UNC-Utah NA-MIC framework for DTI fiber tract analysis

White matter development and language abilities during infancy in autism spectrum disorder

White matter (WM) fiber tract differences are present in autism spectrum disorder (ASD) and could be important markers of behavior. One of the earliest phenotypic differences in ASD are language atypicalities. Although language has been linked to WM in typical development, no work has evaluated this association in early ASD. Participants came from the Infant Brain Imaging Study and included 321 infant siblings of children with ASD at high likelihood (HL) for developing ASD; 70 HL infants were later diagnosed with ASD (HL-ASD), and 251 HL infants were not diagnosed with ASD (HL-Neg). A control sample of 140 low likelihood infants not diagnosed with ASD (LL-Neg) were also included. Infants contributed expressive language, receptive language, and diffusion tensor imaging data at 6-, 12-, and 24 months. Mixed effects regression models were conducted to evaluate associations between WM and language trajectories. Trajectories of microstructural changes in the right arcuate fasciculus were associated with expressive language development. HL-ASD infants demonstrated a different developmental pattern compared to the HL-Neg and LL-Neg groups, wherein the HL-ASD group exhibited a positive association between WM fractional anisotropy and language whereas HL-Neg and LL-Neg groups showed weak or no association. No other fiber tracts demonstrated significant associations with language. In conclusion, results indicated arcuate fasciculus WM is linked to language in early toddlerhood for autistic toddlers, with the strongest associations emerging around 24 months. To our knowledge, this is the first study to evaluate associations between language and WM development during the pre-symptomatic period in ASD.

Subtle microstructural alterations in white matter tracts involved in socio-emotional processing after very preterm birth

Children born very preterm (VPT, < 32 weeks of gestation) have an increased risk of developing socio-emotional difficulties. Possible neural substrates for these socio-emotional difficulties are alterations in the structural connectivity of the social brain due to premature birth. The objective of the current study was to study microstructural white matter integrity in VPT versus full-term (FT) born school-aged children along twelve white matter tracts involved in socio-emotional processing. Diffusion MRI scans were obtained from a sample of 35 VPT and 38 FT 8-to-12-year-old children. Tractography was performed using TractSeg, a state-of-the-art neural network-based approach, which offers investigation of detailed tract profiles of fractional anisotropy (FA). Group differences in FA along the tracts were investigated using both a traditional and complementary functional data analysis approach. Exploratory correlations were performed between the Social Responsiveness Scale (SRS-2), a parent-report questionnaire assessing difficulties in social functioning, and FA along the tract. Both analyses showed significant reductions in FA for the VPT group along the middle portion of the right SLF I and an anterior portion of the left SLF II. These group differences possibly indicate altered white matter maturation due to premature birth and may contribute to altered functional connectivity in the Theory of Mind network which has been documented in earlier work with VPT samples. Apart from reduced social motivation in the VPT group, there were no significant group differences in reported social functioning, as assessed by SRS-2. We found that in the VPT group higher FA values in segments of the left SLF I and right SLF II were associated with better social functioning. Surprisingly, the opposite was found for segments in the right IFO, where higher FA values were associated with worse reported social functioning. Since no significant correlations were found for the FT group, this relationship may be specific for VPT children. The current study overcomes methodological limitations of previous studies by more accurately segmenting white matter tracts using constrained spherical deconvolution based tractography, by applying complementary tractometry analysis approaches to estimate changes in FA more accurately, and by investigating the FA profile along the three components of the SLF.

Effects of anesthesia exposure on postnatal maturation of white matter in rhesus monkeys

There is increasing concern about the potential effects of anesthesia exposure on the developing brain. The effects of relatively brief anesthesia exposures used repeatedly to acquire serial magnetic resonance imaging scans could be examined prospectively in rhesus macaques. We analyzed magnetic resonance diffusion tensor imaging (DTI) of 32 rhesus macaques (14 females, 18 males) aged 2 weeks to 36 months to assess postnatal white matter (WM) maturation. We investigated the longitudinal relationships between each DTI property and anesthesia exposure, taking age, sex, and weight of the monkeys into consideration. Quantification of anesthesia exposure was normalized to account for variation in exposures. Segmented linear regression with two knots provided the best model for quantifying WM DTI properties across brain development as well as the summative effect of anesthesia exposure. The resulting model revealed statistically significant age and anesthesia effects in most WM tracts. Our analysis indicated there were major effects on WM associated with low levels of anesthesia even when repeated as few as three times. Fractional anisotropy values were reduced across several WM tracts in the brain, indicating that anesthesia exposure may delay WM maturation, and highlight the potential clinical concerns with even a few exposures in young children.

Serum assessment of traumatic axonal injury: the correlation of GFAP, t-Tau, UCH-L1, and NfL levels with diffusion tensor imaging metrics and its prognosis utility

OBJECTIVE

Diagnosis of traumatic axonal injury (TAI) is challenging because of its underestimation by conventional MRI and the technical requirements associated with the processing of diffusion tensor imaging (DTI). Serum biomarkers seem to be able to identify patients with abnormal CT scanning findings, but their potential role to assess TAI has seldomly been explored.

METHODS

Patients with all severities of traumatic brain injury (TBI) were prospectively included in this study between 2016 and 2021. They underwent blood extraction within 24 hours after injury and imaging assessment, including DTI. Serum concentrations of glial fibrillary acidic protein, total microtubule-associated protein (t-Tau), ubiquitin C-terminal hydrolase L1 (UCH-L1), and neurofilament light chain (NfL) were measured using an ultrasensitive Simoa multiplex assay panel, a digital form of enzyme-linked immunosorbent assay. The Glasgow Outcome Scale-Extended score was determined at 6 months after TBI. The relationships between biomarker concentrations, volumetric analysis of corpus callosum (CC) lesions, and fractional anisotropy (FA) were analyzed by nonparametric tests. The prognostic utility of the biomarker was determined by calculating the C-statistic and an ordinal regression analysis.

RESULTS

A total of 87 patients were included. Concentrations of all biomarkers were significantly higher for patients compared with controls. Although the concentration of the biomarkers was affected by the presence of mass lesions, FA of the CC was an independent factor influencing levels of UCH-L1 and NfL, which positioned these two biomarkers as better surrogates of TAI. Biomarkers also performed well in determining patients who would have had unfavorable outcome. NfL and the FA of the CC are independent complementary factors related to outcome.

CONCLUSIONS

UCH-L1 and NfL seem to be the biomarkers more specific to detect TAI. The concentration of NfL combined with the FA of the CC might help predict long-term outcome.

Infant Visual Brain Development and Inherited Genetic Liability in Autism

OBJECTIVE

Autism spectrum disorder (ASD) is heritable, and younger siblings of ASD probands are at higher likelihood of developing ASD themselves. Prospective MRI studies of siblings report that atypical brain development precedes ASD diagnosis, although the link between brain maturation and genetic factors is unclear. Given that familial recurrence of ASD is predicted by higher levels of ASD traits in the proband, the authors investigated associations between proband ASD traits and brain development among younger siblings.

METHODS

In a sample of 384 proband-sibling pairs (89 pairs concordant for ASD), the authors examined associations between proband ASD traits and sibling brain development at 6, 12, and 24 months in key MRI phenotypes: total cerebral volume, cortical surface area, extra-axial cerebrospinal fluid, occipital cortical surface area, and splenium white matter microstructure. Results from primary analyses led the authors to implement a data-driven approach using functional connectivity MRI at 6 months.

RESULTS

Greater levels of proband ASD traits were associated with larger total cerebral volume and surface area and larger surface area and reduced white matter integrity in components of the visual system in siblings who developed ASD. This aligned with weaker functional connectivity between several networks and the visual system among all siblings during infancy.

CONCLUSIONS

The findings provide evidence that specific early brain MRI phenotypes of ASD reflect quantitative variation in familial ASD traits. Multimodal anatomical and functional convergence on cortical regions, fiber pathways, and functional networks involved in visual processing suggest that inherited liability has a role in shaping the prodromal development of visual circuitry in ASD.

Diffusion Tensor Based White Matter Tract Atlases for Pediatric Populations

Diffusion Tensor Imaging (DTI) is a non-invasive neuroimaging method that has become the most widely employed MRI modality for investigations of white matter fiber pathways. DTI has proven especially valuable for improving our understanding of normative white matter maturation across the life span and has also been used to index clinical pathology and cognitive function. Despite its increasing popularity, especially in pediatric research, the majority of existing studies examining infant white matter maturation depend on regional or white matter skeleton-based approaches. These methods generally lack the sensitivity and spatial specificity of more advanced functional analysis options that provide information about microstructural properties of white matter along fiber bundles. DTI studies of early postnatal brain development show that profound microstructural and maturational changes take place during the first two years of life. The pattern and rate of these changes vary greatly throughout the brain during this time compared to the rest of the life span. For this reason, appropriate image processing of infant MR imaging requires the use of age-specific reference atlases. This article provides an overview of the pre-processing, atlas building, and the fiber tractography procedures used to generate two atlas resources, one for neonates and one for 1- to 2-year-old populations. Via the UNC-NAMIC DTI Fiber Analysis Framework, our pediatric atlases provide the computational templates necessary for the fully automatic analysis of infant DTI data. To the best of our knowledge, these atlases are the first comprehensive population diffusion fiber atlases in early pediatric ages that are publicly available.

Optimized Tractography Mapping and Quantitative Evaluation of Pyramidal Tracts for Surgical Resection of Insular Gliomas: a Correlative Study with Diffusion Tensor Imaging–Derived Metrics and Patient Motor Strength

We investigate the correlation between diffusion tensor imaging (DTI)-derived metric statistics and motor strength grade of insular glioma patients after optimizing the pyramidal tract (PT) delineation. Motor strength grades of 45 insular glioma patients were assessed. All the patients underwent structural and diffusion MRI examination before and after surgery. We co-registered pre- and post-op datasets, and a two-tensor unscented Kalman filter (UKF) algorithm was employed to delineate bilateral PTs after DWI pre-processing. The tractography results were voxelized, and their labelmaps were cropped according to the location of frontal and insular parts of the lesion. Both the whole and cropped labelmaps were used as regions of interest to analyze fractional anisotropy (FA) and Trace statistics; hence, their ratios were calculated (lesional side tract/contralateral normal tract). The combination of DWI pre-processing and two-tensor UKF algorithm successfully delineated bilateral PTs of all the patients. It effectively accomplished both full fiber delineation within the edema and an extensive lateral fanning that had a favorable correspondence to the bilateral motor cortices. Before surgery, correlations were found between patients' motor strength grades and ratios of PT volume and FA standard deviation (SD). Nearly 3 months after surgery, correlations were found between motor strength grades and the ratios of metric statistics as follows: whole PT volume, whole mean FA, and FA SD. We substantiated the correlation between DTI-derived metric statistics and motor strength grades of insular glioma patients. Moreover, we posed a workflow for comprehensive pre- and post-op DTI quantitative research of glioma patients.

Exposure to prenatal maternal distress and infant white matter neurodevelopment

The prenatal period represents a critical time for brain growth and development. These rapid neurological advances render the fetus susceptible to various influences with life-long implications for mental health. Maternal distress signals are a dominant early life influence, contributing to birth outcomes and risk for offspring psychopathology. This prospective longitudinal study evaluated the association between prenatal maternal distress and infant white matter microstructure. Participants included a racially and socioeconomically diverse sample of 85 mother-infant dyads. Prenatal distress was assessed at 17 and 29 weeks' gestational age (GA). Infant structural data were collected via diffusion tensor imaging at 42-45 weeks' postconceptional age. Findings demonstrated that higher prenatal maternal distress at 29 weeks' GA was associated with increased fractional anisotropy (b = .283, t(64) = 2.319, p = .024) and with increased axial diffusivity (b = .254, t(64) = 2.067, p = .043) within the right anterior cingulate white matter tract. No other significant associations were found with prenatal distress exposure and tract fractional anisotropy or axial diffusivity at 29 weeks' GA, nor earlier in gestation.

Traumatic axonal injury: is the prognostic information produced by conventional MRI and DTI complementary or supplementary?

OBJECTIVE

A traumatic axonal injury (TAI) diagnosis has traditionally been based on conventional MRI, especially on those sequences with a higher sensitivity to edema and blood degradation products. A more recent technique, diffusion tensor imaging (DTI), can infer the microstructure of white matter (WM) due to the restricted diffusion of water in organized tissues. However, there is little information regarding the correlation of the findings obtained by both methods and their use for outcome prognosis. The main objectives of this study were threefold: 1) study the correlation between DTI metrics and conventional MRI findings; 2) evaluate whether the prognostic information provided by the two techniques is supplementary or complementary; and 3) determine the incremental value of the addition of these variables compared to a traditional prognostic model.

METHODS

The authors studied 185 patients with moderate to severe traumatic brain injury (TBI) who underwent MRI with DTI study during the subacute stage. The number and volume of lesions in hemispheric subcortical WM, corpus callosum (CC), basal ganglia, thalamus, and brainstem in at least four conventional MRI sequences (T1-weighted, T2-weighted, FLAIR, T2* gradient recalled echo, susceptibility-weighted imaging, and diffusion-weighted imaging) were determined. Fractional anisotropy (FA) was measured in 28 WM bundles using the region of interest method. Nonparametric tests were used to evaluate the colocalization of macroscopic lesions and FA. A multivariate logistic regression analysis was performed to assess the independent prognostic value of each neuroimaging modality after adjustment for relevant clinical covariates, and the internal validation of the model was evaluated in a contemporary cohort of 92 patients.

RESULTS

Differences in the lesion load between patients according to their severity and outcome were found. Colocalization of macroscopic nonhemorrhagic TAI lesions (not microbleeds) and lower FA was limited to the internal and external capsule, corona radiata, inferior frontooccipital fasciculus, CC, and brainstem. However, a significant association between the FA value and the identification of macroscopic lesions in distant brain regions was also detected. Specifically, lower values of FA of some hemispheric WM bundles and the splenium of the CC were related to a higher number and volume of hyperintensities in the brainstem. The regression analysis revealed that age, motor score, hypoxia, FA of the genu of the CC, characterization of TAI lesions in the CC, and the presence of thalamic/basal ganglia lesions were independent prognostic factors. The performance of the proposed model was higher than that of the IMPACT (International Mission on Prognosis and Analysis of Clinical Trials in TBI) model in the validation cohort.

CONCLUSIONS

Very limited colocalization of hyperintensities (none for microbleeds) with FA values was discovered. DTI and conventional MRI provide complementary prognostic information, and their combination can improve the performance of traditional prognostic models.

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.

Infantile Iron Deficiency Affects Brain Development in Monkeys Even After Treatment of Anemia

A high percent of oxidative energy metabolism is needed to support brain growth during infancy. Unhealthy diets and limited nutrition, as well as other environmental insults, can compromise these essential developmental processes. In particular, iron deficiency anemia (IDA) has been found to undermine both normal brain growth and neurobehavioral development. Even moderate ID may affect neural maturation because when iron is limited, it is prioritized first to red blood cells over the brain. A primate model was used to investigate the neural effects of a transient ID and if deficits would persist after iron treatment. The large size and postnatal growth of the monkey brain makes the findings relevant to the metabolic and iron needs of human infants, and initiating treatment upon diagnosis of anemia reflects clinical practice. Specifically, this analysis determined whether brain maturation would still be compromised at 1 year of age if an anemic infant was treated promptly once diagnosed. The hematology and iron status of 41 infant rhesus monkeys was screened at 2-month intervals. Fifteen became ID; 12 met clinical criteria for anemia and were administered iron dextran and B vitamins for 1-2 months. MRI scans were acquired at 1 year. The volumetric and diffusion tensor imaging (DTI) measures from the ID infants were compared with monkeys who remained continuously iron sufficient (IS). A prior history of ID was associated with smaller total brain volumes, driven primarily by significantly less total gray matter (GM) and smaller GM volumes in several cortical regions. At the macrostructual level, the effect on white matter volumes (WM) was not as overt. However, DTI analyses of WM microstructure indicated two later-maturating anterior tracts were negatively affected. The findings reaffirm the importance of iron for normal brain development. Given that brain differences were still evident even after iron treatment and following recovery of iron-dependent hematological indices, the results highlight the importance of early detection and preemptive supplementation to limit the neural consequences of ID.

Genome-Wide Association Analysis of Neonatal White Matter Microstructure

A better understanding of genetic influences on early white matter development could significantly advance our understanding of neurological and psychiatric conditions characterized by altered integrity of axonal pathways. We conducted a genome-wide association study (GWAS) of diffusion tensor imaging (DTI) phenotypes in 471 neonates. We used a hierarchical functional principal regression model (HFPRM) to perform joint analysis of 44 fiber bundles. HFPRM revealed a latent measure of white matter microstructure that explained approximately 50% of variation in our tractography-based measures and accounted for a large proportion of heritable variation in each individual bundle. An intronic SNP in PSMF1 on chromosome 20 exceeded the conventional GWAS threshold of 5 x 10-8 (p = 4.61 x 10-8). Additional loci nearing genome-wide significance were located near genes with known roles in axon growth and guidance, fasciculation, and myelination.

White Matter Development from Birth to 6 Years of Age: A Longitudinal Study

Human white matter development in the first years of life is rapid, setting the foundation for later development. Microstructural properties of white matter are linked to many behavioral and psychiatric outcomes; however, little is known about when in development individual differences in white matter microstructure are established. The aim of the current study is to characterize longitudinal development of white matter microstructure from birth through 6 years to determine when in development individual differences are established. Two hundred and twenty-four children underwent diffusion-weighted imaging after birth and at 1, 2, 4, and 6 years. Diffusion tensor imaging data were computed for 20 white matter tracts (9 left-right corresponding tracts and 2 commissural tracts), with tract-based measures of fractional anisotropy and axial and radial diffusivity. Microstructural maturation between birth and 1 year are much greater than subsequent changes. Further, by 1 year, individual differences in tract average values are consistently predictive of the respective 6-year values, explaining, on average, 40% of the variance in 6-year microstructure. Results provide further evidence of the importance of the first year of life with regard to white matter development, with potential implications for informing early intervention efforts that target specific sensitive periods.

Trajectories from Distribution-valued Functional Curves: A Unified Wasserstein Framework★

Temporal changes in medical images are often evaluated along a parametrized function that represents a structure of interest (e.g. white matter tracts). By attributing samples along these functions with distributions of image properties in the local neighborhood, we create distribution-valued signatures for these functions. We propose a novel and comprehensive framework which models their temporal evolution trajectories. This is achieved under the unifying scheme of Wasserstein distance metric. The regression problem is formulated as a constrained optimization problem and solved using an alternating projection algorithm. The solution simultaneously preserves the functional characteristics of the curve, models the temporal change in distribution profiles and forces the estimated distributions to be valid. Hypothesis testing is applied in two ways using Wasserstein based test statistics. Validation is presented on synthetic data. Detection of delayed growth is shown on DTI tracts, for a pediatric subject with respect to a healthy population of infants.

Modeling the Mental Lexicon as Part of Long-Term and Working Memory and Simulating Lexical Access in a Naming Task Including Semantic and Phonological Cues

BACKGROUND

To produce and understand words, humans access the mental lexicon. From a functional perspective, the long-term memory component of the mental lexicon is comprised of three levels: the concept level, the lemma level, and the phonological level. At each level, different kinds of word information are stored. Semantic as well as phonological cues can help to facilitate word access during a naming task, especially when neural dysfunctions are present. The processing corresponding to word access occurs in specific parts of working memory. Neural models for simulating speech processing help to uncover the complex relationships that exist between neural dysfunctions and corresponding behavioral patterns.

METHODS

The Neural Engineering Framework (NEF) and the Semantic Pointer Architecture (SPA) are used to develop a quantitative neural model of the mental lexicon and its access during speech processing. By simulating a picture-naming task (WWT 6-10), the influence of cues is investigated by introducing neural dysfunctions within the neural model at different levels of the mental lexicon.

RESULTS

First, the neural model is able to simulate the test behavior for normal children that exhibit no lexical dysfunction. Second, the model shows worse results in test performance as larger degrees of dysfunction are introduced. Third, if the severity of dysfunction is not too high, phonological and semantic cues are observed to lead to an increase in the number of correctly named words. Phonological cues are observed to be more effective than semantic cues.

CONCLUSION

Our simulation results are in line with human experimental data. Specifically, phonological cues seem not only to activate phonologically similar items within the phonological level. Moreover, phonological cues support higher-level processing during access of the mental lexicon. Thus, the neural model introduced in this paper offers a promising approach to modeling the mental lexicon, and to incorporating the mental lexicon into a complex model of language processing.

Sex differences associated with corpus callosum development in human infants: A longitudinal multimodal imaging study

The corpus callosum (CC) is the largest connective pathway in the human brain, linking cerebral hemispheres. There is longstanding debate in the scientific literature whether sex differences are evident in this structure, with many studies indicating the structure is larger in females. However, there are few data pertaining to this issue in infancy, during which time the most rapid developmental changes to the CC occur. In this study, we examined longitudinal brain imaging data collected from 104 infants at ages 6, 12, and 24 months. We identified sex differences in brain-size adjusted CC area and thickness characterized by a steeper rate of growth in males versus females from ages 6-24 months. In contrast to studies of older children and adults, CC size was larger for male compared to female infants. Based on diffusion tensor imaging data, we found that CC thickness is significantly associated with underlying microstructural organization. However, we observed no sex differences in the association between microstructure and thickness, suggesting that the role of factors such as axon density and/or myelination in determining CC size is generally equivalent between sexes. Finally, we found that CC length was negatively associated with nonverbal ability among females.

Neonatal White Matter Maturation Is Associated With Infant Language Development

BACKGROUND

While neonates have no sophisticated language skills, the neural basis for acquiring this function is assumed to already be present at birth. Receptive language is measurable by 6 months of age and meaningful speech production by 10-18 months of age. Fiber tracts supporting language processing include the corpus callosum (CC), which plays a key role in the hemispheric lateralization of language; the left arcuate fasciculus (AF), which is associated with syntactic processing; and the right AF, which plays a role in prosody and semantics. We examined if neonatal maturation of these fiber tracts is associated with receptive language development at 12 months of age.

METHODS

Diffusion-weighted imaging (DWI) was performed in 86 infants at 26.6 ± 12.2 days post-birth. Receptive language was assessed via the MacArthur-Bates Communicative Development Inventory at 12 months of age. Tract-based fractional anisotropy (FA) was determined using the NA-MIC atlas-based fiber analysis toolkit. Associations between neonatal regional FA, adjusted for gestational age at birth and age at scan, and language development at 12 months of age were tested using ANOVA models.

RESULTS

After multiple comparisons correction, higher neonatal FA was positively associated with receptive language at 12 months of age within the genu (p < 0.001), rostrum (p < 0.001), and tapetum (p < 0.001) of the CC and the left fronto-parietal AF (p = 0.008). No significant clusters were found in the right AF.

CONCLUSION

Microstructural development of the CC and the AF in the newborn is associated with receptive language at 12 months of age, demonstrating that interindividual variation in white matter microstructure is relevant for later language development, and indicating that the neural foundation for language processing is laid well ahead of the majority of language acquisition. This suggests that some origins of impaired language development may lie in the intrauterine and potentially neonatal period of life. Understanding how interindividual differences in neonatal brain maturity relate to the acquisition of function, particularly during early development when the brain is in an unparalleled window of plasticity, is key to identifying opportunities for harnessing neuroplasticity in health and disease.

White matter as a monitoring biomarker for neurodevelopmental disorder intervention studies

BACKGROUND

Early intervention is a valuable tool to support the development of toddlers with neurodevelopmental disorders. With recent research advances in early identification that allow for pre-symptomatic detection of autism in infancy, scientists are looking forward to intervention during infancy. These advances may be supported by the identification of biologically based treatment and outcome measures that are sensitive and dimensional. The purpose of this review is to evaluate white matter neurodevelopment as a monitoring biomarker for early treatment of neurodevelopmental disorders. Fragile X syndrome (FXS) and autism spectrum disorder (ASD) as used as exemplars. White matter has unique neurobiology, including a prolonged period of dynamic development. This developmental pattern may make white matter especially responsive to treatment. White matter develops aberrantly in children with ASD and FXS. Histologic studies in rodents have provided targets for FXS pharmacological intervention. However, pharmaceutical clinical trials in humans failed to garner positive clinical results. In this article, we argue that the use of neurobiological monitoring biomarkers may overcome some of these limitations, as they are objective, not susceptible to placebo effects, and are dimensional in nature.

SHORT CONCLUSION

As the field moves towards earlier detection and early intervention for neurodevelopmental disorders, we encourage scientists to consider the advantages of using neurobiological features as monitoring biomarkers.

Anomalies in uncinate fasciculus development and social defects in preschoolers with autism spectrum disorder

BACKGROUND

Individuals with autism spectrum disorder (ASD) have social interaction deficits and difficulties in emotional regulation. The neural substrates for these socio-affective deficits are not yet clear, but one potential candidate is maldevelopment of the uncinate fasciculus (UF), a white matter tract thought to be involved in socio-affective processing. However, the developmental trajectory of the UF in young children with social interaction deficits has not been examined. The present study was designed to describe the developmental growth trajectory of the UF and the relationships between UF development and social deficits in ASD.

METHODS

Eigenvalues of the UF were measured by diffusion tensor imaging (DTI)-based tractography in 37 children with ASD and 27 matched 2-3-year-old subjects with developmental delay (DD) at baseline (time 1) and at 2-year follow-up (time 2). Growth rates of the UF were compared between groups and associations with social deficit scores according to the Autism Diagnostic Interview-Revised (ADI-R) analyzed by Pearson's correlations.

RESULTS

At time 1, axial diffusivity (AD) of the left UF was significantly larger in the ASD group than the DD group. At time 2, left UF fractional anisotropy (FA) was significantly higher and radial diffusivity (RD) significantly lower in the ASD group than the DD group. The rate of UF growth during this 2-year interval was faster in children with ASD than DD. Significant negative correlations were found between the rise in ADI-R social deficit measures and both right UF RD and left UF mean diffusivity (MD).

CONCLUSIONS

Young children with ASD demonstrate UF overgrowth during the 2-year development period between 2 and 3 and 4-5 years of age, and this white matter abnormality is directly associated with the progression of social deficits.

TRIAL REGISTRATION

World Health Organization class I registered international clinical trial platform, ChiCTR-ROC-17012877.

TRActs constrained by UnderLying INfant anatomy (TRACULInA): An automated probabilistic tractography tool with anatomical priors for use in the newborn brain

The ongoing myelination of white-matter fiber bundles plays a significant role in brain development. However, reliable and consistent identification of these bundles from infant brain MRIs is often challenging due to inherently low diffusion anisotropy, as well as motion and other artifacts. In this paper we introduce a new tool for automated probabilistic tractography specifically designed for newborn infants. Our tool incorporates prior information about the anatomical neighborhood of white-matter pathways from a training data set. In our experiments, we evaluate this tool on data from both full-term and prematurely born infants and demonstrate that it can reconstruct known white-matter tracts in both groups robustly, even in the presence of differences between the training set and study subjects. Additionally, we evaluate it on a publicly available large data set of healthy term infants (UNC Early Brain Development Program). This paves the way for performing a host of sophisticated analyses in newborns that we have previously implemented for the adult brain, such as pointwise analysis along tracts and longitudinal analysis, in both health and disease.

Disentangling the effects of early caregiving experience and heritable factors on brain white matter development in rhesus monkeys

Early social experiences, particularly maternal care, shape behavioral and physiological development in primates. Thus, it is not surprising that adverse caregiving, such as child maltreatment leads to a vast array of poor developmental outcomes, including increased risk for psychopathology across the lifespan. Studies of the underlying neurobiology of this risk have identified structural and functional alterations in cortico-limbic brain circuits that seem particularly sensitive to these early adverse experiences and are associated with anxiety and affective disorders. However, it is not understood how these neurobiological alterations unfold during development as it is very difficult to study these early phases in humans, where the effects of maltreatment experience cannot be disentangled from heritable traits. The current study examined the specific effects of experience ("nurture") versus heritable factors ("nature") on the development of brain white matter (WM) tracts with putative roles in socioemotional behavior in primates from birth through the juvenile period. For this we used a randomized crossfostering experimental design in a naturalistic rhesus monkey model of infant maltreatment, where infant monkeys were randomly assigned at birth to either a mother with a history of maltreating her infants, or a competent mother. Using a longitudinal diffusion tensor imaging (DTI) atlas-based tract-profile approach we identified widespread, but also specific, maturational changes on major brain tracts, as well as alterations in a measure of WM integrity (fractional anisotropy, FA) in the middle longitudinal fasciculus (MdLF) and the inferior longitudinal fasciculus (ILF), of maltreated animals, suggesting decreased structural integrity in these tracts due to early adverse experience. Exploratory voxelwise analyses confirmed the tract-based approach, finding additional effects of early adversity, biological mother, social dominance rank, and sex in other WM tracts. These results suggest tract-specific effects of postnatal maternal care experience versus heritable or biological factors on primate WM microstructural development. Further studies are needed to determine the specific behavioral outcomes and biological mechanisms associated with these alterations in WM integrity.

White matter development in infants at risk for schizophrenia

BACKGROUND

Schizophrenia is considered a neurodevelopmental disorder with a pathophysiology that likely begins long before the onset of clinical symptoms. White matter abnormalities have been observed in schizophrenia and we hypothesized that the first 2 years of life is a period in which white matter abnormalities associated with schizophrenia risk may emerge.

METHODS

38 infants at high risk for schizophrenia and 202 healthy controls underwent diffusion tensor MRIs after birth and at 1 and 2 years of age. Quantitative tractography was used to determine diffusion properties (fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD)) of 18 white matter tracts and a general linear model was used to analyze group differences at each age.

RESULTS

Adjusting gestational age at birth, postnatal age at MRI, gender, MRI scanner type, and maternal education, neonates at high risk had significantly lower FA (p = 0.02) and AD (p = 0.03) in the superior segment of the left cingulate, and higher RD in the hippocampal segment of the left cingulate (p = 0.04). High risk one year olds had significantly lower FA (p < 0.01) and AD (p = 0.02) in the hippocampal segment of the left cingulate. High risk two year olds had significantly lower FA in the left prefrontal cortico-thalamic tract (p = 0.04) and higher RD in the right uncinate fasciculus (p = 0.04). None of the tract differences remained significant after correction for multiple comparisons.

CONCLUSIONS

There is evidence of abnormal white matter development in young children at risk for schizophrenia, especially in the hippocampal segment of left cingulum. These results support the neurodevelopmental theory of schizophrenia and indicate that impaired white matter may be present in early childhood.

Maternal Interleukin-6 concentration during pregnancy is associated with variation in frontolimbic white matter and cognitive development in early life

Maternal inflammation during pregnancy can alter the trajectory of fetal brain development and increase risk for offspring psychiatric disorders. However, the majority of relevant research to date has been conducted in animal models. Here, in humans, we focus on the structural connectivity of frontolimbic circuitry as it is both critical for socioemotional and cognitive development, and commonly altered in a range of psychiatric disorders associated with intrauterine inflammation. Specifically, we test the hypothesis that elevated maternal concentration of the proinflammatory cytokine interleukin-6 (IL-6) during pregnancy will be associated with variation in microstructural properties of this circuitry in the neonatal period and across the first year of life. Pregnant mothers were recruited in early pregnancy and maternal blood samples were obtained for assessment of maternal IL-6 concentrations in early (12.6 ± 2.8 weeks [S.D.]), mid (20.4 ± 1.5 weeks [S.D.]) and late (30.3 ± 1.3 weeks [S.D.]) gestation. Offspring brain MRI scans were acquired shortly after birth (N = 86, scan age = 3.7 ± 1.7 weeks [S.D.]) and again at 12-mo age (N = 32, scan age = 54.0 ± 3.1 weeks [S.D.]). Diffusion Tensor Imaging (DTI) was used to characterize fractional anisotropy (FA) along the left and right uncinate fasciculus (UF), representing the main frontolimbic fiber tract. In N = 30 of the infants with serial MRI data at birth and 12-mo age, cognitive and socioemotional developmental status was characterized using the Bayley Scales of Infant Development. All analyses tested for potentially confounding influences of household income, prepregnancy Body-Mass-Index, obstetric risk, smoking during pregnancy, and infant sex, and outcomes at 12-mo age were additionally adjusted for the quality of the postnatal caregiving environment. Maternal IL-6 concentration (averaged across pregnancy) was prospectively and inversely associated with FA (suggestive of reduced integrity under high inflammatory conditions) in the newborn offspring (bi-lateral, p < 0.01) in the central portion of the UF proximal to the amygdala. Furthermore, maternal IL-6 concentration was positively associated with rate of FA increase across the first year of life (bi-lateral, p < 0.05), resulting in a null association between maternal IL-6 and UF FA at 12-mo age. Maternal IL-6 was also inversely associated with offspring cognition at 12-mo age, and this association was mediated by FA growth across the first year of postnatal life. Findings from the current study support the premise that susceptibility for cognitive impairment and potentially psychiatric disorders may be affected in utero, and that maternal inflammation may constitute an intrauterine condition of particular importance in this context.

Quantitative evaluation of diffusion tensor imaging for clinical management of glioma

Diffusion tensor imaging (DTI), assessing physiological motion of water in vivo, provides macroscopic view of microstructures of white matter in the central nervous system, and such imaging technique had been extensively used for the clinical treatment and research of glioma. This review mainly focuses on illuminating the merits of quantitative evaluation of DTI for glioma management. The content of the article includes DTI's application on tissue characterization, white matter tracts mapping, radiotherapy delineation, post-therapy outcome assessment, and multimodal imaging. At last, we elucidate a synoptic presentation of DTI limitation, which is critical for physicians making DTI-based clinical decisions in glioma management.

Quantitative tract-based white matter heritability in 1- and 2-year-old twins

White matter (WM) microstructure, as determined by diffusion tensor imaging (DTI), is increasingly recognized as an important determinant of cognitive function and is also altered in neuropsychiatric disorders. Little is known about genetic and environmental influences on WM microstructure, especially in early childhood, an important period for cognitive development and risk for psychiatric disorders. We studied the heritability of DTI parameters, fractional anisotropy (FA), radial diffusivity (RD) and axial diffusivity (AD) along 34 tracts, including 10 bilateral fiber pathways and the respective subdivision, using quantitative tractography in a longitudinal sample of healthy children at 1 year (N = 215) and 2 years (N = 165) of age. We found that heritabilities for whole brain AD, RD, and FA were 0.48, 0.69, and 0.72 at age 1, and 0.59, 0.77, and 0.76 at age 2 and that mean heritabilities of tract-averaged AD, RD, and FA for individual bundles were moderate (over 0.4). However, the heritability of DTI change between 1 and 2 years of age was not significant for most tracts. We also demonstrated that point-wise heritability tended to be significant in the central portions of the tracts and was generally spatially consistent at ages 1 and 2 years. These results, especially when compared to heritability patterns in neonates, indicate that the heritability of WM microstructure is dynamic in early childhood and likely reflect heterogeneous maturation of WM tracts and differential genetic and environmental influences on maturation patterns.

White matter microstructural development and cognitive ability in the first 2 years of life

White matter (WM) integrity has been related to cognitive ability in adults and children, but it remains largely unknown how WM maturation in early life supports emergent cognition. The associations between tract-based measures of fractional anisotropy (FA) and axial and radial diffusivity (AD, RD) shortly after birth, at age 1, and at age 2 and cognitive measures at 1 and 2 years were investigated in 447 healthy infants. We found that generally higher FA and lower AD and RD across many WM tracts in the first year of life were associated with better performance on measures of general cognitive ability, motor, language, and visual reception skills at ages 1 and 2, suggesting an important role for the overall organization, myelination, and microstructural properties of fiber pathways in emergent cognition. RD in particular was consistently related to ability, and protracted development of RD from ages 1 to 2 years in several tracts was associated with higher cognitive scores and better language performance, suggesting prolonged plasticity may confer cognitive benefits during the second year of life. However, we also found that cognition at age 2 was weakly associated with WM properties across infancy in comparison to child and demographic factors including gestational age and maternal education. Our findings suggest that early postnatal WM integrity across the brain is important for infant cognition, though its role in cognitive development should be considered alongside child and demographic factors.

Development of White Matter Circuitry in Infants With Fragile X Syndrome

IMPORTANCE

Fragile X syndrome (FXS) is a genetic neurodevelopmental disorder and the most common inherited cause of intellectual disability in males. However, there are no published data on brain development in children with FXS during infancy.

OBJECTIVE

To characterize the development of white matter at ages 6, 12, and 24 months in infants with FXS compared with that of typically developing controls.

DESIGN, SETTING, AND PARTICIPANTS

Longitudinal behavioral and brain imaging data were collected at 1 or more time points from 27 infants with FXS and 73 typically developing controls between August 1, 2008, and June 14, 2016, at 2 academic medical centers. Infants in the control group had no first- or second-degree relatives with intellectual or psychiatric disorders, including FXS and autism spectrum disorder.

MAIN OUTCOMES AND MEASURES

Nineteen major white matter pathways were defined in common atlas space based on anatomically informed methods. Diffusion parameters, including fractional anisotropy, were compared between groups using linear mixed effects modeling. Fiber pathways showing group differences were subsequently examined in association with direct measures of verbal and nonverbal development.

RESULTS

There were significant differences in the development of 12 of 19 fiber tracts between the 27 infants with FXS (22 boys and 5 girls) and the 73 infants in the control group (46 boys and 27 girls), with lower fractional anisotropy in bilateral subcortical-frontal, occipital-temporal, temporal-frontal, and cerebellar-thalamic pathways, as well as 4 of 6 subdivisions of the corpus callosum. For all 12 of these pathways, there were significant main effects between groups but not for the interaction of age × group, indicating that lower fractional anisotropy was present and stable from age 6 months in infants with FXS. Lower fractional anisotropy values in the uncinate fasciculi were correlated with lower nonverbal developmental quotient in the FXS group (left uncinate, F = 10.06; false discovery rate-corrected P = .03; right uncinate, F = 21.8; P = .004).

CONCLUSIONS AND RELEVANCE

The results substantiate in human infants the essential role of fragile X gene expression in the early development of white matter. The findings also suggest that the neurodevelopmental effects of FXS are well established at 6 months of age.

TRAFIC: Fiber Tract Classification Using Deep Learning

We present TRAFIC, a fully automated tool for the labeling and classification of brain fiber tracts. TRAFIC classifies new fibers using a neural network trained using shape features computed from previously traced and manually corrected fiber tracts. It is independent from a DTI Atlas as it is applied to already traced fibers. This work is motivated by medical applications where the process of extracting fibers from a DTI atlas, or classifying fibers manually is time consuming and requires knowledge about brain anatomy. With this new approach we were able to classify traced fiber tracts obtaining encouraging results. In this report we will present in detail the methods used and the results achieved with our approach.

HFPRM: Hierarchical Functional Principal Regression Model for Diffusion Tensor Image Bundle Statistics

Diffusion-weighted magnetic resonance imaging (MRI) provides a unique approach to understand the geometric structure of brain fiber bundles and to delineate the diffusion properties across subjects and time. It can be used to identify structural connectivity abnormalities and helps to diagnose brain-related disorders. The aim of this paper is to develop a novel, robust, and efficient dimensional reduction and regression framework, called hierarchical functional principal regression model (HFPRM), to effectively correlate high-dimensional fiber bundle statistics with a set of predictors of interest, such as age, diagnosis status, and genetic markers. The three key novelties of HFPRM include the simultaneous analysis of a large number of fiber bundles, the disentanglement of global and individual latent factors that characterizes between-tract correlation patterns, and a bi-level analysis on the predictor effects. Simulations are conducted to evaluate the finite sample performance of HFPRM. We have also applied HFPRM to a genome-wide association study to explore important genetic variants in neonatal white matter development.

Decreased Axon Caliber Underlies Loss of Fiber Tract Integrity, Disproportional Reductions in White Matter Volume, and Microcephaly in Angelman Syndrome Model Mice

Angelman syndrome (AS) is a debilitating neurodevelopmental disorder caused by loss of function of the maternally inherited UBE3A allele. It is currently unclear how the consequences of this genetic insult unfold to impair neurodevelopment. We reasoned that by elucidating the basis of microcephaly in AS, a highly penetrant syndromic feature with early postnatal onset, we would gain new insights into the mechanisms by which maternal UBE3A loss derails neurotypical brain growth and function. Detailed anatomical analysis of both male and female maternal Ube3a-null mice reveals that microcephaly in the AS mouse model is primarily driven by deficits in the growth of white matter tracts, which by adulthood are characterized by densely packed axons of disproportionately small caliber. Our results implicate impaired axon growth in the pathogenesis of AS and identify noninvasive structural neuroimaging as a potentially valuable tool for gauging therapeutic efficacy in the disorder.SIGNIFICANCE STATEMENT People who maternally inherit a deletion or nonfunctional copy of the UBE3A gene develop Angelman syndrome (AS), a severe neurodevelopmental disorder. To better understand how loss of maternal UBE3A function derails brain development, we analyzed brain structure in a maternal Ube3a knock-out mouse model of AS. We report that the volume of white matter (WM) is disproportionately reduced in AS mice, indicating that deficits in WM development are a major factor underlying impaired brain growth and microcephaly in the disorder. Notably, we find that axons within the WM pathways of AS model mice are abnormally small in caliber. This defect is associated with slowed nerve conduction, which could contribute to behavioral deficits in AS, including motor dysfunction.

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.

Understanding Brain Reorganization in Infants With Perinatal Stroke Through Neuroexcitability and Neuroimaging

PURPOSE

The primary aim of this proposed study is to evaluate brain reorganization patterns in infants with perinatal stroke between 3 and 5 months of age using transcranial magnetic stimulation and magnetic resonance imaging, with the addition of the General Movements Assessment. A secondary aim is to demonstrate feasibility and safety of infant-appropriate brain assessment protocols.

METHODS

Ten infants with perinatal stroke will be enrolled. In this exploratory study, infants will first receive magnetic resonance imaging scanning during natural sleep to examine their corticospinal tract integrity. Infants will then receive transcranial magnetic stimulation to assess their corticomotor excitability. A General Movements Assessment video of at least 5 minutes will also be recorded.

DISCUSSION

Study results will enhance our understanding of brain reorganization in infants with perinatal stroke. We expect these results will also guide the development of early interventions designed to mitigate maladaptive neuroplastic changes and improve long-term motor outcomes.

Neural circuitry at age 6 months associated with later repetitive behavior and sensory responsiveness in autism

Background

Restricted and repetitive behaviors are defining features of autism spectrum disorder (ASD). Under revised diagnostic criteria for ASD, this behavioral domain now includes atypical responses to sensory stimuli. To date, little is known about the neural circuitry underlying these features of ASD early in life.

Methods

Longitudinal diffusion tensor imaging data were collected from 217 infants at high familial risk for ASD. Forty-four of these infants were diagnosed with ASD at age 2. Targeted cortical, cerebellar, and striatal white matter pathways were defined and measured at ages 6, 12, and 24 months. Dependent variables included the Repetitive Behavior Scale-Revised and the Sensory Experiences Questionnaire.

Results

Among children diagnosed with ASD, repetitive behaviors and sensory response patterns were strongly correlated, even when accounting for developmental level or social impairment. Longitudinal analyses indicated that the genu and cerebellar pathways were significantly associated with both repetitive behaviors and sensory responsiveness but not social deficits. At age 6 months, fractional anisotropy in the genu significantly predicted repetitive behaviors and sensory responsiveness at age 2. Cerebellar pathways significantly predicted later sensory responsiveness. Exploratory analyses suggested a possible disordinal interaction based on diagnostic status for the association between fractional anisotropy and repetitive behavior.

Conclusions

Our findings suggest that restricted and repetitive behaviors contributing to a diagnosis of ASD at age 2 years are associated with structural properties of callosal and cerebellar white matter pathways measured during infancy and toddlerhood. We further identified that repetitive behaviors and unusual sensory response patterns co-occur and share common brain-behavior relationships. These results were strikingly specific given the absence of association between targeted pathways and social deficits.

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-017-0126-z) contains supplementary material, which is available to authorized users.

The UNC-Wisconsin Rhesus Macaque Neurodevelopment Database: A Structural MRI and DTI Database of Early Postnatal Development

Rhesus macaques are commonly used as a translational animal model in neuroimaging and neurodevelopmental research. In this report, we present longitudinal data from both structural and diffusion MRI images generated on a cohort of 34 typically developing monkeys from 2 weeks to 36 months of age. All images have been manually skull stripped and are being made freely available via an online repository for use by the research community.

White Matter Fiber-based Analysis of T1w/T2w Ratio Map

PURPOSE

To develop, test, evaluate and apply a novel tool for the white matter fiber-based analysis of T1w/T2w ratio maps quantifying myelin content.

BACKGROUND

The cerebral white matter in the human brain develops from a mostly non-myelinated state to a nearly fully mature white matter myelination within the first few years of life. High resolution T1w/T2w ratio maps are believed to be effective in quantitatively estimating myelin content on a voxel-wise basis. We propose the use of a fiber-tract-based analysis of such T1w/T2w ratio data, as it allows us to separate fiber bundles that a common regional analysis imprecisely groups together, and to associate effects to specific tracts rather than large, broad regions.

METHODS

We developed an intuitive, open source tool to facilitate such fiber-based studies of T1w/T2w ratio maps. Via its Graphical User Interface (GUI) the tool is accessible to non-technical users. The framework uses calibrated T1w/T2w ratio maps and a prior fiber atlas as an input to generate profiles of T1w/T2w values. The resulting fiber profiles are used in a statistical analysis that performs along-tract functional statistical analysis. We applied this approach to a preliminary study of early brain development in neonates.

RESULTS

We developed an open-source tool for the fiber based analysis of T1w/T2w ratio maps and tested it in a study of brain development.

UNC-Emory Infant Atlases for Macaque Brain Image Analysis: Postnatal Brain Development through 12 Months

Computational anatomical atlases have shown to be of immense value in neuroimaging as they provide age appropriate reference spaces alongside ancillary anatomical information for automated analysis such as subcortical structural definitions, cortical parcellations or white fiber tract regions. Standard workflows in neuroimaging necessitate such atlases to be appropriately selected for the subject population of interest. This is especially of importance in early postnatal brain development, where rapid changes in brain shape and appearance render neuroimaging workflows sensitive to the appropriate atlas choice. We present here a set of novel computation atlases for structural MRI and Diffusion Tensor Imaging as crucial resource for the analysis of MRI data from non-human primate rhesus monkey (Macaca mulatta) data in early postnatal brain development. Forty socially-housed infant macaques were scanned longitudinally at ages 2 weeks, 3, 6, and 12 months in order to create cross-sectional structural and DTI atlases via unbiased atlas building at each of these ages. Probabilistic spatial prior definitions for the major tissue classes were trained on each atlas with expert manual segmentations. In this article we present the development and use of these atlases with publicly available tools, as well as the atlases themselves, which are publicly disseminated to the scientific community.

Common and heritable components of white matter microstructure predict cognitive function at 1 and 2 y

Previous studies indicate that the microstructure of individual white matter (WM) tracts is related to cognitive function. More recent studies indicate that the microstructure of individual tracts is highly correlated and that a property common across WM is related to overall cognitive function in adults. However, little is known about whether these common WM properties exist in early childhood development or how they are related to cognitive development. In this study, we used diffusion tensor imaging (DTI) to investigate common underlying factors in 12 fiber tracts, their relationship with cognitive function, and their heritability in a longitudinal sample of healthy children at birth (n = 535), 1 y (n = 322), and 2 y (n = 244) of age. Our data show that, in neonates, there is a highly significant correlation between major WM tracts that decreases from birth to 2 y of age. Over the same period, the factor structure increases in complexity, from one factor at birth to three factors at age 2 y, which explain 50% of variance. The identified common factors of DTI metrics in each age group are significantly correlated with general cognitive scores and predict cognitive ability in later childhood. These factors are moderately heritable. These findings illustrate the anatomical differentiation of WM fiber from birth to 2 y of age that correlate with cognitive development. Our results also suggest that the common factor approach is an informative way to study WM development and its relationship with cognition and is a useful approach for future imaging genetic studies.

A novel maturation index based on neonatal diffusion tensor imaging reflects typical perinatal white matter development in humans

Human birth presents an abrupt transition from intrauterine to extrauterine life. Here we introduce a novel Maturation Index (MI) that considers the relative importance of gestational age at birth and postnatal age at scan in a General Linear Model. The MI is then applied to Diffusion Tensor Imaging (DTI) in newborns for characterizing typical white matter development in neonates. DTI was performed cross-sectionally in 47 neonates (gestational age at birth=39.1±1.6 weeks [GA], postnatal age at scan=25.5±12.2days [SA]). Radial diffusivity (RD), axial diffusivity (AD) and fractional anisotropy (FA) along 27 white matter fiber tracts were considered. The MI was used to characterize inflection in maturation at the time of birth using GLM estimated rates of change before and after birth. It is proposed that the sign (positive versus negative) of MI reflects the period of greatest maturation rate. Two general patterns emerged from the MI analysis. First, RD and AD (but not FA) had positive MI on average across the whole brain (average MI_AD=0.31±0.42, average MI_RD=0.22±0.34). Second, significant regions of negative MI in RD and FA (but not AD) were observed in the inferior corticospinal regions, areas known to myelinate early. Observations using the proposed method are consistent with proposed models of the white matter maturation process in which pre-myelination is described by changes in AD and RD due to oligodendrocyte proliferation while true myelination is characterized by changes in RD and FA due to myelin formation.

An In vivo Multi-Modal Structural Template for Neonatal Piglets Using High Angular Resolution and Population-Based Whole-Brain Tractography

An increasing number of applications use the postnatal piglet model in neuroimaging studies, however, these are based primarily on T1 weighted image templates. There is a growing need for a multimodal structural brain template for a comprehensive depiction of the piglet brain, particularly given the growing applications of diffusion weighted imaging for characterizing tissue microstructures and white matter organization. In this study, we present the first multimodal piglet structural brain template which includes a T1 weighted image with tissue segmentation probability maps, diffusion weighted metric templates with multiple diffusivity maps, and population-based whole-brain fiber tracts for postnatal piglets. These maps provide information about the integrity of white matter that is not available in T1 images alone. The availability of this diffusion weighted metric template will contribute to the structural imaging analysis of the postnatal piglet brain, especially models that are designed for the study of white matter diseases. Furthermore, the population-based whole-brain fiber tracts permit researchers to visualize the white matter connections in the piglet brain across subjects, guiding the delineation of a specific white matter region for structural analysis where current diffusion data is lacking. Researchers are able to augment the tracts by merging tracts from their own data to the population-based fiber tracts and thus improve the confidence of the population-wise fiber distribution.

Antenatal depression, treatment with selective serotonin reuptake inhibitors, and neonatal brain structure: A propensity-matched cohort study

The aim of this propensity-matched cohort study was to evaluate the impact of prenatal SSRI exposure and a history of maternal depression on neonatal brain volumes and white matter microstructure. SSRI-exposed neonates (n=27) were matched to children of mothers with no history of depression or SSRI use (n=54). Additionally, neonates of mothers with a history of depression, but no prenatal SSRI exposure (n=41), were matched to children of mothers with no history of depression or SSRI use (n=82). Structural magnetic resonance imaging and diffusion weighted imaging scans were acquired with a 3T Siemens Allegra scanner. Global tissue volumes were characterized using an automatic, atlas-moderated expectation maximization segmentation tool. Local differences in gray matter volumes were examined using deformation-based morphometry. Quantitative tractography was performed using an adaptation of the UNC-Utah NA-MIC DTI framework. SSRI-exposed neonates exhibited widespread changes in white matter microstructure compared to matched controls. Children exposed to a history of maternal depression but no SSRIs showed no significant differences in brain development compared to matched controls. No significant differences were found in global or regional tissue volumes. Additional research is needed to clarify whether SSRIs directly alter white matter development or whether this relationship is mediated by depressive symptoms during pregnancy.

A framework for incorporating DTI Atlas Builder registration into Tract-Based Spatial Statistics and a simulated comparison to standard TBSS

Tract-based spatial statistics (TBSS)⁶ is a software pipeline widely employed in comparative analysis of the white matter integrity from diffusion tensor imaging (DTI) datasets. In this study, we seek to evaluate the relationship between different methods of atlas registration for use with TBSS and different measurements of DTI (fractional anisotropy, FA, axial diffusivity, AD, radial diffusivity, RD, and medial diffusivity, MD). To do so, we have developed a novel tool that builds on existing diffusion atlas building software, integrating it into an adapted version of TBSS called DAB-TBSS (DTI Atlas Builder-Tract-Based Spatial Statistics) by using the advanced registration offered in DTI Atlas Builder⁷. To compare the effectiveness of these two versions of TBSS, we also propose a framework for simulating population differences for diffusion tensor imaging data, providing a more substantive means of empirically comparing DTI group analysis programs such as TBSS. In this study, we used 33 diffusion tensor imaging datasets and simulated group-wise changes in this data by increasing, in three different simulations, the principal eigenvalue (directly altering AD), the second and third eigenvalues (RD), and all three eigenvalues (MD) in the genu, the right uncinate fasciculus, and the left IFO. Additionally, we assessed the benefits of comparing the tensors directly using a functional analysis of diffusion tensor tract statistics (FADTTS¹⁰). Our results indicate comparable levels of FA-based detection between DAB-TBSS and TBSS, with standard TBSS registration reporting a higher rate of false positives in other measurements of DTI. Within the simulated changes investigated here, this study suggests that the use of DTI Atlas Builder's registration enhances TBSS group-based studies.

Splenium development and early spoken language in human infants

The association between developmental trajectories of language-related white matter fiber pathways from 6 to 24 months of age and individual differences in language production at 24 months of age was investigated. The splenium of the corpus callosum, a fiber pathway projecting through the posterior hub of the default mode network to occipital visual areas, was examined as well as pathways implicated in language function in the mature brain, including the arcuate fasciculi, uncinate fasciculi, and inferior longitudinal fasciculi. The hypothesis that the development of neural circuitry supporting domain-general orienting skills would relate to later language performance was tested in a large sample of typically developing infants. The present study included 77 infants with diffusion weighted MRI scans at 6, 12 and 24 months and language assessment at 24 months. The rate of change in splenium development varied significantly as a function of language production, such that children with greater change in fractional anisotropy (FA) from 6 to 24 months produced more words at 24 months. Contrary to findings from older children and adults, significant associations between language production and FA in the arcuate, uncinate, or left inferior longitudinal fasciculi were not observed. The current study highlights the importance of tracing brain development trajectories from infancy to fully elucidate emerging brain-behavior associations while also emphasizing the role of the splenium as a key node in the structural network that supports the acquisition of spoken language.

Altered corpus callosum morphology associated with autism over the first 2 years of life

Numerous brain imaging studies indicate that the corpus callosum is smaller in older children and adults with autism spectrum disorder. However, there are no published studies examining the morphological development of this connective pathway in infants at-risk for the disorder. Magnetic resonance imaging data were collected from 270 infants at high familial risk for autism spectrum disorder and 108 low-risk controls at 6, 12 and 24 months of age, with 83% of infants contributing two or more data points. Fifty-seven children met criteria for ASD based on clinical-best estimate diagnosis at age 2 years. Corpora callosa were measured for area, length and thickness by automated segmentation. We found significantly increased corpus callosum area and thickness in children with autism spectrum disorder starting at 6 months of age. These differences were particularly robust in the anterior corpus callosum at the 6 and 12 month time points. Regression analysis indicated that radial diffusivity in this region, measured by diffusion tensor imaging, inversely predicted thickness. Measures of area and thickness in the first year of life were correlated with repetitive behaviours at age 2 years. In contrast to work from older children and adults, our findings suggest that the corpus callosum may be larger in infants who go on to develop autism spectrum disorder. This result was apparent with or without adjustment for total brain volume. Although we did not see a significant interaction between group and age, cross-sectional data indicated that area and thickness differences diminish by age 2 years. Regression data incorporating diffusion tensor imaging suggest that microstructural properties of callosal white matter, which includes myelination and axon composition, may explain group differences in morphology.

Early Postnatal Myelin Content Estimate of White Matter via T1w/T2w Ratio

PURPOSE

To develop and evaluate a novel processing framework for the relative quantification of myelin content in cerebral white matter (WM) regions from brain MRI data via a computed ratio of T1 to T2 weighted intensity values.

DATA

We employed high resolution (1mm3 isotropic) T1 and T2 weighted MRI from 46 (28 male, 18 female) neonate subjects (typically developing controls) scanned on a Siemens Tim Trio 3T at UC Irvine.

METHODS

We developed a novel, yet relatively straightforward image processing framework for WM myelin content estimation based on earlier work by Glasser et al. We first co-register the structural MRI data to correct for motion. Then, background areas are masked out via a joint T1w and T2 foreground mask computed. Raw T1w/T2w-ratios images are computed next. For purpose of calibration across subjects, we first coarsely segment the fat-rich facial regions via an atlas co-registration. Linear intensity rescaling based on median T1w/T2w-ratio values in those facial regions yields calibrated T1w/T2w-ratio images. Mean values in lobar regions are evaluated using standard statistical analysis to investigate their interaction with age at scan.

RESULTS

Several lobes have strongly positive significant interactions of age at scan with the computed T1w/T2w-ratio. Most regions do not show sex effects. A few regions show no measurable effects of change in myelin content change within the first few weeks of postnatal development, such as cingulate and CC areas, which we attribute to sample size and measurement variability.

CONCLUSIONS

We developed and evaluated a novel way to estimate white matter myelin content for use in studies of brain white matter development.

Quantitative tract-based white matter heritability in twin neonates

Studies in adults indicate that white matter microstructure, assessed with diffusion tensor imaging (DTI), has high heritability. Little is known about genetic and environmental influences on DTI parameters, measured along fiber tracts particularly, in early childhood. In the present study, we report comprehensive heritability data of white matter microstructure fractional anisotropy (FA), radial diffusion (RD), and axial diffusion (AD) along 47 fiber tracts using the quantitative tractography in a large sample of neonatal twins (n=356). We found significant genetic influences in almost all tracts with similar heritabilities for FA, RD, and AD as well as positive relationships between these parameters and heritability. In a single tract analysis, genetic influences along the length of the tract were highly variable. These findings suggest that at birth, there is marked heterogeneity of genetic influences of white matter microstructure within white matter tracts. This study provides a basis for future studies of developmental changes in genetic and environmental influences during early childhood, a period of rapid development that likely plays a major role in individual differences in white matter structure and function.

Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences

Diffusion-weighted imaging (DWI) is known to be prone to artifacts related to motion originating from subject movement, cardiac pulsation, and breathing, but also to mechanical issues such as table vibrations. Given the necessity for rigorous quality control and motion correction, users are often left to use simple heuristics to select correction schemes, which involves simple qualitative viewing of the set of DWI data, or the selection of transformation parameter thresholds for detection of motion outliers. The scientific community offers strong theoretical and experimental work on noise reduction and orientation distribution function (ODF) reconstruction techniques for HARDI data, where post-acquisition motion correction is widely performed, e.g., using the open-source DTIprep software (1), FSL (the FMRIB Software Library) (2), or TORTOISE (3). Nonetheless, effects and consequences of the selection of motion correction schemes on the final analysis, and the eventual risk of introducing confounding factors when comparing populations, are much less known and far beyond simple intuitive guessing. Hence, standard users lack clear guidelines and recommendations in practical settings. This paper reports a comprehensive evaluation framework to systematically assess the outcome of different motion correction choices commonly used by the scientific community on different DWI-derived measures. We make use of human brain HARDI data from a well-controlled motion experiment to simulate various degrees of motion corruption and noise contamination. Choices for correction include exclusion/scrubbing or registration of motion corrupted directions with different choices of interpolation, as well as the option of interpolation of all directions. The comparative evaluation is based on a study of the impact of motion correction using four metrics that quantify (1) similarity of fiber orientation distribution functions (fODFs), (2) deviation of local fiber orientations, (3) global brain connectivity via graph diffusion distance (GDD), and (4) the reproducibility of prominent and anatomically defined fiber tracts. Effects of various motion correction choices are systematically explored and illustrated, leading to a general conclusion of discouraging users from setting ad hoc thresholds on the estimated motion parameters beyond which volumes are claimed to be corrupted.