Exposure to urban particulate matter (UPM) impairs mitochondrial dynamics in BV2 cells, triggering a mitochondrial biogenesis response.

World Health Organisation data suggest that up to 99% of the global population are exposed to air pollutants above recommended levels. Impacts to health range from increased risk of stroke and cardiovascular disease to chronic respiratory conditions, and air pollution may contribute to over 7 million premature deaths a year. Additionally, mounting evidence suggests that in utero or early life exposure to particulate matter (PM) in ambient air pollution increases the risk of neurodevelopmental impairment with obvious lifelong consequences. Identifying brain-specific cellular targets of PM is vital for determining its long-term consequences. We previously established that microglial-like BV2 cells were particularly sensitive to urban (U)PM-induced damage including reactive oxygen species production, which was abrogated by a mitochondrially targeted antioxidant. Here we extend those studies to find that UPM treatment causes a rapid impairment of mitochondrial function and increased mitochondrial fragmentation. However, there is a subsequent restoration of mitochondrial and therefore cell health occurring concomitantly with upregulated measures of mitochondrial biogenesis and mitochondrial load. Our data highlight that protecting mitochondrial function may represent a valuable mechanism to offset the effects of UPM exposure in the neonatal brain. KEY POINTS: Air pollution represents a growing risk to long-term health especially in early life, and the CNS is emerging a target for airborne particulate matter (PM). We previously showed that microglial-like BV2 cells were vulnerable to urban (U)PM exposure, which impaired cell survival and promoted reactive oxygen species production. Here we find that, following UPM exposure, BV2 mitochondrial membrane potential is rapidly reduced, concomitant with decreased cellular bioenergetics and increased mitochondrial fission. However, markers of mitochondrial biogenesis and mitochondrial mass are subsequently induced, which may represent a cellular mitigation strategy. As mitochondria are more vulnerable in the developing brain, exposure to air pollution may represent a greater risk to lifelong health in this cohort; conversely, promoting mitochondrial integrity may offset these risks.

Executive Function in Preschool Children with Congenital Heart Disease and Controls: The Role of a Cognitively Stimulating Home Environment.

OBJECTIVE: To assess the relationships between (1) environmental and demographic factors and executive function (EF) in preschool children with congenital heart disease (CHD) and controls and (2) clinical and surgical risk factors and EF in preschool children with CHD. STUDY DESIGN: At 4-6 years of age, parents of children with CHD (n = 51) and controls (n = 124) completed the Behavior Rating Inventory of Executive Function, Preschool Version questionnaire and the Cognitively Stimulating Parenting Scale (CSPS). Multivariable general linear modeling assessed the relationship between Behavior Rating Inventory of Executive Function, Preschool Version composite scores (Inhibitory Self-Control Index [ISCI], Flexibility Index [FI], and Emergent Metacognition Index [EMI]) and group (CHD/control), sex, age at assessment, gestational age, Index of Multiple Deprivation, and CSPS scores. The relationships between CHD type, surgical factors, and brain magnetic resonance imaging injury rating and ISCI, FI, and EMI scores were assessed. RESULTS: The presence of CHD, age at assessment, sex, and Index of Multiple Deprivation were not associated with EF scores. Lower gestational age was associated with greater ISCI and FI scores, and age at assessment was associated with lower FI scores. Group significantly moderated the relationship between CSPS and EF, such that CSPS significantly predicted EF in children with CHD (ISCI: P = .0004; FI: P = .0015; EMI: P = .0004) but not controls (ISCI: P = .2727; FI: P = .6185; EMI: P = .3332). There were no significant relationships between EF scores and surgical factors, CHD type, or brain magnetic resonance imaging injury rating. CONCLUSIONS: Supporting parents to provide a cognitively stimulating home environment may improve EF in children with CHD. The home and parenting environment should be considered when designing intervention studies aimed at improving EF in this patient group.

Perioperative Brain Injury in Relation to Early Neurodevelopment Among Children with Severe Congenital Heart Disease: Results from a European Collaboration.

OBJECTIVE: To examine the relationship between perioperative brain injury and neurodevelopment during early childhood in patients with severe congenital heart disease (CHD). STUDY DESIGN: One hundred and seventy children with CHD and born at term who required cardiopulmonary bypass surgery in the first 6 weeks after birth were recruited from 3 European centers and underwent preoperative and postoperative brain MRIs. Uniform description of imaging findings was performed and an overall brain injury score was created, based on the sum of the worst preoperative or postoperative brain injury subscores. Motor and cognitive outcomes were assessed with the Bayley Scales of Infant and Toddler Development Third Edition at 12 to 30 months of age. The relationship between brain injury score and clinical outcome was assessed using multiple linear regression analysis, adjusting for CHD severity, length of hospital stay (LOS), socioeconomic status (SES), and age at follow-up. RESULTS: Neither the overall brain injury score nor any of the brain injury subscores correlated with motor or cognitive outcome. The number of preoperative white matter lesions was significantly associated with gross motor outcome after correction for multiple testing (P = .013, ß = -0.50). SES was independently associated with cognitive outcome (P < .001, ß = 0.26), and LOS with motor outcome (P < .001, ß = -0.35). CONCLUSION: Preoperative white matter lesions appear to be the most predictive MRI marker for adverse early childhood gross motor outcome in this large European cohort of infants with severe CHD. LOS as a marker of disease severity, and SES influence outcome and future intervention trials need to address these risk factors.

Advances in fetal and neonatal neuroimaging and everyday exposures.

The complex, tightly regulated process of prenatal brain development may be adversely affected by "everyday exposures" such as stress and environmental pollutants. Researchers are only just beginning to understand the neural sequelae of such exposures, with advances in fetal and neonatal neuroimaging elucidating structural, microstructural, and functional correlates in the developing brain. This narrative review discusses the wide-ranging literature investigating the influence of parental stress on fetal and neonatal brain development as well as emerging literature assessing the impact of exposure to environmental toxicants such as lead and air pollution. These 'everyday exposures' can co-occur with other stressors such as social and financial deprivation, and therefore we include a brief discussion of neuroimaging studies assessing the effect of social disadvantage. Increased exposure to prenatal stressors is associated with alterations in the brain structure, microstructure and function, with some evidence these associations are moderated by factors such as infant sex. However, most studies examine only single exposures and the literature on the relationship between in utero exposure to pollutants and fetal or neonatal brain development is sparse. Large cohort studies are required that include evaluation of multiple co-occurring exposures in order to fully characterize their impact on early brain development. IMPACT: Increased prenatal exposure to parental stress and is associated with altered functional, macro and microstructural fetal and neonatal brain development. Exposure to air pollution and lead may also alter brain development in the fetal and neonatal period. Further research is needed to investigate the effect of multiple co-occurring exposures, including stress, environmental toxicants, and socioeconomic deprivation on early brain development.

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 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.

Assessing within-subject rates of change of placental MRI diffusion metrics in normal pregnancy.

PURPOSE: Studying placental development informs when development is abnormal. Most placental MRI studies are cross-sectional and do not study the extent of individual variability throughout pregnancy. We aimed to explore how diffusion MRI measures of placental function and microstructure vary in individual healthy pregnancies throughout gestation. METHODS: Seventy-nine pregnant, low-risk participants (17 scanned twice and 62 scanned once) were included. T2 -weighted anatomical imaging and a combined multi-echo spin-echo diffusion-weighted sequence were acquired at 3 T. Combined diffusion-relaxometry models were performed using both a T 2 * $$ {\mathrm{T}}_2^{\ast } $$ -ADC and a bicompartmental T 2 * $$ {\mathrm{T}}_2^{\ast } $$ -intravoxel-incoherent-motion ( T 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ ) model fit. RESULTS: There was a significant decline in placental T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and ADC (both P < 0.01) over gestation. These declines are consistent in individuals for T 2 * $$ {\mathrm{T}}_2^{\ast } $$ (covariance = -0.47), but not ADC (covariance = -1.04). The T 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ model identified a consistent decline in individuals over gestation in T 2 * $$ {\mathrm{T}}_2^{\ast } $$ from both the perfusing and diffusing placental compartments, but not in ADC values from either. The placental perfusing compartment fraction increased over gestation (P = 0.0017), but this increase was not consistent in individuals (covariance = 2.57). CONCLUSION: Whole placental T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and ADC values decrease over gestation, although only T 2 * $$ {\mathrm{T}}_2^{\ast } $$ values showed consistent trends within subjects. There was minimal individual variation in rates of change of T 2 * $$ {\mathrm{T}}_2^{\ast } $$ values from perfusing and diffusing placental compartments, whereas trends in ADC values from these compartments were less consistent. These findings probably relate to the increased complexity of the bicompartmental T 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ model, and differences in how different placental regions evolve at a microstructural level. These placental MRI metrics from low-risk pregnancies provide a useful benchmark for clinical cohorts.

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.

Total and Regional Brain Volumes in Fetuses With Congenital Heart Disease.

BACKGROUND: Congenital heart disease (CHD) is common and is associated with impaired early brain development and neurodevelopmental outcomes, yet the exact mechanisms underlying these associations are unclear. PURPOSE: To utilize MRI data from a cohort of fetuses with CHD as well as typically developing fetuses to test the hypothesis that expected cerebral substrate delivery is associated with total and regional fetal brain volumes. STUDY TYPE: Retrospective case-control study. POPULATION: Three hundred eighty fetuses (188 male), comprising 45 healthy controls and 335 with isolated CHD, scanned between 29 and 37 weeks gestation. Fetuses with CHD were assigned into one of four groups based on expected cerebral substrate delivery. FIELD STRENGTH/SEQUENCE: T2-weighted single-shot fast-spin-echo sequences and a balanced steady-state free precession gradient echo sequence were obtained on a 1.5 T scanner. ASSESSMENT: Images were motion-corrected and reconstructed using an automated slice-to-volume registration reconstruction technique, before undergoing segmentation using an automated pipeline and convolutional neural network that had undergone semi-supervised training. Differences in total, regional brain (cortical gray matter, white matter, deep gray matter, cerebellum, and brainstem) and brain:body volumes were compared between groups. STATISTICAL TESTS: ANOVA was used to test for differences in brain volumes between groups, after accounting for sex and gestational age at scan. PFDR -values <0.05 were considered statistically significant. RESULTS: Total and regional brain volumes were smaller in fetuses where cerebral substrate delivery is reduced. No significant differences were observed in total or regional brain volumes between control fetuses and fetuses with CHD but normal cerebral substrate delivery (all PFDR > 0.12). Severely reduced cerebral substrate delivery is associated with lower brain:body volume ratios. DATA CONCLUSION: Total and regional brain volumes are smaller in fetuses with CHD where there is a reduction in cerebral substrate delivery, but not in those where cerebral substrate delivery is expected to be normal. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Early life exposure to air pollution impacts neuronal and glial cell function leading to impaired neurodevelopment.

The World Health Organisation recently listed air pollution as the most significant threat to human health. Air pollution comprises particulate matter (PM), metals, black carbon and gases such as ozone (O3 ), nitrogen dioxide (NO2 ) and carbon monoxide (CO). In addition to respiratory and cardiovascular disease, PM exposure is linked with increased risk of neurodegeneration as well as neurodevelopmental impairments. Critically, studies suggest that PM crosses the placenta, making direct in utero exposure a reality. Rodent models reveal that neuroinflammation, neurotransmitter imbalance and oxidative stress are triggered following gestational/early life exposure to PM, and may be exacerbated by concomitant mitochondrial dysfunction. Gestational PM exposure (potentiated by mitochondrial impairment in the metabolically active neonatal brain) not only impacts neurodevelopment but may sensitise the brain to subsequent cognitive impairment. Having reviewed this field, we conclude that strategies are urgently required to reduce exposure to PM during this sensitive developmental period.

Risk Factors for Perioperative Brain Lesions in Infants With Congenital Heart Disease: A European Collaboration.

BACKGROUND: Infants with congenital heart disease are at risk of brain injury and impaired neurodevelopment. The aim was to investigate risk factors for perioperative brain lesions in infants with congenital heart disease. METHODS: Infants with transposition of the great arteries, single ventricle physiology, and left ventricular outflow tract and/or aortic arch obstruction undergoing cardiac surgery <6 weeks after birth from 3 European cohorts (Utrecht, Zurich, and London) were combined. Brain lesions were scored on preoperative (transposition of the great arteries N=104; single ventricle physiology N=35; and left ventricular outflow tract and/or aortic arch obstruction N=41) and postoperative (transposition of the great arteries N=88; single ventricle physiology N=28; and left ventricular outflow tract and/or aortic arch obstruction N=30) magnetic resonance imaging for risk factor analysis of arterial ischemic stroke, cerebral sinus venous thrombosis, and white matter injury. RESULTS: Preoperatively, induced vaginal delivery (odds ratio [OR], 2.23 [95% CI, 1.06-4.70]) was associated with white matter injury and balloon atrial septostomy increased the risk of white matter injury (OR, 2.51 [95% CI, 1.23-5.20]) and arterial ischemic stroke (OR, 4.49 [95% CI, 1.20-21.49]). Postoperatively, younger postnatal age at surgery (OR, 1.18 [95% CI, 1.05-1.33]) and selective cerebral perfusion, particularly at ≤20 °C (OR, 13.46 [95% CI, 3.58-67.10]), were associated with new arterial ischemic stroke. Single ventricle physiology was associated with new white matter injury (OR, 2.88 [95% CI, 1.20-6.95]) and transposition of the great arteries with new cerebral sinus venous thrombosis (OR, 13.47 [95% CI, 2.28-95.66]). Delayed sternal closure (OR, 3.47 [95% CI, 1.08-13.06]) and lower intraoperative temperatures (OR, 1.22 [95% CI, 1.07-1.36]) also increased the risk of new cerebral sinus venous thrombosis. CONCLUSIONS: Delivery planning and surgery timing may be modifiable risk factors that allow personalized treatment to minimize the risk of perioperative brain injury in severe congenital heart disease. Further research is needed to optimize cerebral perfusion techniques for neonatal surgery and to confirm the relationship between cerebral sinus venous thrombosis and perioperative risk factors.

Predicting age and clinical risk from the neonatal connectome.

The development of perinatal brain connectivity underpins motor, cognitive and behavioural abilities in later life. Diffusion MRI allows the characterisation of subtle inter-individual differences in structural brain connectivity. Individual brain connectivity maps (connectomes) are by nature high in dimensionality and complex to interpret. Machine learning methods are a powerful tool to uncover properties of the connectome which are not readily visible and can give us clues as to how and why individual developmental trajectories differ. In this manuscript we used Deep Neural Networks and Random Forests to predict demographic and neurodevelopmental characteristics from neonatal structural connectomes in a large sample of babies (n = 524) from the developing Human Connectome Project. We achieved an accurate prediction of post menstrual age (PMA) at scan in term-born infants (mean absolute error (MAE) = 0.72 weeks, r = 0.83 and p < 0.001). We also achieved good accuracy when predicting gestational age at birth in a cohort of term and preterm babies scanned at term equivalent age (MAE = 2.21 weeks, r = 0.82, p < 0.001). We subsequently used sensitivity analysis to obtain feature relevance from our prediction models, with the most important connections for prediction of PMA and GA found to predominantly involve frontal and temporal regions, thalami, and basal ganglia. From our models of PMA at scan for infants born at term, we computed a brain maturation index (predicted age minus actual age) of individual preterm neonates and found a significant correlation between this index and motor outcome at 18 months corrected age. Our results demonstrate the applicability of machine learning techniques in analyses of the neonatal connectome and suggest that a neural substrate of brain maturation with implications for future neurodevelopment is detectable at term equivalent age from the neonatal connectome.

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.

Differential Effects of Urban Particulate Matter on BV2 Microglial-Like and C17.2 Neural Stem/Precursor Cells.

Air pollution affects the majority of the world's population and has been linked to over 7 million premature deaths per year. Exposure to particulate matter (PM) contained within air pollution is associated with cardiovascular, respiratory, and neurological ill health. There is increasing evidence that exposure to air pollution in utero and in early childhood is associated with altered brain development. However, the underlying mechanisms for impaired brain development are not clear. While oxidative stress and neuroinflammation are documented consequences of PM exposure, cell-specific mechanisms that may be triggered in response to air pollution exposure are less well defined. Here, we assess the effect of urban PM exposure on two different cell types, microglial-like BV2 cells and neural stem/precursor-like C17.2 cells. We found that, contrary to expectations, immature C17.2 cells were more resistant to PM-mediated oxidative stress and cell death than BV2 cells. PM exposure resulted in decreased mitochondrial health and increased mitochondrial ROS in BV2 cells which could be prevented by MitoTEMPO antioxidant treatment. Our data suggest that not only is mitochondrial dysfunction a key trigger in PM-mediated cytotoxicity but that such deleterious effects may also depend on cell type and maturity.

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.

The factor structure of the Edinburgh Postnatal Depression Scale among perinatal high-risk and community samples in London.

Timely and accurate detection of perinatal mental health problems is essential for the wellbeing of both mother and child. Growing evidence has suggested that the Edinburgh Postnatal Depression Scale (EPDS) is not a unidimensional measure of perinatal depression, but can be used to screen for anxiety disorders. We aimed to assess the factor structure of the EPDS in 3 different groups of women: n = 266 pregnant women at high-risk of depression ("Perinatal Stress Study"), n = 471 pregnant women from a community sample, and n = 637 early postnatal women from a community sample ("developing Human Connectome Project"). Exploratory factor analysis (40% of each sample) and confirmatory factor analysis (60% of each sample) were performed. The relationship between EPDS scores and history of mental health concerns was investigated. Results suggested that a 3-factor model (depression, anxiety, and anhedonia) is the most appropriate across groups. The anxiety subscale (EPDS-3A) emerged consistently and was related to maternal history of anxiety disorders in the prenatal sample (W = 6861, p < 0.001). EPDS total score was related to history of mental health problems in both the prenatal (W = 12,185, p < 0.001) and postnatal samples (W = 30,044, p < 0.001). In both high-risk and community samples in the perinatal period, the EPDS appears to consist of depression, anxiety, and anhedonia subscales. A better understanding of the multifactorial structure of the EPDS can inform diagnosis and management of women in the prenatal and postnatal period. Further research is required to validate the EPDS-3A as a screening tool for anxiety.

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.

MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances.

In recent years, exploration of the developing brain has become a major focus for researchers and clinicians in an attempt to understand what allows children to acquire amazing and unique abilities, as well as the impact of early disruptions (eg, prematurity, neonatal insults) that can lead to a wide range of neurodevelopmental disorders. Noninvasive neuroimaging methods such as MRI are essential to establish links between the brain and behavioral changes in newborns and infants. In this review article, we aim to highlight recent and representative studies using the various techniques available: anatomical MRI, quantitative MRI (relaxometry, diffusion MRI), multiparametric approaches, and functional MRI. Today, protocols use 1.5 or 3T MRI scanners, and specialized methodologies have been put in place for data acquisition and processing to address the methodological challenges specific to this population, such as sensitivity to motion. MR sequences must be adapted to the brains of newborns and infants to obtain relevant good soft-tissue contrast, given the small size of the cerebral structures and the incomplete maturation of tissues. The use of age-specific image postprocessing tools is also essential, as signal and contrast differ from the adult brain. Appropriate methodologies then make it possible to explore multiple neurodevelopmental mechanisms in a precise way, and assess changes with age or differences between groups of subjects, particularly through large-scale projects. Although MRI measurements only indirectly reflect the complex series of dynamic processes observed throughout development at the molecular and cellular levels, this technique can provide information on brain morphology, structural connectivity, microstructural properties of gray and white matter, and on the functional architecture. Finally, MRI measures related to clinical, behavioral, and electrophysiological markers have a key role to play from a diagnostic and prognostic perspective in the implementation of early interventions to avoid long-term disabilities in children. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 1.

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.