffusion MRI changes in brain reorganization due to intrauterine growth restriction in a rabbit model

Background

Intrauterine growth restriction (IUGR) affects 5–10% of all newborns and is associated with a high risk of abnormal neurodevelopment. The timing and patterns of brain reorganization underlying IUGR are poorly documented. We developed a rabbit model of IUGR allowing neonatal neurobehavioral assessment and high resolution brain diffusion magnetic resonance imaging (MRI). The aim of the study was to describe the pattern and functional correlates of fetal brain reorganization induced by IUGR.

Methodology/Principal Findings

IUGR was induced in 10 New Zealand fetal rabbits by ligation of 40–50% of uteroplacental vessels in one horn at 25 days of gestation. Ten contralateral horn fetuses were used as controls. Cesarean section was performed at 30 days (term 31 days). At postnatal day +1, neonates were assessed by validated neurobehavioral tests including evaluation of tone, spontaneous locomotion, reflex motor activity, motor responses to olfactory stimuli, and coordination of suck and swallow. Subsequently, brains were collected and fixed and MRI was performed using a high resolution acquisition scheme. Global and regional (manual delineation and voxel based analysis) diffusion tensor imaging parameters were analyzed. IUGR was associated with significantly poorer neurobehavioral performance in most domains. Voxel based analysis revealed fractional anisotropy (FA) differences in multiple brain regions of gray and white matter, including frontal, insular, occipital and temporal cortex, hippocampus, putamen, thalamus, claustrum, medial septal nucleus, anterior commissure, internal capsule, fimbria of hippocampus, medial lemniscus and olfactory tract. Regional FA changes were correlated with poorer outcome in neurobehavioral tests.

Conclusions

IUGR is associated with a complex pattern of brain reorganization already at birth, which may open opportunities for early intervention. Diffusion MRI can offer suitable imaging biomarkers to characterize and monitor brain reorganization due to fetal diseases.

VBM-DTI correlates of verbal intelligence: a potential link to Broca's area

Human brain lesion studies first investigated the biological roots of cognitive functions including language in the late 1800s. Neuroimaging studies have reported correlation findings with general intelligence predominantly in fronto-parietal cortical areas. However, there is still little evidence about the relationship between verbal intelligence and structural properties of the brain. We predicted that verbal performance is related to language regions of Broca's and Wernicke's areas. Verbal intelligence quotient (vIQ) was assessed in 30 healthy young subjects. T1-weighted MRI and diffusion tensor imaging data sets were acquired. Voxel-wise regression analyses were used to correlate fractional anisotropy (FA) and mean diffusivity values with vIQ. Moreover, regression analyses of regional brain volume with vIQ were performed adopting voxel-based morphometry (VBM) and ROI methodology. Our analyses revealed a significant negative correlation between vIQ and FA and a significant positive correlation between vIQ and mean diffusivity in the left-hemispheric Broca's area. VBM regression analyses did not show significant results, whereas a subsequent ROI analysis of Broca's area FA peak cluster demonstrated a positive correlation of gray matter volume and vIQ. These findings suggest that cortical thickness in Broca's area contributes to verbal intelligence. Diffusion parameters predicted gray matter ratio in Broca's area more sensitive than VBM methodology.

Generative-discriminative basis learning for medical imaging

This paper presents a novel dimensionality reduction method for classification in medical imaging. The goal is to transform very high-dimensional input (typically, millions of voxels) to a low-dimensional representation (small number of constructed features) that preserves discriminative signal and is clinically interpretable. We formulate the task as a constrained optimization problem that combines generative and discriminative objectives and show how to extend it to the semi-supervised learning (SSL) setting. We propose a novel large-scale algorithm to solve the resulting optimization problem. In the fully supervised case, we demonstrate accuracy rates that are better than or comparable to state-of-the-art algorithms on several datasets while producing a representation of the group difference that is consistent with prior clinical reports. Effectiveness of the proposed algorithm for SSL is evaluated with both benchmark and medical imaging datasets. In the benchmark datasets, the results are better than or comparable to the state-of-the-art methods for SSL. For evaluation of the SSL setting in medical datasets, we use images of subjects with mild cognitive impairment (MCI), which is believed to be a precursor to Alzheimer's disease (AD), as unlabeled data. AD subjects and normal control (NC) subjects are used as labeled data, and we try to predict conversion from MCI to AD on follow-up. The semi-supervised extension of this method not only improves the generalization accuracy for the labeled data (AD/NC) slightly but is also able to predict subjects which are likely to converge to AD.

Effects of aging and calorie restriction on white matter in rhesus macaques

Rhesus macaques on a calorie restricted diet (CR) develop less age-related disease, have virtually no indication of diabetes, are protected against sarcopenia, and potentially live longer. Beneficial effects of caloric restriction likely include reductions in age-related inflammation and oxidative damage. Oligodendrocytes are particularly susceptible to inflammation and oxidative stress, therefore, we hypothesized that CR would have a beneficial effect on brain white matter and would attenuate age-related decline in this tissue. CR monkeys and controls underwent diffusion tensor imaging (DTI). A beneficial effect of CR indexed by DTI was observed in superior longitudinal fasciculus, fronto-occipital fasciculus, external capsule, and brainstem. Aging effects were observed in several regions, although CR appeared to attenuate age-related alterations in superior longitudinal fasciculus, frontal white matter, external capsule, right parahippocampal white matter, and dorsal occipital bundle. The results, however, were regionally specific and also suggested that CR is not salutary across all white matter. Further evaluation of this unique cohort of elderly primates to mortality will shed light on the ultimate benefits of an adult-onset, moderate CR diet for deferring brain aging.