Longitudinal study of neonatal brain tissue volumes in preterm infants and their ability to predict neurodevelopmental outcome

Synthetic magnetic resonance-based relaxometry and brain volume: cutoff values for predicting neurocognitive outcomes in very preterm infants

BACKGROUND

Early neurorehabilitation can enhance neurocognitive outcomes in very preterm infants (<32 weeks), and conventional magnetic resonance imaging (MRI) is commonly used to assess neonatal brain injury; however, the predictive value for neurodevelopmental delay is limited. Timely predictive quantitative biomarkers are needed to improve early identification and management of infants at risk of neurodevelopmental delay.

OBJECTIVE

To evaluate the potential of quantitative synthetic MRI measurements at term-equivalent age as predictive biomarkers of neurodevelopmental impairment and establish practical cutoff values to guide clinical decision-making.

MATERIALS AND METHODS

This retrospective study included 93 very preterm infants who underwent synthetic MRI at term-equivalent age between January 2017 and September 2020. Clinical outcomes were assessed using the Bayley-III scale of infant development (mean age 2.1 years). The predictive value for impaired development was analyzed using receiver operating characteristic curves for synthetic MRI-based volumetry and T1 and T2 relaxation measurements.

RESULTS

The T1 relaxation time in the posterior limb of the internal capsule was a potent predictor of severe (sensitivity, 92%; specificity, 80%; area under the curve (AUC), 0.91) and mild or severe (AUC, 0.75) developmental impairment. T2 relaxation time in the posterior limb of the internal capsule was a significant predictor of severe impairment (AUC, 0.76), whereas the brain parenchymal volume was a significant predictor of severe (AUC, 0.72) and mild or severe impairment (AUC, 0.71) outperforming the reported qualitative MRI scores (AUC, 0.66).

CONCLUSION

The proposed cutoff values for T1 relaxation time in the posterior limb of the internal capsule and for total brain volume measurements, derived from synthetic MRI, show promise as predictors of both mild and severe neurodevelopmental impairment in very preterm infants.

Longitudinal caregiver-reported motor development in infants born at term and preterm

AIM

To examine the extent to which estimates of a latent trait or underlying construct of motor ability differ in infants born at term and preterm, based on caregiver ratings of the motor domain of PediaTrac v3.0.

METHOD

The sample consisted of 571 caregiver-infant dyads (331 born at term, 240 born preterm), 48% female, with 51.7% of caregivers identifying as an ethnic minority. Latent trait of motor ability was estimated based on item response theory modeling. Gestational group differences (term and preterm birth) were examined at the newborn/term-equivalent, 2-, 4-, 6-, 9-, and 12-month time points.

RESULTS

Caregiver ratings of latent trait of motor ability were reliably modeled across the range of abilities at each time point. While the group born preterm exhibited significantly more advanced motor abilities at the term-equivalent time point, by 6 months the group born at term was more advanced. Biological sex difference main and interaction effects were not significant.

INTERPRETATION

Caregivers provided reliable, longitudinal estimates of motor ability in infancy, reflecting important differences in the motor development of infants born at term and preterm. The findings suggest that significant motor development occurs in infants born preterm from birth to the term-equivalent time point and provide a foundation to examine motor growth trajectories as potential predictors in the early identification of neurodevelopmental conditions and needs.

WHAT THIS PAPER ADDS

Longitudinal caregiver ratings of motor function in early infancy yielded reliable estimates of the latent trait of motor ability. Motor ability at the term-equivalent time point was higher in infants born preterm than infants born at term.

A regional brain volume-based age prediction model for neonates and the derived brain maturation index

OBJECTIVE

To develop a postmenstrual age (PMA) prediction model based on segmentation volume and to evaluate the brain maturation index using the proposed model.

METHODS

Neonatal brain MRIs without clinical illness or structural abnormalities were collected from four datasets from the Developing Human Connectome Project, the Catholic University of Korea, Hammersmith Hospital (HS), and Dankook University Hospital (DU). T1- and T2-weighted images were used to train a brain segmentation model. Another model to predict the PMA of neonates based on segmentation data was developed. Accuracy was assessed using mean absolute error (MAE), root mean square error (RMSE), and mean error (ME). The brain maturation index was calculated as the difference between the PMA predicted by the model and the true PMA, and its correlation with postnatal age was analyzed.

RESULTS

A total of 247 neonates (mean gestation age 37 ± 4 weeks; range 24-42 weeks) were included. Thirty-one features were extracted from each neonate and the three most contributing features for PMA prediction were the right lateral ventricle, left caudate, and corpus callosum. The predicted and true PMA were positively correlated (coefficient = 0.88, p < .001). MAE, RMSE, and ME of the external dataset of HS and DU were 1.57 and 1.33, 1.79 and 1.37, and 0.37 and 0.06 weeks, respectively. The brain maturation index negatively correlated with postnatal age (coefficient =  - 0.24, p < .001).

CONCLUSION

A model that calculates the regional brain volume can predict the PMA of neonates, which can then be utilized to show the brain maturation degree.

CLINICAL RELEVANCE STATEMENT

A brain maturity index based on regional volume of neonate's brain can be used to measure brain maturation degree, which can help identify the status of early brain development.

KEY POINTS

• Neonatal brain MRI segmentation model could be used to assess neonatal brain maturation status. • A postmenstrual age (PMA) prediction model was developed based on a neonatal brain MRI segmentation model. • The brain maturation index, derived from the PMA prediction model, enabled the estimation of the neonatal brain maturation status.

Severe Bronchopulmonary Dysplasia Adversely Affects Brain Growth in Preterm Infants

INTRODUCTION

Bronchopulmonary dysplasia (BPD) is associated with neurodevelopmental outcomes of preterm infants, but its effect on brain growth in preterm infants after the neonatal period is unknown. This study aimed to evaluate the effect of severe BPD on brain growth of preterm infants from term to 18 months of corrected age (CA).

METHODS

Sixty-three preterm infants (42 with severe BPD and 21 without severe BPD) who underwent magnetic resonance imaging at term equivalent age (TEA) and 18 months of CA were studied by using the Infant Brain Extraction and Analysis Toolbox (iBEAT). We measured segmented brain volumes and compared brain volume and brain growth velocity between the severe BPD group and the non-severe BPD group.

RESULTS

There was no significant difference in brain volumes at TEA between the groups. However, the brain volumes of the total brain and cerebral white matter in the severe BPD group were significantly smaller than those in the non-severe BPD group at 18 months of CA. The brain growth velocities from TEA to 18 months of CA in the total brain, cerebral cortex, and cerebral white matter in the severe BPD group were lower than those in the non-severe BPD group.

CONCLUSION

Brain growth in preterm infants with severe BPD from TEA age to 18 months of CA is less than that in preterm infants without severe BPD.

Treatments and regulatory mechanisms of acoustic stimuli on mood disorders and neurological diseases

Acoustic stimuli such as music or ambient noise can significantly affect physiological and psychological health in humans. We here summarize positive effects of music therapy in premature infant distress regulation, performance enhancement, sleep quality control, and treatment of mental disorders. Specifically, music therapy exhibits promising effects on treatment of neurological disorders such as Alzheimer's disease (AD) and Parkinson's disease (PD). We also highlight regulatory mechanisms by which auditory intervention affects an organism, encompassing modulation of immune responses, gene expression, neurotransmitter regulation and neural circuitry. As a safe, cost-effective and non-invasive intervention, music therapy offers substantial potential in treating a variety of neurological conditions.

Diagnostic performance of synthetic relaxometry for predicting neurodevelopmental outcomes in premature infants: a feasibility study

OBJECTIVES

To investigate the predictability of synthetic relaxometry for neurodevelopmental outcomes in premature infants and to evaluate whether a combination of relaxation times with clinical variables or qualitative MRI abnormalities improves the predictive performance.

METHODS

This retrospective study included 33 premature infants scanned with synthetic MRI near or at term equivalent age. Based on neurodevelopmental assessments at 18-24 months of corrected age, infants were classified into two groups (no/mild disability [n = 23] vs. moderate/severe disability [n = 10]). Clinical and MRI characteristics associated with moderate/severe disability were explored, and combined models incorporating independent predictors were established. Ultimately, the predictability of relaxation times, clinical variables, MRI findings, and a combination of the two were evaluated and compared. The models were internally validated using bootstrap resampling.

RESULTS

Prolonged T1-frontal/parietal and T2-parietal periventricular white matter (PVWM), moderate-to-severe white matter abnormality, and bronchopulmonary dysplasia were significantly associated with moderate/severe disability. The overall predictive performance of each T1-frontal/-parietal PVWM model was comparable to that of individual MRI finding and clinical models (AUC = 0.71 and 0.76 vs. 0.73 vs. 0.83, respectively; p > 0.27). The combination of clinical variables and T1-parietal PVWM achieved an AUC of 0.94, sensitivity of 90%, and specificity of 91.3%, outperforming the clinical model alone (p = 0.049). The combination of MRI finding and T1-frontal PVWM yielded AUC of 0.86, marginally outperforming the MRI finding model (p = 0.09). Bootstrap resampling showed that the models were valid.

CONCLUSIONS

It is feasible to predict adverse outcomes in premature infants by using early synthetic relaxometry. Combining relaxation time with clinical variables or MRI finding improved prediction.

CLINICAL RELEVANCE STATEMENT

Synthetic relaxometry performed during the neonatal period may serve as a biomarker for predicting adverse neurodevelopmental outcomes in premature infants.

KEY POINTS

• Synthetic relaxometry based on T1 relaxation time of parietal periventricular white matter showed acceptable performance in predicting adverse outcome with an AUC of 0.76 and an accuracy of 78.8%. • The combination of relaxation time with clinical variables and/or structural MRI abnormalities improved predictive performance of adverse outcomes. • Synthetic relaxometry performed during the neonatal period helps predict adverse neurodevelopmental outcome in premature infants.

Correlation of NICU anthropometry in extremely preterm infants with brain development and language scores at early school age

Growth in preterm infants in the neonatal intensive care unit (NICU) is associated with increased global and regional brain volumes at term, and increased postnatal linear growth is associated with higher language scores at age 2. It is unknown whether these relationships persist to school age or if an association between growth and cortical metrics exists. Using regression analyses, we investigated relationships between the growth of 42 children born extremely preterm (< 28 weeks gestation) from their NICU hospitalization, standardized neurodevelopmental/language assessments at 2 and 4-6 years, and multiple neuroimaging biomarkers obtained from T1-weighted images at 4-6 years. We found length at birth and 36 weeks post-menstrual age had positive associations with language scores at 2 years in multivariable linear regression. No growth metric correlated with 4-6 year assessments. Weight and head circumference at 36 weeks post-menstrual age positively correlated with total brain volume and negatively with global cortical thickness at 4-6 years of age. Head circumference relationships remained significant after adjusting for age, sex, and socioeconomic status. Right temporal cortical thickness was related to receptive language at 4-6 years in the multivariable model. Results suggest growth in the NICU may have lasting effects on brain development in extremely preterm children.

Determining regional brain growth in premature and mature infants in relation to age at MRI using deep neural networks

Neonatal MRIs are used increasingly in preterm infants. However, it is not always feasible to analyze this data. Having a tool that assesses brain maturation during this period of extraordinary changes would be immensely helpful. Approaches based on deep learning approaches could solve this task since, once properly trained and validated, they can be used in practically any system and provide holistic quantitative information in a matter of minutes. However, one major deterrent for radiologists is that these tools are not easily interpretable. Indeed, it is important that structures driving the results be detailed and survive comparison to the available literature. To solve these challenges, we propose an interpretable pipeline based on deep learning to predict postmenstrual age at scan, a key measure for assessing neonatal brain development. For this purpose, we train a state-of-the-art deep neural network to segment the brain into 87 different regions using normal preterm and term infants from the dHCP study. We then extract informative features for brain age estimation using the segmented MRIs and predict the brain age at scan with a regression model. The proposed framework achieves a mean absolute error of 0.46 weeks to predict postmenstrual age at scan. While our model is based solely on structural T2-weighted images, the results are superior to recent, arguably more complex approaches. Furthermore, based on the extracted knowledge from the trained models, we found that frontal and parietal lobes are among the most important structures for neonatal brain age estimation.

Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer

Predictive models in neuroimaging are increasingly designed with the intent to improve risk stratification and support interventional efforts in psychiatry. Many of these models have been developed in samples of children school-aged or older. Nevertheless, despite growing evidence that altered brain maturation during the fetal, infant, and toddler (FIT) period modulates risk for poor mental health outcomes in childhood, these models are rarely implemented in FIT samples. Applications of predictive modeling in children of these ages provide an opportunity to develop powerful tools for improved characterization of the neural mechanisms underlying development. To facilitate the broader use of predictive models in FIT neuroimaging, we present a brief primer and systematic review on the methods used in current predictive modeling FIT studies. Reflecting on current practices in more than 100 studies conducted over the past decade, we provide an overview of topics, modalities, and methods commonly used in the field and under-researched areas. We then outline ethical and future considerations for neuroimaging researchers interested in predicting health outcomes in early life, including researchers who may be relatively new to either advanced machine learning methods or using FIT data. Altogether, the last decade of FIT research in machine learning has provided a foundation for accelerating the prediction of early-life trajectories across the full spectrum of illness and health.

Music impacts brain cortical microstructural maturation in very preterm infants: A longitudinal diffusion MR imaging study

Preterm birth disrupts important neurodevelopmental processes occurring from mid-fetal to term-age. Musicotherapy, by enriching infants' sensory input, might enhance brain maturation during this critical period of activity-dependent plasticity. To study the impact of music on preterm infants' brain structural changes, we recruited 54 very preterm infants randomized to receive or not a daily music intervention, that have undergone a longitudinal multi-shell diffusion MRI acquisition, before the intervention (at 33 weeks' gestational age) and after it (at term-equivalent-age). Using whole-brain fixel-based (FBA) and NODDI analysis (n = 40), we showed a longitudinal increase of fiber cross-section (FC) and fiber density (FD) in all major cerebral white matter fibers. Regarding cortical grey matter, FD decreased while FC and orientation dispersion index (ODI) increased, reflecting intracortical multidirectional complexification and intracortical myelination. The music intervention resulted in a significantly higher longitudinal increase of FC and ODI in cortical paralimbic regions, namely the insulo-orbito-temporopolar complex, precuneus/posterior cingulate gyrus, as well as the auditory association cortex. Our results support a longitudinal early brain macro and microstructural maturation of white and cortical grey matter in preterm infants. The music intervention led to an increased intracortical complexity in regions important for socio-emotional development, known to be impaired in preterm infants.

Association of Preterm Birth and Socioeconomic Status With Neonatal Brain Structure

Importance

Preterm birth and socioeconomic status (SES) are associated with brain structure in childhood, but the relative contributions of each during the neonatal period are unknown.

Objective

To investigate associations of birth gestational age (GA) and SES with neonatal brain morphology by testing 3 hypotheses: GA and SES are associated with brain morphology; associations between SES and brain morphology vary with GA; and associations between SES and brain structure and morphology depend on how SES is operationalized.

Design, Setting, and Participants

This cohort study recruited participants from November 2016 to September 2021 at a single center in the United Kingdom. Participants were 170 extremely and very preterm infants and 91 full-term or near-term infants. Exclusion criteria were major congenital malformation, chromosomal abnormality, congenital infection, cystic periventricular leukomalacia, hemorrhagic parenchymal infarction, and posthemorrhagic ventricular dilatation.

Exposures

Birth GA and SES, operationalized at the neighborhood level (using the Scottish Index of Multiple Deprivation), the family level (using parental education and occupation), and subjectively (World Health Organization Quality of Life measure).

Main Outcomes and Measures

Brain volume (85 parcels) and 5 whole-brain cortical morphology measures (gyrification index, thickness, sulcal depth, curvature, surface area) at term-equivalent age (median [range] age, 40 weeks, 5 days [36 weeks, 2 days to 45 weeks, 6 days] and 42 weeks [38 weeks, 2 days to 46 weeks, 1 day] for preterm and full-term infants, respectively).

Results

Participants were 170 extremely and very preterm infants (95 [55.9%] male; 4 of 166 [2.4%] Asian, 145 of 166 [87.3%] White) and 91 full-term or near-term infants (50 [54.9%] male; 3 of 86 [3.5%] Asian, 78 of 86 [90.7%] White infants) with median (range) birth GAs of 30 weeks, 0 days (22 weeks, 1 day, to 32 weeks, 6 days) and 39 weeks, 4 days (36 weeks, 3 days, to 42 weeks, 1 day), respectively. In fully adjusted models, birth GA was associated with a higher proportion of brain volumes (27 of 85 parcels [31.8%]; β range, -0.20 to 0.24) than neighborhood-level SES (1 of 85 parcels [1.2%]; β = 0.17 [95% CI, -0.16 to 0.50]) or family-level SES (maternal education: 4 of 85 parcels [4.7%]; β range, 0.09 to 0.15; maternal occupation: 1 of 85 parcels [1.2%]; β = 0.06 [95% CI, 0.02 to 0.11] respectively). There were interactions between GA and both family-level and subjective SES measures on regional brain volumes. Birth GA was associated with cortical surface area (β = 0.10 [95% CI, 0.02 to 0.18]) and gyrification index (β = 0.16 [95% CI, 0.07 to 0.25]); no SES measure was associated with cortical measures.

Conclusions and Relevance

In this cohort study of UK infants, birth GA and SES were associated with neonatal brain morphology, but low GA had more widely distributed associations with neonatal brain structure than SES. Further work is warranted to elucidate the mechanisms underlying the association of both GA and SES with early brain development.

[Oxytocin: a new target for neuroprotection?]

Every year, 30 million infants worldwide are delivered after intra-uterine growth restriction (IUGR) and 15 million are born preterm. These two conditions are the leading causes of ante-/perinatal stress and brain injury responsible for neurocognitive and behavioral disorders affecting more than 9 million children each year. Most pharmacological candidates to prevent perinatal brain damage have failed to demonstrate substantial benefits. In contrast, environment enrichment based on developmental care, skin-to-skin contact and vocal/music exposure appear to exert positive effects on brain structure and function. However, mechanisms underlying these effects remain unknown. There is strong evidence that an adverse environment during pregnancy and the neonatal period can influence hormonal responses of the newborn with long-lasting neurobehavioral consequences in infancy and adulthood. In particular, excessive cortisol release in response to perinatal stress associated with prematurity or IUGR is recognized to induce brain-programming effects and neuroinflammation, a key predictor of subsequent neurological impairments. These deleterious effects are known to be balanced by oxytocin (OT), a neuropeptide released by the hypothalamus, which plays a role during the perinatal period and in social behavior. In addition, preclinical studies suggest that OT is able to regulate the central inflammatory response to injury in the adult brain. Using a rodent model of IUGR associated with developing white matter damage, we recently reported that carbetocin, a brain permeable OT receptor (OTR) agonist, induced a significant reduction of activated microglia, the primary immune cells of the brain. Moreover, this reduced microglia reactivity was associated with long-term neuroprotection. These findings make OT a promising candidate for neonatal neuroprotection through neuroinflammation regulation. However, the mechanisms linking endogenous OT and central inflammation response to injury have not yet been established. Further studies are needed to assess the protective role of OT in the developing brain through modulation of microglial activation, a key feature of brain injury observed in infants born preterm or growth-restricted. They are expected to have several impacts in the near future not only for improving knowledge of microglial cell physiology and reactivity during brain development, but also to design clinical trials testing interventions associated with endogenous OT release as a relevant strategy to alleviate neuroinflammation in neonates.

Behavioral outcome of very preterm children at 5 years of age: Prognostic utility of brain tissue volumes at term-equivalent-age, perinatal, and environmental factors

OBJECTIVE

Prematurity is associated with a high risk of long-term behavioral problems. This study aimed to assess the prognostic utility of volumetric brain data at term-equivalent-age (TEA), clinical perinatal factors, and parental social economic risk in the prediction of the behavioral outcome at 5 years in a cohort of very preterm infants (VPT, <32 gestational weeks).

METHODS

T2-weighted magnetic resonance brain images of 80 VPT children were acquired at TEA and automatically segmented into cortical gray matter, deep subcortical gray matter, white matter (WM), cerebellum (CB), and cerebrospinal fluid. The gray matter structure of the amygdala was manually segmented. Children were examined at 5 years of age with a behavioral assessment, using the strengths and difficulties questionnaire (SDQ). The utility of brain volumes at TEA, perinatal factors, and social economic risk for the prediction of behavioral outcome was investigated using support vector machine classifiers and permutation feature importance.

RESULTS

The predictive modeling of the volumetric data showed that WM, amygdala, and CB volumes were the best predictors of the SDQ emotional symptoms score. Among the perinatal factors, sex, sepsis, and bronchopulmonary dysplasia were the best predictors of the hyperactivity/inattention score. When combining the social economic risk with volumetric and perinatal factors, we were able to accurately predict the emotional symptoms score. Finally, social economic risk was positively correlated with the scores of conduct problems and peer problems.

CONCLUSIONS

This study provides information on the relation between brain structure at TEA and clinical perinatal factors with behavioral outcome at age 5 years in VPT children. Nevertheless, the overall predictive power of our models is relatively modest, and further research is needed to identify factors associated with subsequent behavioral problems in this population.

Spatiotemporal Developmental Gradient of Thalamic Morphology, Microstructure, and Connectivity fromthe Third Trimester to Early Infancy

Thalamus is a critical component of the limbic system that is extensively involved in both basic and high-order brain functions. However, how the thalamic structure and function develops at macroscopic and microscopic scales during the perinatal period development is not yet well characterized. Here, we used multishell high-angular resolution diffusion MRI of 144 preterm-born and full-term infants in both sexes scanned at 32-44 postmenstrual weeks (PMWs) from the Developing Human Connectome Project database to investigate the thalamic development in morphology, microstructure, associated connectivity, and subnucleus division. We found evident anatomic expansion and linear increases of fiber integrity in the lateral side of thalamus compared with the medial part. The tractography results indicated that thalamic connection to the frontal cortex developed later than the other thalamocortical connections (parieto-occipital, motor, somatosensory, and temporal). Using a connectivity-based segmentation strategy, we revealed that functional partitions of thalamic subdivisions were formed at 32 PMWs or earlier, and the partition developed toward the adult pattern in a lateral-to-medial pattern. Collectively, these findings revealed faster development of the lateral thalamus than the central part as well as a posterior-to-anterior developmental gradient of thalamocortical connectivity from the third trimester to early infancy.SIGNIFICANCE STATEMENT This is the first study that characterizes the spatiotemporal developmental pattern of thalamus during the third trimester to early infancy. We found that thalamus develops in a lateral-to-medial pattern for both thalamic microstructures and subdivisions; and thalamocortical connectivity develops in a posterior-to-anterior gradient that thalamofrontal connectivity appears later than the other thalamocortical connections. These findings may enrich our understanding of the developmental principles of thalamus and provide references for the atypical brain growth in neurodevelopmental disorders.

Ultrasonographic evaluation of the early brain growth pattern in very low birth weight infants

BACKGROUND

Preterm infants develop smaller brain volumes compared to term newborns. Our aim is to study early brain growth related to perinatal factors in very low birth weight infants (VLBWI).

METHODS

Manual segmentation of total brain volume (TBV) was performed in weekly 3D-ultrasonographies in our cohort of VLBWI. We studied the brain growth pattern related to term magnetic resonance image (term-MRI).

RESULTS

We found different brain growth trajectories, with smaller brain volumes and a decrease in brain growth rate in those VLBWI who would later have an abnormal term-MRI (mean TBV 190.68 vs. 213.9 cm3; P = 0.0001 and mean TBV growth rate 14.35 (±1.27) vs. 16.94 (±2.29) cm3/week; P = 0.0001). TBV in those with normal term-MRI was related to gestational age (GA), being small for gestational age (SGA), sex, and duration of parenteral nutrition (TPN) while in those with abnormal term-MRI findings it was related to GA, SGA, TPN, and comorbidities. We found a deceleration in brain growth rate in those with ≥3 comorbidities.

CONCLUSIONS

An altered brain growth pattern in VLBWI who subsequently present worst scores on term-MRI is related to GA, being SGA and comorbidities. Early ultrasonographic monitoring of TBV could be useful to detect deviated patterns of brain growth.

IMPACT STATEMENT

We describe the brain growth pattern in very low birth weight infants during their first postnatal weeks. Brain growth may be affected in the presence of certain perinatal factors and comorbidities, conditioning a deviation of the normal growth pattern. The serial ultrasound follow-up of these at-risk patients allows identifying these brain growth patterns early, which offers a window of opportunity for implementing earlier interventions.

New trends in developmental coordination disorder: Multivariate, multidimensional and multimodal

Developmental coordination disorder (DCD) is a motor development disorder that affects an individual's growth and development, and may persist throughout life. It is not caused by intellectual or physical disability. Studies have suggested DCD often occurs in childhood, resulting in a series of abnormal manifestations that hinder children's normal development; cohort studies suggest a higher incidence in boys than in girls. Early diagnosis and appropriate interventions can help relieve symptoms. Unfortunately, the relevant research still needs to be further developed. In this paper, we first start from the definition of DCD, systematically investigate the relevant research papers in the past decades and summarize the current research hotspots and research trends in this field. After summarizing, it is found that this research field has attracted more researchers to join, the number of papers published has increased year by year and has become a hot spot in multidisciplinary research, such as education, psychology, sports rehabilitation, neurobiology, and neuroimaging. The continuous development of the correlation between perinatal factors and DCD, various omics studies, and neuroimaging methods also brings new perspectives and working targets to DCD research. DCD-related research will continue to deepen along the research direction of multivariate, multidimensional, and multimodal.

The Role of Oxytocin in Abnormal Brain Development: Effect on Glial Cells and Neuroinflammation

The neonatal period is critical for brain development and determinant for long-term brain trajectory. Yet, this time concurs with a sensitivity and risk for numerous brain injuries following perinatal complications such as preterm birth. Brain injury in premature infants leads to a complex amalgam of primary destructive diseases and secondary maturational and trophic disturbances and, as a consequence, to long-term neurocognitive and behavioral problems. Neuroinflammation is an important common factor in these complications, which contributes to the adverse effects on brain development. Mediating this inflammatory response forms a key therapeutic target in protecting the vulnerable developing brain when complications arise. The neuropeptide oxytocin (OT) plays an important role in the perinatal period, and its importance for lactation and social bonding in early life are well-recognized. Yet, novel functions of OT for the developing brain are increasingly emerging. In particular, OT seems able to modulate glial activity in neuroinflammatory states, but the exact mechanisms underlying this connection are largely unknown. The current review provides an overview of the oxytocinergic system and its early life development across rodent and human. Moreover, we cover the most up-to-date understanding of the role of OT in neonatal brain development and the potential neuroprotective effects it holds when adverse neural events arise in association with neuroinflammation. A detailed assessment of the underlying mechanisms between OT treatment and astrocyte and microglia reactivity is given, as well as a focus on the amygdala, a brain region of crucial importance for socio-emotional behavior, particularly in infants born preterm.

Italian, European, and international neuroinformatics efforts: An overview

Neuroinformatics is a research field that focusses on software tools capable of identifying, analysing, modelling, organising and sharing multiscale neuroscience data. Neuroinformatics has exploded in the last two decades with the emergence of the Big Data phenomenon, characterised by the so-called 3Vs (volume, velocity and variety), which provided neuroscientists with an improved ability to acquire and process data faster and more cheaply thanks to technical improvements in clinical, genomic and radiological technologies. This situation has led to a 'data deluge', as neuroscientists can routinely collect more study data in a few days than they could in a year just a decade ago. To address this phenomenon, several neuroimaging-focussed neuroinformatics platforms have emerged, funded by national or transnational agencies, with the following goals: (i) development of tools for archiving and organising analytical data (XNAT, REDCap and LabKey); (ii) development of data-driven models evolving from reductionist approaches to multidimensional models (RIN, IVN, HBD, EuroPOND, E-DADS and GAAIN BRAIN); and (iii) development of e-infrastructures to provide sufficient computational power and storage resources (neuGRID, HBP-EBRAINS, LONI and CONP). Although the scenario is still fragmented, there are technological and economical attempts at both national and international levels to introduce high standards for open and Findable, Accessible, Interoperable and Reusable (FAIR) neuroscience worldwide.

MRI-based brain volumes of preterm infants at term: a systematic review and meta-analysis

BACKGROUND

MRI allows a detailed assessment of brain structures in preterm infants, outperforming cranial ultrasound. Neonatal MR-based brain volumes of preterm infants could serve as objective, quantitative and reproducible surrogate parameters of early brain development. To date, there are no reference values for preterm infants' brain volumes at term-equivalent age.

OBJECTIVE

Systematic review of the literature to determine reference ranges for MRI-based brain volumes of very preterm infants at term-equivalent age.

METHODS

PubMed Database was searched on 6 April 2020 for studies reporting MR-based brain volumes on representative unselected populations of very preterm and/or very low birthweight infants examined at term equivalent age (defined as 37-42 weeks mean postmenstrual age at MRI). Analyses were limited to volumetric parameters reported in >3 studies. Weighted mean volumes and SD were both calculated and simulated for each parameter.

RESULTS

An initial 367 publications were identified. Following application of exclusion criteria, 13 studies from eight countries were included for analysis, yielding four parameters. Weighted mean total brain volume was 379 mL (SD 72 mL; based on n=756). Cerebellar volume was 21 mL (6 mL; n=791), cortical grey matter volume 140 mL (47 mL; n=572) and weighted mean volume of unmyelinated white matter was 195 mL (38 mL; n=499).

CONCLUSION

This meta-analysis reports pooled data on several brain and cerebellar volumes which can serve as reference for future studies assessing MR-based volumetric parameters as a surrogate outcome for neurodevelopment and for the interpretation of individual or cohort MRI-based volumetric findings.

Associations of Macronutrient Intake Determined by Point-of-Care Human Milk Analysis with Brain Development among very Preterm Infants

Point-of-care human milk analysis is now feasible in the neonatal intensive care unit (NICU) and allows accurate measurement of macronutrient delivery. Higher macronutrient intakes over this period may promote brain growth and development. In a prospective, observational study of 55 infants born at <32 weeks’ gestation, we used a mid-infrared spectroscopy-based human milk analyzer to measure the macronutrient content in repeated samples of human milk over the NICU hospitalization. We calculated daily nutrient intakes from unfortified milk and assigned infants to quintiles based on median intakes over the hospitalization. Infants underwent brain magnetic resonance imaging at term equivalent age to quantify total and regional brain volumes and fractional anisotropy of white matter tracts. Infants in the highest quintile of energy intake from milk, as compared with the lower four quintiles, had larger total brain volume (31 cc, 95% confidence interval [CI]: 5, 56), cortical gray matter (15 cc, 95%CI: 1, 30), and white matter volume (23 cc, 95%CI: 12, 33). Higher protein intake was associated with larger total brain (36 cc, 95%CI: 7, 65), cortical gray matter (22 cc, 95%CI: 6, 38) and deep gray matter (1 cc, 95%CI: 0.1, 3) volumes. These findings suggest innovative strategies to close nutrient delivery gaps in the NICU may promote brain growth for preterm infants.

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.

Cyto/myeloarchitecture of cortical gray matter and superficial white matter in early neurodevelopment: multimodal MRI study in preterm neonates

The cerebral cortex undergoes rapid microstructural changes throughout the third trimester. Recently, there has been growing interest on imaging features that represent cyto/myeloarchitecture underlying intracortical myelination, cortical gray matter (GM), and its adjacent superficial whitematter (sWM). Using 92 magnetic resonance imaging scans from 78 preterm neonates, the current study used combined T1-weighted/T2-weighted (T1w/T2w) intensity ratio and diffusion tensor imaging (DTI) measurements, including fractional anisotropy (FA) and mean diffusivity (MD), to characterize the developing cyto/myeloarchitectural architecture. DTI metrics showed a linear trajectory: FA decreased in GM but increased in sWM with time; and MD decreased in both GM and sWM. Conversely, T1w/T2w measurements showed a distinctive parabolic trajectory, revealing additional cyto/myeloarchitectural signature inferred. Furthermore, the spatiotemporal courses were regionally heterogeneous: central, ventral, and temporal regions of GM and sWM exhibited faster T1w/T2w changes; anterior sWM areas exhibited faster FA increases; and central and cingulate areas in GM and sWM exhibited faster MD decreases. These results may explain cyto/myeloarchitectural processes, including dendritic arborization, synaptogenesis, glial proliferation, and radial glial cell organization and apoptosis. Finally, T1w/T2w values were significantly associated with 1-year language and cognitive outcome scores, while MD significantly decreased with intraventricular hemorrhage.

The role of artificial intelligence in paediatric neuroradiology

Imaging plays a fundamental role in the managing childhood neurologic, neurosurgical and neuro-oncological disease. Employing multi-parametric MRI techniques, such as spectroscopy and diffusion- and perfusion-weighted imaging, to the radiophenotyping of neuroradiologic conditions is becoming increasingly prevalent, particularly with radiogenomic analyses correlating imaging characteristics with molecular biomarkers of disease. However, integration into routine clinical practice remains elusive. With modern multi-parametric MRI now providing additional data beyond anatomy, informing on histology, biology and physiology, such metric-rich information can present as information overload to the treating radiologist and, as such, information relevant to an individual case can become lost. Artificial intelligence techniques are capable of modelling the vast radiologic, biological and clinical datasets that accompany childhood neurologic disease, such that this information can become incorporated in upfront prognostic modelling systems, with artificial intelligence techniques providing a plausible approach to this solution. This review examines machine learning approaches than can be used to underpin such artificial intelligence applications, with exemplars for each machine learning approach from the world literature. Then, within the specific use case of paediatric neuro-oncology, we examine the potential future contribution for such artificial intelligence machine learning techniques to offer solutions for patient care in the form of decision support systems, potentially enabling personalised medicine within this domain of paediatric radiologic practice.

Shape variability of the central sulcus in the developing brain: a longitudinal descriptive and predictive study in preterm infants

Despite growing evidence of links between sulcation and function in the adult brain, the folding dynamics, occurring mostly before normal-term-birth, is vastly unknown. Looking into the development of cortical sulci in infants can give us keys to address fundamental questions: what is the sulcal shape variability in the developing brain? When are the shape features encoded? How are these morphological parameters related to further functional development? In this study, we aimed to investigate the shape variability of the developing central sulcus, which is the frontier between the primary somatosensory and motor cortices. We studied a cohort of 71 extremely preterm infants scanned twice using MRI - once around 30 weeks post-menstrual age (w PMA) and once at term-equivalent age, around 40w PMA -, in order to quantify the sulcus's shape variability using manifold learning, regardless of age-group or hemisphere. We then used these shape descriptors to evaluate the sulcus's variability at both ages and to assess hemispheric and age-group specificities. This led us to propose a description of ten shape features capturing the variability in the central sulcus of preterm infants. Our results suggested that most of these features (8/10) are encoded as early as 30w PMA. We unprecedentedly observed hemispheric asymmetries at both ages, and the one captured at term-equivalent age seems to correspond with the asymmetry pattern previously reported in adults. We further trained classifiers in order to explore the predictive value of these shape features on manual performance at 5 years of age (handedness and fine motor outcome). The central sulcus's shape alone showed a limited but relevant predictive capacity in both cases. The study of sulcal shape features during early neurodevelopment may participate to a better comprehension of the complex links between morphological and functional organization of the developing brain.

Relationship between the Quantitative Indicators of Cranial MRI and the Early Neurodevelopment of Preterm Infants

Aim

To explore the relationship between the quantitative indicators (biparietal width, interhemispheric distance) of the cranial MRI for preterm infants at 37 weeks of postmenstrual age (PMA) and neurodevelopment at 6 months of corrected age.

Methods

A total of 113 preterm infants (gestational age < 37 weeks) delivered in the Obstetrics Department of the First People's Hospital of Lianyungang from September 2018 to February 2020 and directly transferred to the Neonatology Department for treatment were enrolled in this study. Based on their development quotient (DQ), the patients were divided into the normal (DQ ≥ 85, n = 76) group and the abnormal (DQ < 85, n = 37) group. Routine cranial MRI (cMRI) was performed at 37 weeks of PMA to measure the biparietal width (BPW) and interhemispheric distance (IHD). At the corrected age of 6 months, Development Screening Test (for children under six) was used to assess the participants' neurodevelopment.

Results

Univariate analysis showed statistically significant differences in BPW, IHD, and the incidence of bronchopulmonary dysplasia between the normal and the abnormal groups (P < 0.05), while no statistically significant differences were found in maternal complications and other clinical conditions between the two groups (P > 0.05). Binary logistic regression analysis demonstrated statistically significant differences in IHD and BPW between the normal and the abnormal groups (95% CI: 1.629-12.651 and 0.570-0.805, respectively; P = 0.004 and P < 0.001, respectively), while no significant differences were found in the incidence of bronchopulmonary dysplasia between the two groups (95% CI: 0.669-77.227, P = 0.104). Receiver operating characteristic curve revealed that the area under the curve of BPW, IHD, and the joint predictor (BPW + IHD) were 0.867, 0.805, and 0.881, respectively (95% CI: 0.800-0.933, 0.710-0.900, and 0.819-0.943, respectively; all P values < 0.001).

Conclusion

BPW and IHD, the two quantitative indicators acquired by cMRI, could predict the neurodevelopmental outcome of preterm infants at the corrected age of 6 months. The combination of the two indicators showed an even higher predictive value.

Effects of Live Music Therapy on Autonomic Stability in Preterm Infants: A Cluster-Randomized Controlled Trial

Unbuffered stress levels may negatively influence preterm-infants’ autonomic nervous system (ANS) maturation, thus affecting neurobehavior and psycho-emotional development. Music therapy (MT) is an evidence-based treatment modality in neonatal care. When coupled with skin-to-skin care (SSC), it may reduce stress responses in both preterm infants and their parents and enhance family-centered care. Accordingly, we aimed to compare the effects of combined MT and SSC and SSC alone on ANS stabilization in preterm infants. In a single-center, cluster-randomized trial design, ten two-month time-clusters were randomized to either combined MT and SSC or SSC alone. Families of preterm infants were offered two sessions of the allocated condition in the NICU, and a three-month follow up session at home. The primary outcome variable was stabilization of the ANS, defined by change in the high frequency (HF) power of heart rate variability (HRV) during the second session. Secondary outcomes included other HRV measures, parent–infant attachment, and parental anxiety at each session. Sixty-eight families were included. MT combined with SSC improved infants’ ANS stability, as indicated by a greater increase in HF power during MT compared to SSC alone (mean difference 5.19 m²/Hz, SE = 1.27, p < 0.001) (95% confidence interval 0.87 to 2.05). Most secondary outcomes were not significantly different between the study groups. MT contributes to preterm-infants’ autonomic stability, thus laying an important foundation for neuro-behavioral and psycho-emotional development. Studies evaluating longer-term effects of MT on preterm infants’ development are warranted.

Brain Volumetric Measurements in Children With Attention Deficit Hyperactivity Disorder: A Comparative Study Between Synthetic and Conventional Magnetic Resonance Imaging

Objective: To investigate the profiles of brain volumetric measurements in children with attention deficit hyperactivity disorder (ADHD), and the consistency of these brain volumetric measurements derived from the synthetic and conventional T1 weighted MRI (SyMRI and cT1w MRI).

Methods: Brain SyMRI and cT1w images were prospectively collected for 38 pediatric patients with ADHD and 38 healthy children (HC) with an age range of 6–14 years. The gray matter volume (GMV), white matter volume (WMV), cerebrospinal fluid (CSF), non-WM/GM/CSF (NoN), myelin, myelin fraction (MYF), brain parenchyma volume (BPV), and intracranial volume (ICV) were automatically estimated from SyMRI data, and the four matching measurements (GMV, WMV, BPV, ICV) were extracted from cT1w images. The group differences of brain volumetric measurements were performed, respectively, using analysis of covariance. Pearson correlation analysis and interclass correlation coefficient (ICC) were applied to evaluate the association between synthetic and cT1w MRI-derived measurements.

Results: As for the brain volumetric measurements extracted from SyMRI, significantly decreased GMV, WMV, BPV, and increased NON volume (p < 0.05) were found in the ADHD group compared with HC; No group differences were found in ICV, CSF, myelin volume and MYF (p > 0.05). With regard to GMV, WMV, BPV, and ICV estimated from cT1w images, the group differences between ADHD and HC were consistent with the results estimated from SyMRI. And these four measurements showed noticeable correlation between the two approaches (r = 0.692, 0.643, 0.898, 0.789, respectively, p < 0.001; ICC values are 0.809, 0.782, 0.946, 0.873, respectively).

Conclusion: Our study demonstrated a global brain development disability, but normal whole-brain myelination in children with ADHD. Moreover, our results demonstrated the high consistency of brain volumetric indices between synthetic and cT1w MRI in children, which indicates the high reliability of SyMRI in the child-brain volumetric analysis.

Association between brain structural network efficiency at term-equivalent age and early development of cerebral palsy in very preterm infants

Very preterm infants (born at less than 32 weeks gestational age) are at high risk for serious motor impairments, including cerebral palsy (CP). The brain network changes that antecede the early development of CP in infants are not well characterized, and a better understanding may suggest new strategies for risk-stratification at term, which could lead to earlier access to therapies. Graph theoretical methods applied to diffusion MRI-derived brain connectomes may help quantify the organization and information transfer capacity of the preterm brain with greater nuance than overt structural or regional microstructural changes. Our aim was to shed light on the pathophysiology of early CP development, before the occurrence of early intervention therapies and other environmental confounders, to help identify the best early biomarkers of CP risk in VPT infants. In a cohort of 395 very preterm infants, we extracted cortical morphometrics and brain volumes from structural MRI and also applied graph theoretical methods to diffusion MRI connectomes, both acquired at term-equivalent age. Metrics from graph network analysis, especially global efficiency, strength values of the major sensorimotor tracts, and local efficiency of the motor nodes and novel non-motor regions were strongly inversely related to early CP diagnosis. These measures remained significantly associated with CP after correction for common risk factors of motor development, suggesting that metrics of brain network efficiency at term may be sensitive biomarkers for early CP detection. We demonstrate for the first time that in VPT infants, early CP diagnosis is anteceded by decreased brain network segregation in numerous nodes, including motor regions commonly-associated with CP and also novel regions that may partially explain the high rate of cognitive impairments concomitant with CP diagnosis. These advanced MRI biomarkers may help identify the highest risk infants by term-equivalent age, facilitating earlier interventions that are informed by early pathophysiological changes.

Exploring the distribution of grey and white matter brain volumes in extremely preterm children, using magnetic resonance imaging at term age and at 10 years of age

OBJECTIVES

To investigate differences in brain volumes between children born extremely preterm and term born controls at term age and at 10 years of age.

STUDY DESIGN

Children born extremely preterm (EPT), up to 26 weeks and 6 days gestational age, in Stockholm between January 1 2004 to March 31 2007 were included in this population-based cohort study. A total of 45 EPT infants were included at term age and 51 EPT children were included at 10 years of age. There were 27 EPT children included at both time points. Two different control groups were recruited; 15 control infants were included at term age and 38 control children at 10 years of age. The primary outcomes were the grey and white matter volumes. Linear regression, adjusted for intracranial volume and sex, was used.

RESULTS

At term age, the extremely preterm infants had significantly smaller grey matter volume compared to the control infants with an adjusted mean difference of 5.0 cm3 and a 95% confidence interval of -8.4 to -1.5 (p = 0.004). At 10 years of age the extremely preterm children had significantly smaller white matter volume compared to the control children with an adjusted mean difference of 6.0 cm3 and a 95% confidence interval of -10.9 to -1.0 (p = 0.010).

CONCLUSION

Extremely preterm birth was associated with reduced grey matter volume at term age and reduced white matter volume at 10 years of age compared to term born controls.

Duration of mechanical ventilation is more critical for brain growth than postnatal hydrocortisone in extremely preterm infants

Hydrocortisone is used in preterm infants. However, early disruption of growth velocities was observed in infants exposed to hydrocortisone. This retrospective study aimed to explore the postnatal brain growth of extremely preterm infants requiring hydrocortisone treatment as well as its association with perinatal factors. Extremely preterm infants exposed to hydrocortisone from 2011 to 2016 who survived up to 12 months were included. Each of them was matched with two infants not treated with hydrocortisone exhibiting similar gestational ages and nearly similar birth head circumferences. The outcome variables were brain tissue areas on MRIs performed at term-equivalent age and postnatal head circumference growth up to a corrected age of 12 months. Univariate and multiple regression analyses were performed. Infants treated with hydrocortisone (n=20) were matched with 40 infants not exposed to hydrocortisone. The infants exposed to hydrocortisone exhibited a lower birth weight (p=0.04) and a longer duration of mechanical ventilation (p<0.0001). Infants treated with hydrocortisone exhibited a smaller basal ganglia/thalamus area (p=0.04) at term-equivalent age and a smaller head circumference at a corrected age of 12 months (p=0.003). However, the basal ganglia/thalamus area and the postnatal brain growth were independently associated with the duration of mechanical ventilation and not with hydrocortisone. Interestingly, a significant interaction between hydrocortisone and sex was observed (p=0.04).Conclusion: This study supports previous data that indicated no obvious impact of hydrocortisone on brain growth and highlights the relationship between the severity of the neonatal course and postnatal brain growth in extremely preterm infants. What is Known: • Postnatal hydrocortisone disrupts transiently growth velocities including the head circumference growth. • Postnatal hydrocortisone has less impact on neurodevelopment than dexamethasone. What is New: • Hydrocortisone prescribed for infants in the most severe conditions did not show independent effect on brain growth up to the corrected age of 12 months. However, a different effect of hydrocortisone according to sex can't be excluded and needs further explorations. • Perinatal factors as birth weight and duration of mechanical ventilation were determinant for the subsequent brain growth.

Preterm Birth Is Associated With Depression From Childhood to Early Adulthood

OBJECTIVE

There have been inconsistent findings on the associations among prematurity, poor fetal growth, and depression. We examined the associations among gestational age, poor fetal growth, and depression in individuals aged 5 to 25 years.

METHOD

We identified 37,682 case subjects based on International Classification of Diseases, Ninth Revision code 2961 and International Classification of Diseases, Tenth Revision codes F32.0-F32.9 and F33.0-F33.9 from the Care Register for Health Care, and 148,795 matched controls from the Finnish Central Population Register. Conditional logistic regression examined the associations between gestational age by each gestational week, poor fetal growth, and depression. The associations were adjusted for parental age and psychopathology, paternal immigrant status, maternal substance abuse, depression, number of previous births, marital status, socio-economic status, smoking during pregnancy, and the infant's birthplace.

RESULTS

In the adjusted models, increased risk of depression was found in children born ≤25 weeks (adjusted odds ratio [aOR] 1.89, 95% CI 1.08-3.31), at 26 weeks (aOR 2.62, 95% CI 1.49-4.61), at 27 weeks (aOR 1.93, 95% CI 1.05-3.53), and ≥42 weeks (aOR 1.11, 95% CI 1.05-1.19). In girls, extremely preterm birth was associated with depression diagnosed at 5 to 12 years (aOR 2.70, 95% CI 1.83-3.98) and 13 to 18 years (aOR 2.97, 95% CI 1.84-4.78). In boys, postterm birth (≥42 weeks) was associated with depression diagnosed at 19 to 25 years (aOR 1.28, 95% CI 1.07-1.54). Poor fetal growth was associated with an increased risk of depression in full-term infants (aOR 1.06, 95% CI 1.03-1.10) and postterm infants (aOR 1.24, 95% CI 1.08-1.43).

CONCLUSION

Preterm birth before 28 weeks of gestation appeared to play a role in the development of childhood depression. Smaller effects were also seen in postterm births, especially in boys.

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.

Precision Medicine in Neonates: A Tailored Approach to Neonatal Brain Injury

Despite advances in neonatal care to prevent neonatal brain injury and neurodevelopmental impairment, predicting long-term outcome in neonates at risk for brain injury remains difficult. Early prognosis is currently based on cranial ultrasound (CUS), MRI, EEG, NIRS, and/or general movements assessed at specific ages, and predicting outcome in an individual (precision medicine) is not yet possible. New algorithms based on large databases and machine learning applied to clinical, neuromonitoring, and neuroimaging data and genetic analysis and assays measuring multiple biomarkers (omics) can fulfill the needs of modern neonatology. A synergy of all these techniques and the use of automatic quantitative analysis might give clinicians the possibility to provide patient-targeted decision-making for individualized diagnosis, therapy, and outcome prediction. This review will first focus on common neonatal neurological diseases, associated risk factors, and most common treatments. After that, we will discuss how precision medicine and machine learning (ML) approaches could change the future of prediction and prognosis in this field.

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.

Brain volumetry in fetuses that deliver very preterm: An MRI pilot study

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Fetuses that subsequently deliver very preterm have a reduction in cortical and extra cerebrospinal fluid volumes.

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If such alterations commence antenatally this suggests a role for earlier administration of neuroprotective agents.

Background

Infants born preterm are at increased risk of neurological complications resulting in significant morbidity and mortality. The exact mechanism and the impact of antenatal factors has not been fully elucidated, although antenatal infection/inflammation has been implicated in both the aetiology of preterm birth and subsequent neurological sequelae. It is therefore hypothesized that processes driving preterm birth are affecting brain development in utero. This study aims to compare MRI derived regional brain volumes in fetuses that deliver < 32 weeks with fetuses that subsequently deliver at term.

Methods

Women at high risk of preterm birth, with gestation 19.4–32 weeks were recruited prospectively. A control group was obtained from existing study datasets. Fetal MRI was performed on a 1.5 T or 3 T MRI scanner: T2-weighted images were obtained of the fetal brain. 3D brain volumetric datsets were produced using slice to volume reconstruction and regional segmentations were produced using multi-atlas approaches for supratentorial brain tissue, lateral ventricles, cerebellum cerebral cortex and extra-cerebrospinal fluid (eCSF). Statistical comparison of control and high-risk for preterm delivery fetuses was performed by creating normal ranges for each parameter from the control datasets and then calculating gestation adjusted z scores. Groups were compared using t-tests.

Results

Fetal image datasets from 24 pregnancies with delivery < 32 weeks and 87 control pregnancies that delivered > 37 weeks were included. Median gestation at MRI of the preterm group was 26.8 weeks (range 19.4–31.4) and control group 26.2 weeks (range 21.7–31.9). No difference was found in supra-tentorial brain volume, ventricular volume or cerebellar volume but the eCSF and cerebral cortex volumes were smaller in fetuses that delivered preterm (p < 0.001 in both cases).

Conclusion

Fetuses that deliver preterm have a reduction in cortical and eCSF volumes. This is a novel finding and needs further investigation. If alterations in brain development are commencing antenatally in fetuses that subsequently deliver preterm, this may present a window for in utero therapy in the future.

Brain MRI radiomics analysis may predict poor psychomotor outcome in preterm neonates

OBJECTIVES

This study aimed to apply a radiomics approach to predict poor psychomotor development in preterm neonates using brain MRI.

METHODS

Prospectively enrolled preterm neonates underwent brain MRI near or at term-equivalent age and neurodevelopment was assessed at a corrected age of 12 months. Two radiologists visually assessed the degree of white matter injury. The radiomics analysis on white matter was performed using T1-weighted images (T1WI) and T2-weighted images (T2WI). A total of 1906 features were extracted from the images and the minimum redundancy maximum relevance algorithm was used to select features. A prediction model for the binary classification of the psychomotor developmental index was developed and eightfold cross-validation was performed. The diagnostic performance of the model was evaluated using the AUC with and without including significant clinical and DTI parameters.

RESULTS

A total of 46 preterm neonates (median gestational age, 29 weeks; 26 males) underwent brain MRI (median corrected gestational age, 37 weeks). Thirteen of 46 (28.3%) neonates showed poor psychomotor outcomes. There was one neonate among 46 with moderate to severe white matter injury on visual assessment. For the radiomics analysis, twenty features were selected for each analysis. The AUCs of prediction models based on T1WI, T2WI, and both T1WI and T2WI were 0.925, 0.834, and 0.902. Including gestational age or DTI parameters did not improve the prediction performance of T1WI.

CONCLUSIONS

A radiomics analysis of white matter using early T1WI or T2WI could predict poor psychomotor outcomes in preterm neonates.

KEY POINTS

• Radiomics analysis on T1-weighted images of preterm neonates showed the highest diagnostic performance (AUC, 0.925) for predicting poor psychomotor outcomes. • In spite of 45 of 46 neonates having no significant white matter injury on visual assessment, the radiomics analysis of early brain MRI showed good diagnostic performance (sensitivity, 84.6%; specificity, 78.8%) for predicting poor psychomotor outcomes. • Radiomics analysis on early brain MRI can help to predict poor neurodevelopmental outcomes in preterm neonates.

Uncomplicated intraventricular hemorrhage is not associated with lower estimated cerebral volume at term age

BACKGROUND AND AIMS

Cerebral lesions detected using cerebral ultrasound (cUS) in very preterm infants are associated with increased risk for neurodevelopmental problems. However, uncomplicated intraventricular hemorrhage (IVH) has no consistent association with poor outcome. In this study we evaluate the effect of uncomplicated IVH on estimated brain volume at term-equivalent age (TEA), using a model based on measurements made from cUS.

METHODS

We studied 2 groups of preterm infants (<32 weeks' gestational age (GA)) up to and at TEA: (1) infants with uncomplicated grades 2 or 3 IVH, (2) infants with consistently normal scans. Estimated cerebral volumes at TEA were calculated using a previously described model based on linear measurements and compared between the 2 groups using independent groups t-test or the Mann-Whitney test; p-value <0.05 was considered significant.

RESULTS

We assessed 95 preterm infants (18 with uncomplicated IVH and 71 with normal scans). GA and birth weight were lower in infants with uncomplicated IVH (26.8/28.7weeks, p < 0.001, 944/1082g, p < 0.05, respectively); occipital-frontal circumference at TEA was smaller in the IVH infants (34.2 vs 35.3 cm, p < 0.05). However, no significant differences at TEA were found for estimated cranial volume (383/411cc³), estimated cerebral volume (337/341cc³), Levene ventricular index (13.5/12.2 mm) or thalamo-occipital distance (21.5/20.3 mm). Statistical adjustment for the lower GA in the IVH group confirmed the absence of a significant difference in the findings.

CONCLUSIONS

In summary, we found that estimated cerebral volume at TEA, based on measurements made at the bedside using cranial US, is not different between very preterm infants with consistently normal scans and those with uncomplicated grades 2 and 3 IVH.

Ultrasonographic Estimation of Total Brain Volume: 3D Reliability and 2D Estimation. Enabling Routine Estimation During NICU Admission in the Preterm Infant

Objectives: The aim of this study is to explore if manually segmented total brain volume (TBV) from 3D ultrasonography (US) is comparable to TBV estimated by magnetic resonance imaging (MRI). We then wanted to test 2D based TBV estimation obtained through three linear axes which would enable monitoring brain growth in the preterm infant during admission. Methods: We included very low birth weight preterm infants admitted to our neonatal intensive care unit (NICU) with normal neuroimaging findings. We measured biparietal diameter, anteroposterior axis, vertical axis from US and MRI and TBV from both MRI and 3D US. We calculated intra- and interobserver agreement within and between techniques using the intraclass correlation coefficient and Bland-Altman methodology. We then developed a multilevel prediction model of TBV based on linear measurements from both US and MRI, compared them and explored how they changed with increasing age. The multilevel prediction model for TBV from linear measures was tested for internal and external validity and we developed a reference table for ease of prediction of TBV. Results: We used measurements obtained from 426 US and 93 MRI scans from 118 patients. We found good intra- and interobserver agreement for all the measurements. US measurements were reliable when compared to MRI, including TBV which achieved excellent agreement with that of MRI [ICC of 0.98 (95% CI 0.96-0.99)]. TBV estimated through 2D measurements of biparietal diameter, anteroposterior axis, and vertical axis was comparable among both techniques. We estimated the population 95% confidence interval for the mean values of biparietal diameter, anteroposterior axis, vertical axis, and total brain volume by post-menstrual age. A TBV prediction table based on the three axes is proposed to enable easy implementation of TBV estimation in routine 2D US during admission in the NICU. Conclusions: US measurements of biparietal diameter, vertical axis, and anteroposterior axis are reliable. TBV segmented through 3D US is comparable to MRI estimated TBV. 2D US accurate estimation of TBV is possible through biparietal diameter, vertical, and anteroposterior axes.

Cumulative procedural pain and brain development in very preterm infants: A systematic review of clinical and preclinical studies

Very preterm infants may manifest neurodevelopmental impairments, even in the absence of brain lesions. Pathogenesis is complex and multifactorial. Evidence suggests a role of early adversities on neurodevelopmental outcomes, via epigenetic regulation and changes in brain architecture. In this context, we focused on cumulative pain exposure which preterm neonates experience in neonatal intensive care unit (NICU). We systematically searched for: i) evidence linking pain with brain development and exploring the potential pathogenetic role of epigenetics; ii) preclinical research supporting clinical observational studies. Nine clinical neuroimaging studies, during neonatal or school age, mostly from the same research group, revealed volume reduction of white and gray matter structures in association with postnatal pain exposure. Three controlled animal studies mimicking NICU settings found increased cell death or apoptosis; nevertheless, eligible groups were limited in size. Epigenetic modulation (SLC6A4 promoter methylation) was identified in only two clinical trials. We call for additional research and, although knowledge gaps, we also point out the urgent need of minimizing painful procedures in NICUs.

Fish oil-containing multicomponent lipid emulsion vs soy-based lipid emulsion and neurodevelopmental outcomes of children born < 29 weeks' gestation

OBJECTIVE

To compare neurodevelopmental outcomes of extremely preterm children who received soy-medium chain triglycerides-olive-fish oil-containing lipid emulsion (SMOF-LE) vs soy-based LE.

STUDY DESIGN

We conducted a pre-post comparative cohort study of children born < 29 weeks' gestation who received > 7 days of LE. Outcomes were mortality/significant neurodevelopmental impairment (NDI), mortality/any NDI, significant NDI, any NDI, and individual components of NDI.

RESULTS

Among children with follow-up data (Intralipid: n = 340/442, 77%; SMOF-LE: n = 214/286, 75%), baseline characteristics were comparable except for postnatal steroids. There was no significant difference in death/significant NDI between groups. Adjusted odds of death/any NDI [0.68 (95% CI 0.48, 0.97)], any NDI [0.64 (95% CI 0.44, 0.93)] and Bayley-III language score < 85 and <70 were significantly lower in the SMOF-LE group.

CONCLUSIONS

In extremely preterm children, a change from soy-based LE to SMOF-LE was not associated with deleterious effect on neurodevelopmental outcomes and may have been associated with some improvement.

Automated brain morphometric biomarkers from MRI at term predict motor development in very preterm infants

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Nearly 1/3 of very preterm (VPT) infants develop motor impairments later in life.

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Better early biomarkers are needed for risk-stratification and early intervention.

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We used MRI morphometrics at term to predict 2-year motor ability in VPT infants.

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Inner cortical curvature at term is a novel biomarker of early motor aptitude.

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In regression models, morphometrics explained nearly 50% of motor score variance.

Very preterm infants are at high risk for motor impairments. Early interventions can improve outcomes in this cohort, but they would be most effective if clinicians could accurately identify the highest-risk infants early. A number of biomarkers for motor development exist, but currently none are sufficiently accurate for early risk-stratification. We prospectively enrolled very preterm (gestational age ≤31 weeks) infants from four level-III NICUs. Structural brain MRI was performed at term-equivalent age. We used a established pipeline to automatically derive brain volumetrics and cortical morphometrics – cortical surface area, sulcal depth, gyrification index, and inner cortical curvature – from structural MRI. We related these objective measures to Bayley-III motor scores (overall, gross, and fine) at two-years corrected age. Lasso regression identified the three best predictive biomarkers for each motor scale from our initial feature set. In multivariable regression, we assessed the independent value of these brain biomarkers, over-and-above known predictors of motor development, to predict motor scores. 75 very preterm infants had high-quality T2-weighted MRI and completed Bayley-III motor testing. All three motor scores were positively associated with regional cortical surface area and subcortical volumes and negatively associated with cortical curvature throughout the majority of brain regions. In multivariable regression modeling, thalamic volume, curvature of the temporal lobe, and curvature of the insula were significant predictors of overall motor development on the Bayley-III, independent of known predictors. Objective brain morphometric biomarkers at term show promise in predicting motor development in very preterm infants.

Mental development is associated with cortical connectivity of the ventral and nonspecific thalamus of preterm newborns

INTRODUCTION

The thalamus is a key hub for regulating cortical connectivity. Dysmaturation of thalamocortical networks that accompany white matter injury has been hypothesized as neuroanatomical correlate of late life neurocognitive impairment following preterm birth. Our objective was to find a link between thalamocortical connectivity measures at term equivalent age and two-year neurodevelopmental outcome in preterm infants.

METHODS

Diffusion tensor MRI data of 58 preterm infants (postmenstrual age at birth, mean (SD), 29.71 (1.47) weeks) were used in the study. We utilized probabilistic diffusion tractography to trace connections between the cortex and thalami. Possible associations between connectivity strength, the length of the probabilistic fiber pathways, and developmental scores (Bayley Scales of Infant Development, Second Edition) were analyzed using multivariate linear regression models.

RESULTS

We found strong correlation between mental developmental index and two complementary measures of thalamocortical networks: Connectivity strength projected to a cortical skeleton and pathway length emerging from thalamic voxels (partial correlation, R = .552 and R = .535, respectively, threshold-free cluster enhancement, corrected p-value < .05), while psychomotor development was not associated with thalamocortical connectivity. Post hoc stepwise linear regression analysis revealed that parental socioeconomic scale, postmenstrual age, and the duration of mechanical ventilation at the intensive care unit contribute to the variability of outcome.

CONCLUSIONS

Our findings independently validated previous observations in preterm infants, providing additional evidence injury or dysmaturation of tracts emerging from ventral-specific and various nonspecific thalamus projecting to late-maturing cortical regions are predictive of mental, but not psychomotor developmental outcomes.

Brain tissue volumes at term-equivalent age are associated with early motor behavior in very preterm infants

Preterm birth is associated with a wide range of adverse developmental outcomes, including sensory, motor, cognitive and language impairments, and behavioral or attention problems. Subtle motor deficits that might emerge in premature infants with no evident or with mild brain injury encompass qualitative and quantitative aspects of motor behavior. This prospective cohort study provided an evaluation of the relationship between brain tissue volumes revealed by magnetic resonance imaging (MRI) at term-equivalent age and motor behavior in infancy in very preterm infants (total number = 40; mean gestational age = 28 weeks + 4 days; mean birth weight = 1190 g) without evident or with mild brain injury. Infants were recruited at birth and assessed at 12 months corrected age using the tool for qualitative and quantitative assessment of motor behavior, infant motor profile. The brain tissue was segmented first using advanced segmentation techniques and the volumes were measured by summing the volumes of all voxels belonging to a particular tissue class. The associations between volumetric brain MRI measures with motor behavior were explored using linear regression analyses. Results showed that larger total brain volumes were associated with higher motor score. Similar relationships were documented for parietal lobe, deep gray matter, and cerebellum volumes. Volumetric quantitative data of brain structures may serve as biomarkers for subtle motor deficits described in very preterm born infants without or with mild brain lesions apparent on MRI.

Synthetic MRI of Preterm Infants at Term-Equivalent Age: Evaluation of Diagnostic Image Quality and Automated Brain Volume Segmentation

BACKGROUND AND PURPOSE

Neonatal MR imaging brain volume measurements can be used as biomarkers for long-term neurodevelopmental outcome, but quantitative volumetric MR imaging data are not usually available during routine radiologic evaluation. In the current study, the feasibility of automated quantitative brain volumetry and image reconstruction via synthetic MR imaging in very preterm infants was investigated.

MATERIALS AND METHODS

Conventional and synthetic T1WIs and T2WIs from 111 very preterm infants were acquired at term-equivalent age. Overall image quality and artifacts of the conventional and synthetic images were rated on a 4-point scale. Legibility of anatomic structures and lesion conspicuity were assessed on a binary scale. Synthetic MR volumetry was compared with that generated via MANTiS, which is a neonatal tissue segmentation toolbox based on T2WI.

RESULTS

Image quality was good or excellent for most conventional and synthetic images. The 2 methods did not differ significantly regarding image quality or diagnostic performance for focal and cystic WM lesions. Dice similarity coefficients had excellent overlap for intracranial volume (97.3%) and brain parenchymal volume (94.3%), and moderate overlap for CSF (75.6%). Bland-Altman plots demonstrated a small systematic bias in all cases (1.7%-5.9%) CONCLUSIONS: Synthetic T1WI and T2WI sequences may complement or replace conventional images in neonatal imaging, and robust synthetic volumetric results are accessible from a clinical workstation in less than 1 minute. Via the above-described methods, volume assessments could be routinely used in daily clinical practice.

Neonatal morphometric similarity mapping for predicting brain age and characterizing neuroanatomic variation associated with preterm birth

Multi-contrast MRI captures information about brain macro- and micro-structure which can be combined in an integrated model to obtain a detailed "fingerprint" of the anatomical properties of an individual's brain. Inter-regional similarities between features derived from structural and diffusion MRI, including regional volumes, diffusion tensor metrics, neurite orientation dispersion and density imaging measures, can be modelled as morphometric similarity networks (MSNs). Here, individual MSNs were derived from 105 neonates (59 preterm and 46 term) who were scanned between 38 and 45 weeks postmenstrual age (PMA). Inter-regional similarities were used as predictors in a regression model of age at the time of scanning and in a classification model to discriminate between preterm and term infant brains. When tested on unseen data, the regression model predicted PMA at scan with a mean absolute error of 0.70  ±  0.56 weeks, and the classification model achieved 92% accuracy. We conclude that MSNs predict chronological brain age accurately; and they provide a data-driven approach to identify networks that characterise typical maturation and those that contribute most to neuroanatomic variation associated with preterm birth.

Socioeconomic status and brain injury in children born preterm: modifying neurodevelopmental outcome

Improved intensive care therapies have increased the survival of children born preterm. Yet, many preterm children experience long-term neurodevelopmental sequelae. Indeed, preterm birth remains a leading cause of lifelong neurodevelopmental disability globally, posing significant challenges to the child, family, and society. Neurodevelopmental disability in children born preterm is traditionally linked to acquired brain injuries such as white matter injury and to impaired brain maturation resulting from neonatal illness such as chronic lung disease. Socioeconomic status (SES) has long been recognized to contribute to variation in outcome in children born preterm. Recent brain imaging data in normative term-born cohorts suggest that lower SES itself predicts alterations in brain development, including the growth of the cerebral cortex and subcortical structures. Recent evidence in children born preterm suggests that the response to early-life brain injuries is modified by the socioeconomic circumstances of children and families. Exciting new data points to the potential of more favorable SES circumstances to mitigate the impact of neonatal brain injury. This review addresses emerging evidence suggesting that SES modifies the relationship between early-life exposures, brain injury, and neurodevelopmental outcomes in children born preterm. Better understanding these relationships opens new avenues for research with the ultimate goal of promoting optimal outcomes for those children born preterm at highest risk of neurodevelopmental consequence.

A novel hybrid atlas-free hierarchical graph-based segmentation of newborn brain MRI using wavelet filter banks

Objective: The newborn brain MRI (magnetic resonance imaging) tissue segmentation plays a vital part in assessment of primary brain growth. In the newborn stage (nearly less than 28 days old), in T1- as well as T2-weighted MR images similar levels of intensity are exhibited by WM and GM, makes segmentation of the tissue extremely challenging. In this newborn stage for tissue segmentation, very few methods are developed. Hence the development of accurate brain tissue segmentation of neonate is prime objective of this paper.Methods: In this research work, we propose a novel hybrid atlas-free hierarchical graph-based tissue segmentation method for newborn infants. Wavelet filter banks are a class of deep models wherein filters and local neighborhood processes are used alternately for efficient segmentation on the raw input images, and fuzzy-based SVM (support vector machine) is used for precise tissue classification.Results: Specifically, from T1, T2 images multimodality information are used as inputs and then as outputs the segmentation maps are generated. The proposed approach considerably outperforms preceding methods of tissue segmentation as reflected in results. With this approach, the newborn MRI images that are even suffered from noise, poor resolution or the low contrasted images are also segmented more effectively with precision of 90% and sensitivity 98%.Conclusion: In addition, our findings indicate that the incorporation of multi-modality image led to significant improvements in performance. Thus, the proposed work effectively tackles the unreliability as well as the other issues faced with the prior methodologies with an interactive accurate segmentation outline.

Quantitative MRI study of infant regional brain size following surgery for long-gap esophageal atresia requiring prolonged critical care

INTRODUCTION

Little is known regarding the impact of concurrent critical illness and thoracic noncardiac perioperative critical care on postnatal brain development. Previously, we reported smaller total brain volumes in both critically ill full-term and premature patients following complex perioperative critical care for long-gap esophageal atresia (LGEA). Our current report assessed trends in regional brain sizes during infancy, and probed for any group differences.

METHODS

Full-term (n = 13) and preterm (n = 13) patients without any previously known neurological concerns, and control infants (n = 16), underwent non-sedated 3 T MRI in infancy (<1 year old). T2-weighted images underwent semi-automated brain segmentation using Morphologically Adaptive Neonatal Tissue Segmentation (MANTiS). Regional tissue volumes of the forebrain, deep gray matter (DGM), cerebellum, and brainstem are presented as absolute (cm3) and normalized (% total brain volume (%TBV)) values. Group differences were assessed using a general linear model univariate analysis with corrected age at scan as a covariate.

RESULTS

Absolute volumes of regions analyzed increased with advancing age, paralleling total brain size, but were significantly smaller in both full-term and premature patients compared to controls. Normalized volumes (%TBV) of forebrain, DGM, and cerebellum were not different between subject groups analyzed. Normalized brainstem volumes showed group differences that warrant future studies to confirm the same finding.

DISCUSSION

Both full-term and premature critically ill infants undergoing life-saving surgery for LGEA are at risk of smaller total and regional brain sizes. Normalized volumes support globally delayed or diminished brain growth in patients. Future research should look into neurodevelopmental outcomes of infants born with LGEA.

New insights into the development of the human cerebral cortex

The cerebral cortex constitutes more than half the volume of the human brain and is presumed to be responsible for the neuronal computations underlying complex phenomena, such as perception, thought, language, attention, episodic memory and voluntary movement. Rodent models are extremely valuable for the investigation of brain development, but cannot provide insight into aspects that are unique or highly derived in humans. Many human psychiatric and neurological conditions have developmental origins but cannot be studied adequately in animal models. The human cerebral cortex has some unique genetic, molecular, cellular and anatomical features, which need to be further explored. The Anatomical Society devoted its summer meeting to the topic of Human Brain Development in June 2018 to tackle these important issues. The meeting was organized by Gavin Clowry (Newcastle University) and Zoltán Molnár (University of Oxford), and held at St John's College, Oxford. The participants provided a broad overview of the structure of the human brain in the context of scaling relationships across the brains of mammals, conserved principles and recent changes in the human lineage. Speakers considered how neuronal progenitors diversified in human to generate an increasing variety of cortical neurons. The formation of the earliest cortical circuits of the earliest generated neurons in the subplate was discussed together with their involvement in neurodevelopmental pathologies. Gene expression networks and susceptibility genes associated to neurodevelopmental diseases were discussed and compared with the networks that can be identified in organoids developed from induced pluripotent stem cells that recapitulate some aspects of in vivo development. New views were discussed on the specification of glutamatergic pyramidal and γ-aminobutyric acid (GABA)ergic interneurons. With the advancement of various in vivo imaging methods, the histopathological observations can be now linked to in vivo normal conditions and to various diseases. Our review gives a general evaluation of the exciting new developments in these areas. The human cortex has a much enlarged association cortex with greater interconnectivity of cortical areas with each other and with an expanded thalamus. The human cortex has relative enlargement of the upper layers, enhanced diversity and function of inhibitory interneurons and a highly expanded transient subplate layer during development. Here we highlight recent studies that address how these differences emerge during development focusing on diverse facets of our evolution.