Surface-based morphometry of the corpus callosum in young children of ages 1-5.

The corpus callosum (CC) is a large white matter fiber bundle in the brain and is involved in various cognitive, sensory, and motor processes. While implicated in various developmental and psychiatric disorders, much is yet to be uncovered about the normal development of this structure, especially in young children. Additionally, while sexual dimorphism has been reported in prior literature, observations have not necessarily been consistent. In this study, we use morphometric measures including surface tensor-based morphometry (TBM) to investigate local changes in the shape of the CC in children between the ages of 12 and 60 months, in intervals of 12 months. We also analyze sex differences in each of these age groups. We observed larger significant clusters in the earlier ages between 12 v 24 m and between 48 v 60 m and localized differences in the anterior region of the body of the CC. Sex differences were most pronounced in the 12 m group. This study adds to the growing literature of work aiming to understand the developing brain and emphasizes the utility of surface TBM as a useful tool for analyzing regional differences in neuroanatomical morphometry.

Widespread, depth-dependent cortical microstructure alterations in pediatric focal epilepsy.

OBJECTIVE: Tissue abnormalities in focal epilepsy may extend beyond the presumed focus. The underlying pathophysiology of these broader changes is unclear, and it is not known whether they result from ongoing disease processes or treatment-related side effects, or whether they emerge earlier. Few studies have focused on the period of onset for most focal epilepsies, childhood. Fewer still have utilized quantitative magnetic resonance imaging (MRI), which may provide a more sensitive and interpretable measure of tissue microstructural change. Here, we aimed to determine common spatial modes of changes in cortical architecture in children with heterogeneous drug-resistant focal epilepsy and, secondarily, whether changes were related to disease severity. METHODS: To assess cortical microstructure, quantitative T1 and T2 relaxometry (qT1 and qT2) was measured in 43 children with drug-resistant focal epilepsy (age range = 4-18 years) and 46 typically developing children (age range = 2-18 years). We assessed depth-dependent qT1 and qT2 values across the neocortex, as well as their gradient of change across cortical depths. We also determined whether global changes seen in group analyses were driven by focal pathologies in individual patients. Finally, as a proof-of-concept, we trained a classifier using qT1 and qT2 gradient maps from patients with radiologically defined abnormalities (MRI positive) and healthy controls, and tested whether this could classify patients without reported radiological abnormalities (MRI negative). RESULTS: We uncovered depth-dependent qT1 and qT2 increases in widespread cortical areas in patients, likely representing microstructural alterations in myelin or gliosis. Changes did not correlate with disease severity measures, suggesting they may represent antecedent neurobiological alterations. Using a classifier trained with MRI-positive patients and controls, sensitivity was 71.4% at 89.4% specificity on held-out MRI-negative patients. SIGNIFICANCE: These findings suggest the presence of a potential imaging endophenotype of focal epilepsy, detectable irrespective of radiologically identified abnormalities.

Comprehensive volumetric phenotyping of the neonatal brain in Down syndrome.

Down syndrome (DS) is the most common genetic cause of intellectual disability with a wide range of neurodevelopmental outcomes. To date, there have been very few in vivo neuroimaging studies of the neonatal brain in DS. In this study we used a cross-sectional sample of 493 preterm- to term-born control neonates from the developing Human Connectome Project to perform normative modeling of regional brain tissue volumes from 32 to 46 weeks postmenstrual age, accounting for sex and age variables. Deviation from the normative mean was quantified in 25 neonates with DS with postnatally confirmed karyotypes from the Early Brain Imaging in DS study. Here, we provide the first comprehensive volumetric phenotyping of the neonatal brain in DS, which is characterized by significantly reduced whole brain, cerebral white matter, and cerebellar volumes; reduced relative frontal and occipital lobar volumes, in contrast with enlarged relative temporal and parietal lobar volumes; enlarged relative deep gray matter volume (particularly the lentiform nuclei); and enlargement of the lateral ventricles, amongst other features. In future, the ability to assess phenotypic severity at the neonatal stage may help guide early interventions and, ultimately, help improve neurodevelopmental outcomes in children with DS.

Development of neonatal brain functional centrality and alterations associated with preterm birth.

Formation of the functional connectome in early life underpins future learning and behavior. However, our understanding of how the functional organization of brain regions into interconnected hubs (centrality) matures in the early postnatal period is limited, especially in response to factors associated with adverse neurodevelopmental outcomes such as preterm birth. We characterized voxel-wise functional centrality (weighted degree) in 366 neonates from the Developing Human Connectome Project. We tested the hypothesis that functional centrality matures with age at scan in term-born babies and is disrupted by preterm birth. Finally, we asked whether neonatal functional centrality predicts general neurodevelopmental outcomes at 18 months. We report an age-related increase in functional centrality predominantly within visual regions and a decrease within the motor and auditory regions in term-born infants. Preterm-born infants scanned at term equivalent age had higher functional centrality predominantly within visual regions and lower measures in motor regions. Functional centrality was not related to outcome at 18 months old. Thus, preterm birth appears to affect functional centrality in regions undergoing substantial development during the perinatal period. Our work raises the question of whether these alterations are adaptive or disruptive and whether they predict neurodevelopmental characteristics that are more subtle or emerge later in life.

Development of human white matter pathways in utero over the second and third trimester.

During the second and third trimesters of human gestation, rapid neurodevelopment is underpinned by fundamental processes including neuronal migration, cellular organization, cortical layering, and myelination. In this time, white matter growth and maturation lay the foundation for an efficient network of structural connections. Detailed knowledge about this developmental trajectory in the healthy human fetal brain is limited, in part, due to the inherent challenges of acquiring high-quality MRI data from this population. Here, we use state-of-the-art high-resolution multishell motion-corrected diffusion-weighted MRI (dMRI), collected as part of the developing Human Connectome Project (dHCP), to characterize the in utero maturation of white matter microstructure in 113 fetuses aged 22 to 37 wk gestation. We define five major white matter bundles and characterize their microstructural features using both traditional diffusion tensor and multishell multitissue models. We found unique maturational trends in thalamocortical fibers compared with association tracts and identified different maturational trends within specific sections of the corpus callosum. While linear maturational increases in fractional anisotropy were seen in the splenium of the corpus callosum, complex nonlinear trends were seen in the majority of other white matter tracts, with an initial decrease in fractional anisotropy in early gestation followed by a later increase. The latter is of particular interest as it differs markedly from the trends previously described in ex utero preterm infants, suggesting that this normative fetal data can provide significant insights into the abnormalities in connectivity which underlie the neurodevelopmental impairments associated with preterm birth.

Trajectories of brain volumes in young children are associated with maternal education.

Brain growth in early childhood is reflected in the evolution of proportional cerebrospinal fluid volumes (pCSF), grey matter (pGM), and white matter (pWM). We study brain development as reflected in the relative fractions of these three tissues for a cohort of 388 children that were longitudinally followed between the ages of 18 and 96 months. We introduce statistical methodology (Riemannian Principal Analysis through Conditional Expectation, RPACE) that addresses major challenges that are of general interest for the analysis of longitudinal neuroimaging data, including the sparsity of the longitudinal observations over time and the compositional structure of the relative brain volumes. Applying the RPACE methodology, we find that longitudinal growth as reflected by tissue composition differs significantly for children of mothers with higher and lower maternal education levels.

Simultaneous Optimization of MP2RAGE T1 -weighted (UNI) and FLuid And White matter Suppression (FLAWS) brain images at 7T using Extended Phase Graph (EPG) Simulations.

PURPOSE: The MP2RAGE sequence is typically optimized for either T1 -weighted uniform image (UNI) or gray matter-dominant fluid and white matter suppression (FLAWS) contrast images. Here, the purpose was to optimize an MP2RAGE protocol at 7 Tesla to provide UNI and FLAWS images simultaneously in a clinically applicable acquisition time at <0.7 mm isotropic resolution. METHODS: Using the extended phase graph formalism, the signal evolution of the MP2RAGE sequence was simulated incorporating T2 relaxation, diffusion, RF spoiling, and B1 + variability. Flip angles and TI were optimized at different TRs (TRMP2RAGE ) to produce an optimal contrast-to-noise ratio for UNI and FLAWS images. Simulation results were validated by comparison to MP2RAGE brain scans of 5 healthy subjects, and a final protocol at TRMP2RAGE  = 4000 ms was applied in 19 subjects aged 8-62 years with and without epilepsy. RESULTS: FLAWS contrast images could be obtained while maintaining >85% of the optimal UNI contrast-to-noise ratio. Using TI1 /TI2 /TRMP2RAGE of 650/2280/4000 ms, 6/8 partial Fourier in the inner phase-encoding direction, and GRAPPA factor = 4 in the other, images with 0.65 mm isotropic resolution were produced in <7.5 min. The contrast-to-noise ratio was around 20% smaller at TRMP2RAGE  = 4000 ms compared to that at TRMP2RAGE  = 5000 ms; however, the 20% shorter duration makes TRMP2RAGE  = 4000 ms a good candidate for clinical applications example, pediatrics. CONCLUSION: FLAWS and UNI images could be obtained in a single scan with 0.65 mm isotropic resolution, providing a set of high-contrast images and full brain coverage in a clinically applicable scan time. Images with excellent anatomical detail were demonstrated over a wide age range using the optimized parameter set.

In vivo T1 mapping of neonatal brain tissue at 64 mT.

PURPOSE: Ultralow-field (ULF) point-of-care MRI systems allow image acquisition without interrupting medical provision, with neonatal clinical care being an important potential application. The ability to measure neonatal brain tissue T1 is a key enabling technology for subsequent structural image contrast optimization, as well as being a potential biomarker for brain development. Here we describe an optimized strategy for neonatal T1 mapping at ULF. METHODS: Examinations were performed on a 64-mT portable MRI system. A phantom validation experiment was performed, and a total of 33 in vivo exams were acquired from 28 neonates with postmenstrual age ranging from 31+4 to 49+0  weeks. Multiple inversion-recovery turbo spin-echo sequences were acquired with differing inversion and repetition times. An analysis pipeline incorporating inter-sequence motion correction generated proton density and T1 maps. Regions of interest were placed in the cerebral deep gray matter, frontal white matter, and cerebellum. Weighted linear regression was used to predict T1 as a function of postmenstrual age. RESULTS: Reduction of T1 with postmenstrual age is observed in all measured brain tissue; the change in T1 per week and 95% confidence intervals is given by dT1  = -21 ms/week [-25, -16] (cerebellum), dT1  = -14 ms/week [-18, -10] (deep gray matter), and dT1  = -35 ms/week [-45, -25] (white matter). CONCLUSION: Neonatal T1 values at ULF are shorter than those previously described at standard clinical field strengths, but longer than those of adults at ULF. T1 reduces with postmenstrual age and is therefore a candidate biomarker for perinatal brain development.

Cortical morphology at birth reflects spatiotemporal patterns of gene expression in the fetal human brain.

Interruption to gestation through preterm birth can significantly impact cortical development and have long-lasting adverse effects on neurodevelopmental outcome. We compared cortical morphology captured by high-resolution, multimodal magnetic resonance imaging (MRI) in n = 292 healthy newborn infants (mean age at birth = 39.9 weeks) with regional patterns of gene expression in the fetal cortex across gestation (n = 156 samples from 16 brains, aged 12 to 37 postconceptional weeks [pcw]). We tested the hypothesis that noninvasive measures of cortical structure at birth mirror areal differences in cortical gene expression across gestation, and in a cohort of n = 64 preterm infants (mean age at birth = 32.0 weeks), we tested whether cortical alterations observed after preterm birth were associated with altered gene expression in specific developmental cell populations. Neonatal cortical structure was aligned to differential patterns of cell-specific gene expression in the fetal cortex. Principal component analysis (PCA) of 6 measures of cortical morphology and microstructure showed that cortical regions were ordered along a principal axis, with primary cortex clearly separated from heteromodal cortex. This axis was correlated with estimated tissue maturity, indexed by differential expression of genes expressed by progenitor cells and neurons, and engaged in stem cell differentiation, neuron migration, and forebrain development. Preterm birth was associated with altered regional MRI metrics and patterns of differential gene expression in glial cell populations. The spatial patterning of gene expression in the developing cortex was thus mirrored by regional variation in cortical morphology and microstructure at term, and this was disrupted by preterm birth. This work provides a framework to link molecular mechanisms to noninvasive measures of cortical development in early life and highlights novel pathways to injury in neonatal populations at increased risk of neurodevelopmental disorder.

Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

Effects of gestational age at birth on perinatal structural brain development in healthy term-born babies.

Infants born in early term (37-38 weeks gestation) experience slower neurodevelopment than those born at full term (40-41 weeks gestation). While this could be due to higher perinatal morbidity, gestational age at birth may also have a direct effect on the brain. Here we characterise brain volume and white matter correlates of gestational age at birth in healthy term-born neonates and their relationship to later neurodevelopmental outcome using T2 and diffusion weighted MRI acquired in the neonatal period from a cohort (n = 454) of healthy babies born at term age (>37 weeks gestation) and scanned between 1 and 41 days after birth. Images were analysed using tensor-based morphometry and tract-based spatial statistics. Neurodevelopment was assessed at age 18 months using the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III). Infants born earlier had higher relative ventricular volume and lower relative brain volume in the deep grey matter, cerebellum and brainstem. Earlier birth was also associated with lower fractional anisotropy, higher mean, axial, and radial diffusivity in major white matter tracts. Gestational age at birth was positively associated with all Bayley-III subscales at age 18 months. Regression models predicting outcome from gestational age at birth were significantly improved after adding neuroimaging features associated with gestational age at birth. This work adds to the body of evidence of the impact of early term birth and highlights the importance of considering the effect of gestational age at birth in future neuroimaging studies including term-born babies.

Simultaneous high-resolution T2 -weighted imaging and quantitative T2 mapping at low magnetic field strengths using a multiple TE and multi-orientation acquisition approach.

PURPOSE: Low magnetic field systems provide an important opportunity to expand MRI to new and diverse clinical and research study populations. However, a fundamental limitation of low field strength systems is the reduced SNR compared to 1.5 or 3T, necessitating compromises in spatial resolution and imaging time. Most often, images are acquired with anisotropic voxels with low through-plane resolution, which provide acceptable image quality with reasonable scan times, but can impair visualization of subtle pathology. METHODS: Here, we describe a super-resolution approach to reconstruct high-resolution isotropic T2 -weighted images from a series of low-resolution anisotropic images acquired in orthogonal orientations. Furthermore, acquiring each image with an incremented TE allows calculations of quantitative T2 images without time penalty. RESULTS: Our approach is demonstrated via phantom and in vivo human brain imaging, with simultaneous 1.5 × 1.5 × 1.5 mm3 T2 -weighted and quantitative T2 maps acquired using a clinically feasible approach that combines three acquisition that require approximately 4-min each to collect. Calculated T2 values agree with reference multiple TE measures with intraclass correlation values of 0.96 and 0.85 in phantom and in vivo measures, respectively, in line with previously reported brain T2 values at 150 mT, 1.5T, and 3T. CONCLUSION: Our multi-orientation and multi-TE approach is a time-efficient method for high-resolution T2 -weighted images for anatomical visualization with simultaneous quantitative T2 imaging for increased sensitivity to tissue microstructure and chemical composition.

Atlas of lesion locations and postsurgical seizure freedom in focal cortical dysplasia: A MELD study.

OBJECTIVE: Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome. METHODS: The MELD (Multi-centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging-based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom. RESULTS: FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%. SIGNIFICANCE: FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data-driven atlases and predictive models are essential for evidence-based, precision medicine and risk counseling in epilepsy.

The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity.

The Developing Human Connectome Project is an Open Science project that provides the first large sample of neonatal functional MRI data with high temporal and spatial resolution. These data enable mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organization in humans. Here, we characterize in unprecedented detail the maturation and integrity of resting state networks (RSNs) at term-equivalent age in 337 infants (including 65 born preterm). First, we applied group independent component analysis to define 11 RSNs in term-born infants scanned at 43.5-44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37-43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder, which occur frequently in preterm children. Overall, we found a robust, modular, symmetrical functional brain organization at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity.

Phenotyping the Preterm Brain: Characterizing Individual Deviations From Normative Volumetric Development in Two Large Infant Cohorts.

The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterizing brain volumetric development in 274 term-born infants, modeling for age at scan and sex. We then compared 89 preterm infants scanned at term-equivalent age with these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalizability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, nonuniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguises a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterization of the cerebral consequences of preterm birth by profiling the individual neonatal brain.

Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age.

INTRODUCTION: The dynamic nature and complexity of the cellular events that take place during the last trimester of pregnancy make the developing cortex particularly vulnerable to perturbations. Abrupt interruption to normal gestation can lead to significant deviations to many of these processes, resulting in atypical trajectory of cortical maturation in preterm birth survivors. METHODS: We sought to first map typical cortical micro- and macrostructure development using invivo MRI in a large sample of healthy term-born infants scanned after birth (n = 259). Then we offer a comprehensive characterization of the cortical consequences of preterm birth in 76 preterm infants scanned at term-equivalent age (37-44 weeks postmenstrual age). We describe the group-average atypicality, the heterogeneity across individual preterm infants, and relate individual deviations from normative development to age at birth and neurodevelopment at 18 months. RESULTS: In the term-born neonatal brain, we observed heterogeneous and regionally specific associations between age at scan and measures of cortical morphology and microstructure, including rapid surface expansion, greater cortical thickness, lower cortical anisotropy and higher neurite orientation dispersion. By term-equivalent age, preterm infants had on average increased cortical tissue water content and reduced neurite density index in the posterior parts of the cortex, and greater cortical thickness anteriorly compared to term-born infants. While individual preterm infants were more likely to show extreme deviations (over 3.1 standard deviations) from normative cortical maturation compared to term-born infants, these extreme deviations were highly variable and showed very little spatial overlap between individuals. Measures of regional cortical development were associated with age at birth, but not with neurodevelopment at 18 months. CONCLUSION: We showed that preterm birth alters cortical micro- and macrostructural maturation near the time of full-term birth. Deviations from normative development were highly variable between individual preterm infants.

Neurodevelopmental Outcomes following Intrauterine Growth Restriction and Very Preterm Birth.

OBJECTIVES: To evaluate whether intrauterine growth restriction (IUGR) adds further neurodevelopmental risk to that posed by very preterm birth alone in terms of alterations in brain growth and poorer toddlerhood outcomes. STUDY DESIGN: Participants were 314 infants of very preterm birth enrolled in the Evaluation of Preterm Imaging Study (e-Prime) who were subsequently followed up in toddlerhood. IUGR was identified postnatally from discharge records (n = 49) and defined according to prenatal evaluation of growth restriction confirmed by birth weight <10th percentile for gestational age and/or alterations in fetal Doppler. Appropriate for gestational age (AGA; n = 265) was defined as birth weight >10th percentile for gestational age at delivery. Infants underwent magnetic resonance imaging at term-equivalent age (median = 42 weeks); T2-weighted images were obtained for voxelwise gray matter volumes. Follow-up assessments were conducted at corrected median age of 22 months using the Bayley Scales of Infant and Toddler Development III and the Modified-Checklist for Autism in Toddlers. RESULTS: Infants of very preterm birth with IUGR displayed a relative volumetric decrease in gray matter in limbic regions and a relative increase in frontoinsular, temporal-parietal, and frontal areas compared with peers of very preterm birth who were AGA. At follow-up, toddlers born very preterm with IUGR had significantly lower cognitive (effect size = 0.42) and motor (effect size = 0.41) scores and were more likely to have a positive Modified-Checklist for Autism in Toddlers screening for autism (OR = 2.12) compared with peers of very preterm birth who were AGA. CONCLUSIONS: IUGR might confer a neurodevelopmental risk that is greater than that posed by very preterm alone, in terms of both alterations in brain growth and poorer toddlerhood outcomes.

Modelling brain development to detect white matter injury in term and preterm born neonates.

Premature birth occurs during a period of rapid brain growth. In this context, interpreting clinical neuroimaging can be complicated by the typical changes in brain contrast, size and gyrification occurring in the background to any pathology. To model and describe this evolving background in brain shape and contrast, we used a Bayesian regression technique, Gaussian process regression, adapted to multiple correlated outputs. Using MRI, we simultaneously estimated brain tissue intensity on T1- and T2-weighted scans as well as local tissue shape in a large cohort of 408 neonates scanned cross-sectionally across the perinatal period. The resulting model provided a continuous estimate of brain shape and intensity, appropriate to age at scan, degree of prematurity and sex. Next, we investigated the clinical utility of this model to detect focal white matter injury. In individual neonates, we calculated deviations of a neonate's observed MRI from that predicted by the model to detect punctate white matter lesions with very good accuracy (area under the curve > 0.95). To investigate longitudinal consistency of the model, we calculated model deviations in 46 neonates who were scanned on a second occasion. These infants' voxelwise deviations from the model could be used to identify them from the other 408 images in 83% (T2-weighted) and 76% (T1-weighted) of cases, indicating an anatomical fingerprint. Our approach provides accurate estimates of non-linear changes in brain tissue intensity and shape with clear potential for radiological use.

Heterogeneity in Brain Microstructural Development Following Preterm Birth.

Preterm-born children are at increased risk of lifelong neurodevelopmental difficulties. Group-wise analyses of magnetic resonance imaging show many differences between preterm- and term-born infants but do not reliably predict neurocognitive prognosis for individual infants. This might be due to the unrecognized heterogeneity of cerebral injury within the preterm group. This study aimed to determine whether atypical brain microstructural development following preterm birth is significantly variable between infants. Using Gaussian process regression, a technique that allows a single-individual inference, we characterized typical variation of brain microstructure using maps of fractional anisotropy and mean diffusivity in a sample of 270 term-born neonates. Then, we compared 82 preterm infants to these normative values to identify brain regions with atypical microstructure and relate observed deviations to degree of prematurity and neurocognition at 18 months. Preterm infants showed strikingly heterogeneous deviations from typical development, with little spatial overlap between infants. Greater and more extensive deviations, captured by a whole brain atypicality index, were associated with more extreme prematurity and predicted poorer cognitive and language abilities at 18 months. Brain microstructural development after preterm birth is highly variable between individual infants. This poorly understood heterogeneity likely relates to both the etiology and prognosis of brain injury.

Development of Microstructural and Morphological Cortical Profiles in the Neonatal Brain.

Interruptions to neurodevelopment during the perinatal period may have long-lasting consequences. However, to be able to investigate deviations in the foundation of proper connectivity and functional circuits, we need a measure of how this architecture evolves in the typically developing brain. To this end, in a cohort of 241 term-born infants, we used magnetic resonance imaging to estimate cortical profiles based on morphometry and microstructure over the perinatal period (37-44 weeks postmenstrual age, PMA). Using the covariance of these profiles as a measure of inter-areal network similarity (morphometric similarity networks; MSN), we clustered these networks into distinct modules. The resulting modules were consistent and symmetric, and corresponded to known functional distinctions, including sensory-motor, limbic, and association regions, and were spatially mapped onto known cytoarchitectonic tissue classes. Posterior regions became more morphometrically similar with increasing age, while peri-cingulate and medial temporal regions became more dissimilar. Network strength was associated with age: Within-network similarity increased over age suggesting emerging network distinction. These changes in cortical network architecture over an 8-week period are consistent with, and likely underpin, the highly dynamic processes occurring during this critical period. The resulting cortical profiles might provide normative reference to investigate atypical early brain development.