Brain structural and functional outcomes in the offspring of women experiencing psychological distress during pregnancy.

In-utero exposure to maternal psychological distress is increasingly linked with disrupted fetal and neonatal brain development and long-term neurobehavioral dysfunction in children and adults. Elevated maternal psychological distress is associated with changes in fetal brain structure and function, including reduced hippocampal and cerebellar volumes, increased cerebral cortical gyrification and sulcal depth, decreased brain metabolites (e.g., choline and creatine levels), and disrupted functional connectivity. After birth, reduced cerebral and cerebellar gray matter volumes, increased cerebral cortical gyrification, altered amygdala and hippocampal volumes, and disturbed brain microstructure and functional connectivity have been reported in the offspring months or even years after exposure to maternal distress during pregnancy. Additionally, adverse child neurodevelopment outcomes such as cognitive, language, learning, memory, social-emotional problems, and neuropsychiatric dysfunction are being increasingly reported after prenatal exposure to maternal distress. The mechanisms by which prenatal maternal psychological distress influences early brain development include but are not limited to impaired placental function, disrupted fetal epigenetic regulation, altered microbiome and inflammation, dysregulated hypothalamic pituitary adrenal axis, altered distribution of the fetal cardiac output to the brain, and disrupted maternal sleep and appetite. This review will appraise the available literature on the brain structural and functional outcomes and neurodevelopmental outcomes in the offspring of pregnant women experiencing elevated psychological distress. In addition, it will also provide an overview of the mechanistic underpinnings of brain development changes in stress response and discuss current treatments for elevated maternal psychological distress, including pharmacotherapy (e.g., selective serotonin reuptake inhibitors) and non-pharmacotherapy (e.g., cognitive-behavior therapy). Finally, it will end with a consideration of future directions in the field.

Intrauterine exposure to SARS-CoV-2 infection and early newborn brain development.

Epidemiologic studies suggest that prenatal exposures to certain viruses may influence early neurodevelopment, predisposing offspring to neuropsychiatric conditions later in life. The long-term effects of maternal COVID-19 infection in pregnancy on early brain development, however, remain largely unknown. We prospectively enrolled infants in an observational cohort study for a single-site study in the Washington, DC Metropolitan Area from June 2020 to November 2021 and compared these infants to pre-pandemic controls (studied March 2014-February 2020). The primary outcomes are measures of cortical morphometry (tissue-specific volumes), along with global and regional measures of local gyrification index, and sulcal depth. We studied 210 infants (55 infants of COVID-19 unexposed mothers, 47 infants of COVID-19-positive mothers, and 108 pre-pandemic healthy controls). We found increased cortical gray matter volume (182.45 ± 4.81 vs. 167.29 ± 2.92) and accelerated sulcal depth of the frontal lobe (5.01 ± 0.19 vs. 4.40 ± 0.13) in infants of COVID-19-positive mothers compared to controls. We found additional differences in infants of COVID-19 unexposed mothers, suggesting both maternal viral exposures, as well as non-viral stressors associated with the pandemic, may influence early development and warrant ongoing follow-up.

Separating group- and individual-level brain signatures in the newborn functional connectome: A deep learning approach.

Recent studies indicate that differences in cognition among individuals may be partially attributed to unique brain wiring patterns. While functional connectivity (FC)-based fingerprinting has demonstrated high accuracy in identifying adults, early studies on neonates suggest that individualized FC signatures are absent. We posit that individual uniqueness is present in neonatal FC data and that conventional linear models fail to capture the rapid developmental trajectories characteristic of newborn brains. To explore this hypothesis, we employed a deep generative model, known as a variational autoencoder (VAE), leveraging two extensive public datasets: one comprising resting-state functional MRI (rs-fMRI) scans from 100 adults and the other from 464 neonates. VAE models trained on rs-fMRI from both adults and newborns produced superior age prediction performance (with r between predicted- and actual age ∼ 0.7) and individual identification accuracy (∼45 %) compared to models trained solely on adult or neonatal data. The VAE model also showed significantly higher individual identification accuracy than linear models (=10∼30 %). Importantly, the VAE differentiated connections reflecting age-related changes from those indicative of individual uniqueness, a distinction not possible with linear models. Moreover, we derived 20 latent variables, each corresponding to distinct patterns of cortical functional network (CFNs). These CFNs varied in their representation of brain maturation and individual signatures; notably, certain CFNs that failed to capture neurodevelopmental traits, in fact, exhibited individual signatures. CFNs associated with neonatal neurodevelopment predominantly encompassed unimodal regions such as visual and sensorimotor areas, whereas those linked to individual uniqueness spanned multimodal and transmodal brain regions. The VAE's capacity to extract features from rs-fMRI data beyond the capabilities of linear models positions it as a valuable tool for delineating cognitive traits inherent in rs-fMRI and exploring individualized imaging phenotypes.

Central Autonomic Network and heart rate variability in premature neonates.

INTRODUCTION: The Central Autonomic Network (CAN) is a hierarchy of brain structures that collectively influence cardiac autonomic input, mediating the majority of brain-heart interactions, but has never been studied in premature neonates. In this study, we use heart rate variability (HRV), which has been described as the "primary output" of the CAN, and resting state functional MRI to characterize brain-heart relationships in premature neonates. METHODS: We studied premature neonates who underwent resting state functional MRI (rsfMRI) at term, (37-weeks postmenstrual age [PMA] or above) and had HRV data recorded during the same week of their MRI. HRV was derived from continuous electrocardiogram data during the week of the rsfMRI scan. For rsfMRI, a seed-based approach was used to define regions of interest (ROI) pertinent to the CAN, and blood oxygen level-dependent signal was correlated between each ROI as a measure of functional connectivity. HRV was correlated with CAN connectivity (CANconn) for each region, and sub-group analysis was performed based on sex and clinical comorbidities. RESULTS: Forty-seven premature neonates were included in this study, with a mean gestational age at birth of 28.1 +/- 2.6 weeks. Term CANconn was found to be significantly correlated with HRV in approximately one-fifth of CAN connections. Two distinct patterns emerged among these HRV-CANconn relationships. In the first, increased HRV was associated with stronger CANconn of limbic regions. In the second pattern, stronger CANconn at the precuneus was associated with impaired HRV maturation. These patterns were especially pronounced in male premature neonates. CONCLUSION: We report for the first time evidence of brain-heart relationships in premature neonates and an emerging CAN, most striking in male neonates, suggesting that the brain-heart axis may be more vulnerable in male premature neonates. Signatures in the heart rate may eventually become an important non-invasive tool to identify premature males at highest risk for neurodevelopmental impairment.

Greater Neighborhood Disadvantage Is Associated with Alterations in Fetal Functional Brain Network Structure.

OBJECTIVE: To determine the association between neighborhood disadvantage (ND) and functional brain development of in utero fetuses. STUDY DESIGN: We conducted an observational study using Social Vulnerability Index (SVI) scores to assess the impact of ND on a prospectively recruited sample of healthy pregnant women from Washington, DC. Using 79 functional magnetic resonance imaging scans from 68 healthy pregnancies at a mean gestational age of 33.12 weeks, we characterized the overall functional brain network structure using a graph metric approach. We used linear mixed effects models to assess the relationship between SVI and gestational age on 5 graph metrics, adjusting for multiple scans. RESULTS: Exposure to greater ND was associated with less well integrated functional brain networks, as observed by longer characteristic path lengths and diminished global efficiency (GE), as well as diminished small world propensity (SWP). Across gestational ages, however, the association between SVI and network integration diminished to a negligible relationship in the third trimester. Conversely, SWP was significant across pregnancy, but the relationship changed such that there was a negative association with SWP earlier in the second trimester that inverted around the transition to the third trimester to a positive association. CONCLUSIONS: These data directly connect ND and altered functional brain maturation in fetuses. Our results suggest that, even before birth, proximity to environmental stressors in the wider neighborhood environment are associated with altered brain development.

Gestational age-related changes in the fetal functional connectome: in utero evidence for the global signal.

The human brain begins to develop in the third gestational week and rapidly grows and matures over the course of pregnancy. Compared to fetal structural neurodevelopment, less is known about emerging functional connectivity in utero. Here, we investigated gestational age (GA)-associated in vivo changes in functional brain connectivity during the second and third trimesters in a large dataset of 110 resting-state functional magnetic resonance imaging scans from a cohort of 95 healthy fetuses. Using representational similarity analysis, a multivariate analytical technique that reveals pair-wise similarity in high-order space, we showed that intersubject similarity of fetal functional connectome patterns was strongly related to between-subject GA differences (r = 0.28, P < 0.01) and that GA sensitivity of functional connectome was lateralized, especially at the frontal area. Our analysis also revealed a subnetwork of connections that were critical for predicting age (mean absolute error = 2.72 weeks); functional connectome patterns of individual fetuses reliably predicted their GA (r = 0.51, P < 0.001). Lastly, we identified the primary principal brain network that tracked fetal brain maturity. The main network showed a global synchronization pattern resembling global signal in the adult brain.

Robust sex differences in functional brain connectivity are present in utero.

Sex-based differences in brain structure and function are observable throughout development and are thought to contribute to differences in behavior, cognition, and the presentation of neurodevelopmental disorders. Using multiple support vector machine (SVM) models as a data-driven approach to assess sex differences, we sought to identify regions exhibiting sex-dependent differences in functional connectivity and determine whether they were robust and sufficiently reliable to classify sex even prior to birth. To accomplish this, we used a sample of 110 human fetal resting state fMRI scans from 95 fetuses, performed between 19 and 40 gestational weeks. Functional brain connectivity patterns classified fetal sex with 73% accuracy. Across SVM models, we identified features (functional connections) that reliably differentiated fetal sex. Highly consistent predictors included connections in the somatomotor and frontal areas alongside the hippocampus, cerebellum, and basal ganglia. Moreover, high consistency features also implicated a greater magnitude of cross-region connections in females, while male weighted features were predominately within anatomically bounded regions. Our findings indicate that these differences, which have been observed later in childhood, are present and reliably detectable even before birth. These results show that sex differences arise before birth in a manner that is consistent and reliable enough to be highly identifiable.

Severity of prematurity and age impact early postnatal development of GABA and glutamate systems.

Gamma-aminobutyric acid (GABA) and glutamatergic system perturbations following premature birth may explain neurodevelopmental deficits in the absence of structural brain injury. Using GABA-edited spectroscopy (MEscher-GArwood Point Resolved Spectroscopy [MEGA-PRESS] on 3 T MRI), we have described in-vivo brain GABA+ (+macromolecules) and Glx (glutamate + glutamine) concentrations in term-born infants. We report previously unavailable comparative data on in-vivo GABA+ and Glx concentrations in the cerebellum, the right basal ganglia, and the right frontal lobe of preterm-born infants without structural brain injury. Seventy-five preterm-born (gestational age 27.8 ± 2.9 weeks) and 48 term-born (39.6 ± 0.9 weeks) infants yielded reliable MEGA-PRESS spectra acquired at post-menstrual age (PMA) of 40.2 ± 2.3 and 43.0 ± 2 weeks, respectively. GABA+ (median 2.44 institutional units [i.u.]) concentrations were highest in the cerebellum and Glx higher in the cerebellum (5.73 i.u.) and basal ganglia (5.16 i.u.), with lowest concentrations in the frontal lobe. Metabolite concentrations correlated positively with advancing PMA and postnatal age at MRI (Spearman's rho 0.2-0.6). Basal ganglia Glx and NAA, and frontal GABA+ and NAA concentrations were lower in preterm compared with term infants. Moderate preterm infants had lower metabolite concentrations than term and extreme preterm infants. Our findings emphasize the impact of premature extra-uterine stimuli on GABA-glutamate system development and may serve as early biomarkers of neurodevelopmental deficits.

Psychological distress among postpartum women who took opioids during pregnancy: the role of perceived stigma in healthcare settings.

This study examined the relationship between perceived stigma in healthcare settings during pregnancy and psychological distress and well-being in the postpartum period among individuals who took opioids while pregnant. Analyses included 134 birth mothers of opioid-exposed infants. At 0-1 months postpartum, perceived stigma and psychological distress were measured using the Prenatal Opioid use Perceived Stigma scale and measures from the Patient-Reported Outcome Measurement Information System (PROMIS). Food insecurity, housing instability, and Adverse Childhood Experiences (ACEs) were also assessed. Linear and generalized linear mixed-effect models were conducted to compare PROMIS scale scores and unmet needs by stigma, adjusting for site/location, age, race/ethnicity, marital status, education, public insurance, and parity. More than half of participants (54%) perceived stigma in healthcare settings. Individuals reporting stigma had higher depression, anxiety, and anger scores (p < 0.001) indicating greater psychological distress in the postpartum period compared to those reporting no stigma, after controlling for demographic characteristics. In addition, they scored significantly lower on the PROMIS meaning and purpose scale, an indicator of well-being (p = 0.002). Those reporting stigma were more likely to have food insecurity (p = 0.003), three or more ACEs (p = 0.040), verbal or physical abuse during pregnancy (p < 0.001), and less emotional support (p = 0.006) than those who did not. An association was observed between perceived stigma in the prenatal period and psychological distress in the postpartum period, providing support for stigma reduction interventions and education for healthcare providers on trauma-informed care.

Feasibility and success of a non-sedated brain MRI training protocol in 7-year-old children from rural and semi-rural Colombia.

BACKGROUND: Brain magnetic resonance imaging (MRI) is a crucial tool for clinical evaluation of the brain and neuroscience research. Obtaining successful non-sedated MRI in children who live in resource-limited settings may be an additional challenge. OBJECTIVE: To present a feasibility study of a novel, low-cost MRI training protocol used in a clinical research study in a rural/semi-rural region of Colombia and to examine neurodevelopmental factors associated with successful scans. MATERIALS AND METHODS: Fifty-seven typically developing Colombian children underwent a training protocol and non-sedated brain MRI at age 7. Group training utilized a customized booklet, an MRI toy set, and a simple mock scanner. Children attended MRI visits in small groups of two to three. Resting-state functional and structural images were acquired on a 1.5-Tesla scanner with a protocol duration of 30-40 minutes. MRI success was defined as the completion of all sequences and no more than mild motion artifact. Associations between the Wechsler Preschool and Primary Scale of Intelligence (WPPSI), Movement Assessment Battery for Children (MABC), Behavioral Rating Inventory of Executive Function (BRIEF), Child Behavior Checklist (CBCL), and Adaptive Behavior Assessment System (ABAS) scores and MRI success were analyzed. RESULTS: Mean (SD) age at first MRI attempt was 7.2 (0.2) years (median 7.2 years, interquartile range 7.1-7.3 years). Twenty-six (45.6%) participants were male. Fifty-one (89.5%) children were successful across two attempts; 44 (77.2%) were successful on their first attempt. Six (10.5%) were unsuccessful due to refusal or excessive motion. Age, sex, and scores across all neurodevelopmental assessments (MABC, TVIP, ABAS, BRIEF, CBCL, NIH Toolbox Flanker, NIH Toolbox Pattern Comparison, WPPSI) were not associated with likelihood of MRI success (P=0.18, 0.19, 0.38, 0.92, 0.84, 0.80, 1.00, 0.16, 0.75, 0.86, respectively). CONCLUSION: This cohort of children from a rural/semi-rural region of Colombia demonstrated comparable MRI success rates to other published cohorts after completing a low-cost MRI familiarization training protocol suitable for low-resource settings. Achieving non-sedated MRI success in children in low-resource and international settings is important for the continuing diversification of pediatric research studies.

Systematic evaluation of head motion on resting-state functional connectivity MRI in the neonate.

Reliability and robustness of resting state functional connectivity MRI (rs-fcMRI) relies, in part, on minimizing the influence of head motion on measured brain signals. The confounding effects of head motion on functional connectivity have been extensively studied in adults, but its impact on newborn brain connectivity remains unexplored. Here, using a large newborn data set consisting of 159 rs-fcMRI scans acquired in the Developing Brain Institute at Children's National Hospital and 416 scans from The Developing Human Connectome Project (dHCP), we systematically investigated associations between head motion and rs-fcMRI. Head motion during the scan significantly affected connectivity at sensory-related networks and default mode networks, and at the whole brain scale; the direction of motion effects varied across the whole brain. Comparing high- versus low-head motion groups suggested that head motion can impact connectivity estimates across the whole brain. Censoring of high-motion volumes using frame-wise displacement significantly reduced the confounding effects of head motion on neonatal rs-fcMRI. Lastly, in the dHCP data set, we demonstrated similar persistent associations between head motion and network connectivity despite implementing a standard denoising strategy. Collectively, our results highlight the importance of using rigorous head motion correction in preprocessing neonatal rs-fcMRI to yield reliable estimates of brain activity.

Experience of early-life pain in premature infants is associated with atypical cerebellar development and later neurodevelopmental deficits.

BACKGROUND: Infants born very and extremely premature (V/EPT) are at a significantly elevated risk for neurodevelopmental disorders and delays even in the absence of structural brain injuries. These risks may be due to earlier-than-typical exposure to the extrauterine environment, and its bright lights, loud noises, and exposures to painful procedures. Given the relative underdeveloped pain modulatory responses in these infants, frequent pain exposures may confer risk for later deficits. METHODS: Resting-state fMRI scans were collected at term equivalent age from 148 (45% male) infants born V/EPT and 99 infants (56% male) born at term age. Functional connectivity analyses were performed between functional regions correlating connectivity to the number of painful skin break procedures in the NICU, including heel lances, venipunctures, and IV placements. Subsequently, preterm infants returned at 18 months, for neurodevelopmental follow-up and completed assessments for autism risk and general neurodevelopment. RESULTS: We observed that V/EPT infants exhibit pronounced hyperconnectivity within the cerebellum and between the cerebellum and both limbic and paralimbic regions correlating with the number of skin break procedures. Moreover, skin breaks were strongly associated with autism risk, motor, and language scores at 18 months. Subsample analyses revealed that the same cerebellar connections strongly correlating with breaks at term age were associated with language dysfunction at 18 months. CONCLUSIONS: These results have significant implications for the clinical care of preterm infants undergoing painful exposures during routine NICU care, which typically occurs without anesthesia. Repeated pain exposures appear to have an increasingly detrimental effect on brain development during a critical period, and effects continue to be seen even 18 months later.

Rapid anatomical imaging of the neonatal brain using T2 -prepared 3D balanced steady-state free precession.

PURPOSE: To develop a new approach to 3D gradient echo-based anatomical imaging of the neonatal brain with a substantially shorter scan time than standard 3D fast spin echo (FSE) methods, while maintaining a high SNR. METHODS: T2 -prepration was employed immediately prior to image acquisition of 3D balanced steady-state free precession (bSSFP) with a single trajectory of center-out k-space view ordering, which requires no magnetization recovery time between imaging segments during the scan. This approach was compared with 3D FSE, 2D single-shot FSE, and product 3D bSSFP imaging in numerical simulations, plus phantom and in vivo experiments. RESULTS: T2 -prepared 3D bSSFP generated image contrast of gray matter, white matter, and CSF very similar to that of reference T2 -weighted imaging methods, without major image artifacts. Scan time of T2 -prepared 3D bSSFP was remarkably shorter compared to 3D FSE, whereas SNR was comparable to that of 3D FSE and higher than that of 2D single-shot FSE. Specific absorption rate of T2 -prepared 3D bSSFP remained within the safety limit. Determining an optimal imaging flip angle of T2 -prepared 3D bSSFP was critical to minimizing blurring of images. CONCLUSION: T2 -prepared 3D bSSFP offers an alternative method for anatomical imaging of the neonatal brain with dramatically reduced scan time compared to standard 3D FSE and higher SNR than 2D single-shot FSE.

Outcomes of Babies with Opioid Exposure (OBOE): protocol of a prospective longitudinal cohort study.

BACKGROUND: While the health, social, and economic impacts of opioid addiction on adults and their communities are well known, the impact of maternal opioid use on the fetus exposed in utero is less well understood. METHODS: This paper presents the protocol of the ACT NOW Outcomes of Babies with Opioid Exposure (OBOE) Study, a multi-site prospective longitudinal cohort study of infants with antenatal opioid exposure and unexposed controls. Study objectives are to determine the impact of antenatal opioid exposure on brain development and neurodevelopmental outcomes over the first 2 years of life and explore whether family, home, and community factors modify developmental trajectories during this critical time period. RESULTS: Primary outcomes related to brain development include cortical volumes, deep cerebral gray matter volumes, resting-state functional connectivity measures, and structural connectivity measures using diffusion tensor imaging. Primary neurodevelopmental outcomes include visual abnormalities, cognitive, language, and motor skills measured using the Bayley Scales of Infant Development and social-emotional and behavioral problems and competence measured by the Brief Infant-Toddler Social and Emotional Assessment. CONCLUSIONS: The OBOE study has been designed to overcome challenges of previous studies and will help further understanding of the effects of antenatal opioid exposure on early infant development. IMPACT: This study will integrate MRI findings and comprehensive neurodevelopmental assessments to provide early insights into the functional topography of the brain in this high-risk population and assess MRI as a potential biomarker. Rather than conducting neuroimaging at a single time point, the study will include serial MRI assessments from birth to 2 years, allowing for the examination of trajectories throughout this period of rapid brain development. While previous studies often have had limited information on exposures, this study will use umbilical cord assays to accurately measure amounts of opioids and other substances from 20 weeks of gestation to birth.

Impaired in vivo feto-placental development is associated with neonatal neurobehavioral outcomes.

BACKGROUND: Fetal growth restriction (FGR) is a risk factor for neurodevelopmental problems, yet remains poorly understood. We sought to examine the relationship between intrauterine development and neonatal neurobehavior in pregnancies diagnosed with antenatal FGR. METHODS: We recruited women with singleton pregnancies diagnosed with FGR and measured placental and fetal brain volumes using MRI. NICU Network Neurobehavioral Scale (NNNS) assessments were performed at term equivalent age. Associations between intrauterine volumes and neurobehavioral outcomes were assessed using generalized estimating equation models. RESULTS: We enrolled 44 women diagnosed with FGR who underwent fetal MRI and 28 infants underwent NNNS assessments. Placental volumes were associated with increased self-regulation and decreased excitability; total brain, brainstem, cortical and subcortical gray matter (SCGM) volumes were positively associated with higher self-regulation; SCGM also was positively associated with higher quality of movement; increasing cerebellar volumes were positively associated with attention, decreased lethargy, non-optimal reflexes and need for special handling; brainstem volumes also were associated with decreased lethargy and non-optimal reflexes; cerebral and cortical white matter volumes were positively associated with hypotonicity. CONCLUSION: Disrupted intrauterine growth in pregnancies complicated by antenatally diagnosed FGR is associated with altered neonatal neurobehavior. Further work to determine long-term neurodevelopmental impacts is warranted. IMPACT: Fetal growth restriction is a risk factor for adverse neurodevelopment, but remains difficult to accurately identify. Intrauterine brain volumes are associated with infant neurobehavior. The antenatal diagnosis of fetal growth restriction is a risk factor for abnormal infant neurobehavior.

In Utero MRI Identifies Impaired Second Trimester Subplate Growth in Fetuses with Congenital Heart Disease.

The subplate is a transient brain structure which plays a key role in the maturation of the cerebral cortex. Altered brain growth and cortical development have been suggested in fetuses with complex congenital heart disease (CHD) in the third trimester. However, at an earlier gestation, the putative role of the subplate in altered brain development in CHD fetuses is poorly understood. This study aims to examine subplate growth (i.e., volume and thickness) and its relationship to cortical sulcal development in CHD fetuses compared with healthy fetuses by using 3D reconstructed fetal magnetic resonance imaging. We studied 260 fetuses, including 100 CHD fetuses (22.3-32 gestational weeks) and 160 healthy fetuses (19.6-31.9 gestational weeks). Compared with healthy fetuses, CHD fetuses had 1) decreased global and regional subplate volumes and 2) decreased subplate thickness in the right hemisphere overall, in frontal and temporal lobes, and insula. Compared with fetuses with two-ventricle CHD, those with single-ventricle CHD had reduced subplate volume and thickness in right occipital and temporal lobes. Finally, impaired subplate growth was associated with disturbances in cortical sulcal development in CHD fetuses. These findings suggested a potential mechanistic pathway and early biomarker for the third-trimester failure of brain development in fetuses with complex CHD. SIGNIFICANCE STATEMENT: Our findings provide an early biomarker for brain maturational failure in fetuses with congenital heart disease, which may guide the development of future prenatal interventions aimed at reducing neurological compromise of prenatal origin in this high-risk population.

Hippocampal rotation is associated with ventricular atrial size.

BACKGROUND: Fetal ventriculomegaly is a source of apprehension for expectant parents and may present prognostic uncertainty for physicians. Accurate prenatal counseling requires knowledge of its cause and associated findings as the differential diagnosis is broad. We have observed an association between ventriculomegaly and incomplete hippocampal inversion. OBJECTIVE: To determine whether ventricular size is related to incomplete hippocampal inversion. MATERIALS AND METHODS: We retrospectively evaluated pre- and postnatal brain MRIs in normal subjects (mean GA, 31 weeks; mean postnatal age, 27 days) and patients with isolated ventriculomegaly (mean GA, 31 weeks; mean postnatal age, 68 days) at a single academic medical center. Lateral ventricular diameter, multiple qualitative and quantitative markers of hippocampal inversion, and evidence of intraventricular hemorrhage were documented. RESULTS: Incomplete hippocampal inversion and ventricular size were associated in both normal subjects (n=51) and patients with ventriculomegaly (n=32) (P<0.05). Severe ventriculomegaly was significantly associated with adverse clinical outcome in postnatal (P=0.02) but not prenatal (P=0.43) groups. In all additional cases of isolated ventriculomegaly, clinical outcome was normal over the time of assessment (mean 1±1.9 years; range 0.01 to 10 years). CONCLUSION: Lateral ventricular atrial diameter and incomplete hippocampal inversion are associated. Less hippocampal inversion correlates with larger atria. For every 1-mm increase in fetal ventricular size, the odds of incomplete hippocampal inversion occurring increases by a factor of 1.6 in normal controls and 1.4 in patients with ventriculomegaly.

Automatic brain segmentation in preterm infants with post-hemorrhagic hydrocephalus using 3D Bayesian U-Net.

Post-hemorrhagic hydrocephalus (PHH) is a severe complication of intraventricular hemorrhage (IVH) in very preterm infants. PHH monitoring and treatment decisions rely heavily on manual and subjective two-dimensional measurements of the ventricles. Automatic and reliable three-dimensional (3D) measurements of the ventricles may provide a more accurate assessment of PHH, and lead to improved monitoring and treatment decisions. To accurately and efficiently obtain these 3D measurements, automatic segmentation of the ventricles can be explored. However, this segmentation is challenging due to the large ventricular anatomical shape variability in preterm infants diagnosed with PHH. This study aims to (a) propose a Bayesian U-Net method using 3D spatial concrete dropout for automatic brain segmentation (with uncertainty assessment) of preterm infants with PHH; and (b) compare the Bayesian method to three reference methods: DenseNet, U-Net, and ensemble learning using DenseNets and U-Nets. A total of 41 T2 -weighted MRIs from 27 preterm infants were manually segmented into lateral ventricles, external CSF, white and cortical gray matter, brainstem, and cerebellum. These segmentations were used as ground truth for model evaluation. All methods were trained and evaluated using 4-fold cross-validation and segmentation endpoints, with additional uncertainty endpoints for the Bayesian method. In the lateral ventricles, segmentation endpoint values for the DenseNet, U-Net, ensemble learning, and Bayesian U-Net methods were mean Dice score = 0.814 ± 0.213, 0.944 ± 0.041, 0.942 ± 0.042, and 0.948 ± 0.034 respectively. Uncertainty endpoint values for the Bayesian U-Net were mean recall = 0.953 ± 0.037, mean  negative predictive value = 0.998 ± 0.005, mean accuracy = 0.906 ± 0.032, and mean AUC = 0.949 ± 0.031. To conclude, the Bayesian U-Net showed the best segmentation results across all methods and provided accurate uncertainty maps. This method may be used in clinical practice for automatic brain segmentation of preterm infants with PHH, and lead to better PHH monitoring and more informed treatment decisions.

In infants with congenital heart disease autonomic dysfunction is associated with pre-operative brain injury.

BACKGROUND: Brain injury is a serious and common complication of critical congenital heart disease (CHD). Impaired autonomic development (assessed by heart rate variability (HRV)) is associated with brain injury in other high-risk neonatal populations. OBJECTIVE: To determine whether impaired early neonatal HRV is associated with pre-operative brain injury in CHD. METHODS: In infants with critical CHD, we evaluated HRV during the first 24 h of cardiac ICU (CICU) admission using time-domain (RMS 1, RMS 2, and alpha 1) and frequency-domain metrics (LF, nLF, HF, nHF). Pre-operative brain magnetic resonance imaging (MRI) was scored for injury using an established system. Spearman's correlation coefficient was used to determine the association between HRV and pre-operative brain injury. RESULTS: We enrolled 34 infants with median birth gestational age of 38.8 weeks (IQR 38.1-39.1). Median postnatal age at pre-operative brain MRI was 2 days (IQR 1-3 days). Thirteen infants had MRI evidence of brain injury. RMS 1 and RMS 2 were inversely correlated with pre-operative brain injury. CONCLUSIONS: Time-domain metrics of autonomic function measured within the first 24 h of admission to the CICU are associated with pre-operative brain injury, and may perform better than frequency-domain metrics under non-stationary conditions such as critical illness. IMPACT: Autonomic dysfunction, measured by heart rate variability (HRV), in early transition is associated with pre-operative brain injury in neonates with critical congenital heart disease. These data extend our earlier findings by providing further evidence for (i) autonomic dysfunction in infants with CHD, and (ii) an association between autonomic dysfunction and brain injury in critically ill neonates. These data support the notion that further investigation of HRV as a biomarker for brain injury risk is warranted in infants with critical CHD.

Global Network Organization of the Fetal Functional Connectome.

Recent advances in brain imaging have enabled non-invasive in vivo assessment of the fetal brain. Characterizing brain development in healthy fetuses provides baseline measures for identifying deviations in brain function in high-risk clinical groups. We examined 110 resting state MRI data sets from fetuses at 19 to 40 weeks' gestation. Using graph-theoretic techniques, we characterized global organizational features of the fetal functional connectome and their prenatal trajectories. Topological features related to network integration (i.e., global efficiency) and segregation (i.e., clustering) were assessed. Fetal networks exhibited small-world topology, showing high clustering and short average path length relative to reference networks. Likewise, fetal networks' quantitative small world indices met criteria for small-worldness (σ > 1, ω = [-0.5 0.5]). Along with this, fetal networks demonstrated global and local efficiency, economy, and modularity. A right-tailed degree distribution, suggesting the presence of central areas that are more highly connected to other regions, was also observed. Metrics, however, were not static during gestation; measures associated with segregation-local efficiency and modularity-decreased with advancing gestational age. Altogether, these suggest that the neural circuitry underpinning the brain's ability to segregate and integrate information exists as early as the late 2nd trimester of pregnancy and reorganizes during the prenatal period. Significance statement. Mounting evidence for the fetal origins of some neurodevelopmental disorders underscores the importance of identifying features of healthy fetal brain functional development. Alterations in prenatal brain connectomics may serve as early markers for identifying fetal-onset neurodevelopmental disorders, which in turn provide improved surveillance of at-risk fetuses and support the initiation of early interventions.