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

Motion Robust MR Fingerprinting Scan to Image Neonates With Prenatal Opioid Exposure

PURPOSE

To explore whether MR fingerprinting (MRF) scans provide motion-robust and quantitative brain tissue measurements for non-sedated infants with prenatal opioid exposure (POE).

STUDY TYPE

Prospective.

POPULATION

13 infants with POE (3 male; 12 newborns (age 7-65 days) and 1 infant aged 9-months).

FIELD STRENGTH/SEQUENCE

3T, 3D T1-weighted MPRAGE, 3D T2-weighted TSE and MRF sequences.

ASSESSMENT

The image quality of MRF and MRI was assessed in a fully crossed, multiple-reader, multiple-case study. Sixteen image quality features in three types-image artifacts, structure and myelination visualization-were ranked by four neuroradiologists (8, 7, 5, and 8 years of experience respectively), using a 3-point scale. MRF T1 and T2 values in 8 white matter brain regions were compared between babies younger than 1 month and babies between 1 and 2 months.

STATISTICAL TESTS

Generalized estimating equations model to test the significance of differences of regional T1 and T2 values of babies under 1 month and those older. MRI and MRF image quality was assessed using Gwet's second order auto-correlation coefficient (AC2) with confidence levels. The Cochran-Mantel-Haenszel test was used to assess the difference in proportions between MRF and MRI for all features and stratified by the type of features. A P value <0.05 was considered statistically significant.

RESULTS

The MRF of two infants were excluded in T1 and T2 value analysis due to severe motion artifact but were included in the image quality assessment. In infants under 1 month of age (N = 6), the T1 and T2 values were significantly higher compared to those between 1 and 2 months of age (N = 4). MRF images showed significantly higher image quality ratings in all three feature types compared to MRI images.

CONCLUSIONS

MR Fingerprinting scans have potential to be a motion-robust and efficient method for nonsedated infants.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 1.

Intrauterine exposure to chorioamnionitis and neuroanatomical alterations at term-equivalent age in preterm infants

PURPOSE

Infants born to mothers with chorioamnionitis (CAM) are at increased risk of developing adverse neurodevelopmental disorders in later life. However, clinical magnetic resonance imaging (MRI) studies examining brain injuries and neuroanatomical alterations attributed to CAM have yielded inconsistent results. We aimed to determine whether exposure to histological CAM in utero leads to brain injuries and alterations in the neuroanatomy of preterm infants using 3.0- Tesla MRI at term-equivalent age.

METHODS

A total of 58 preterm infants born before 34 weeks of gestation at Nagoya University Hospital between 2010 and 2018 were eligible for this study (CAM group, n = 21; non-CAM group, n = 37). Brain injuries and abnormalities were assessed using the Kidokoro Global Brain Abnormality Scoring system. Gray matter, white matter, and subcortical gray matter (thalamus, caudate nucleus, putamen, pallidum, hippocampus, amygdala, and nucleus accumbens) volumes were evaluated using segmentation tools (SPM12 and Infant FreeSurfer).

RESULTS

The Kidokoro scores for each category and severity in the CAM group were comparable to those observed in the non-CAM group. White matter volume was significantly smaller in the CAM group after adjusting for covariates (postmenstrual age at MRI, infant sex, and gestational age) (p = 0.007), whereas gray matter volume was not significantly different. Multiple linear regression analyses revealed significantly smaller volumes in the bilateral pallidums (right, p = 0.045; left, p = 0.038) and nucleus accumbens (right, p = 0.030; left, p = 0.004) after adjusting for covariates.

CONCLUSIONS

Preterm infants born to mothers with histological CAM showed smaller volumes in white matter, pallidum, and nucleus accumbens at term-equivalent age.

Multi-level fMRI analysis applied to hemispheric specialization in the language network, functional areas, and their behavioral correlations in the ABCD sample

Prior research suggests that the organization of the language network in the brain is left-dominant and becomes more lateralized with age and increasing language skill. The age at which specific components of the language network become adult-like varies depending on the abilities they subserve. So far, a large, developmental study has not included a language task paradigm, so we introduce a method to study resting-state laterality in the Adolescent Brain Cognitive Development (ABCD) study. Our approach mixes source timeseries between left and right homotopes of the (1) inferior frontal and (2) middle temporal gyri and (3) a region we term "Wernicke's area" near the supramarginal gyrus. Our large subset sample size of ABCD (n = 6153) allows improved reliability and validity compared to previous, smaller studies of brain-behavior associations. We show that behavioral metrics from the NIH Youth Toolbox and other resources are differentially related to tasks with a larger linguistic component over ones with less (e.g., executive function-dominant tasks). These baseline characteristics of hemispheric specialization in youth are critical for future work determining the correspondence of lateralization with language onset in earlier stages of development.

Associations between maternal pre-pregnancy BMI and infant striatal mean diffusivity

BACKGROUND

It is well-established that parental obesity is a strong risk factor for offspring obesity. Further, a converging body of evidence now suggests that maternal weight profiles may affect the developing offspring's brain in a manner that confers future obesity risk. Here, we investigated how pre-pregnancy maternal weight status influences the reward-related striatal areas of the offspring's brain during in utero development.

METHODS

We used diffusion tensor imaging to quantify the microstructure of the striatal brain regions of interest in neonates (N = 116 [66 males, 50 females], mean gestational weeks at birth [39.88], SD = 1.14; at scan [43.56], SD = 1.05). Linear regression was used to test the associations between maternal pre-pregnancy body mass index (BMI) and infant striatal mean diffusivity.

RESULTS

High maternal pre-pregnancy BMI was associated with higher mean MD values in the infant's left caudate nucleus. Results remained unchanged after the adjustment for covariates.

CONCLUSIONS

In utero exposure to maternal adiposity might have a growth-impairing impact on the mean diffusivity of the infant's left caudate nucleus. Considering the involvement of the caudate nucleus in regulating eating behavior and food-related reward processing later in life, this finding calls for further investigations to define the prognostic relevance of early-life caudate nucleus development and weight trajectories of the offspring.

Global trends in neonatal MRI brain neuroimaging research over the last decade: a bibliometric analysis

Background

Neuroimaging plays a central role in the evaluation, treatment, and prognosis of neonates. In recent years, the exploration of the developing brain has been a major focus of research for researchers and clinicians. In this study, we conducted bibliometric and visualization analyses of the related studies in the field of neonatal magnetic resonance imaging (MRI) brain neuroimaging from the past 10 years, and summarized its research status, hotspots, and frontier development trends.

Methods

The Web of Science core collection database was used as the literature source from which to retrieve the relevant papers and reviews in the field of neonatal MRI brain neuroimaging published in the Science Citation Index-Expanded from 2013 to 2022. VOSviewer and CiteSpace were used to conduct bibliometric and visualization analyses of the annual publication volume, countries, institutions, journals, authors, co-cited literature, and the overall distribution of keywords.

Results

We retrieved 3,568 papers and reviews published from 2013 to 2022. The number of publications increased during this period. The United States (US) and the United Kingdom were the largest contributors, with the US receiving the highest H-index and number of citations. The institutions that published the most were the University of London and Harvard University. The research mainly focused on cerebral cortex, brain tissue, brain structure network, artificial intelligence algorithm, automatic image segmentation, and premature infants.

Conclusions

This study reveals the research status and hotspots of magnetic resonance imaging in the field of neonatal brain neuroimaging in the past decade, which helps researchers to better understand the research status, hotspots, and frontier development trends.

Scaling patterns of cortical folding and thickness in early human brain development in comparison with primates

Across mammalia, brain morphology follows specific scaling patterns. Bigger bodies have bigger brains, with surface area outpacing volume growth, resulting in increased foldedness. We have recently studied scaling rules of cortical thickness, both local and global, finding that the cortical thickness difference between thick gyri and thin sulci also increases with brain size and foldedness. Here, we investigate early brain development in humans, using subjects from the Developing Human Connectome Project, scanned shortly after pre-term or full-term birth, yielding magnetic resonance images of the brain from 29 to 43 postmenstrual weeks. While the global cortical thickness does not change significantly during this development period, its distribution does, with sulci thinning, while gyri thickening. By comparing our results with our recent work on humans and 11 non-human primate species, we also compare the trajectories of primate evolution with human development, noticing that the 2 trends are distinct for volume, surface area, cortical thickness, and gyrification index. Finally, we introduce the global shape index as a proxy for gyrification index; while correlating very strongly with gyrification index, it offers the advantage of being calculated only from local quantities without generating a convex hull or alpha surface.

Development of neonatal-specific sequences for portable ultralow field magnetic resonance brain imaging: a prospective, single-centre, cohort study

Background

Magnetic Resonance (MR) imaging is key for investigation of suspected newborn brain abnormalities. Access is limited in low-resource settings and challenging in infants needing intensive care. Portable ultralow field (ULF) MRI is showing promise in bedside adult brain imaging. Use in infants and children has been limited as brain-tissue composition differences necessitate sequence modification. The aim of this study was to develop neonatal-specific ULF structural sequences and test these across a range of gestational maturities and pathologies to inform future validation studies.

Methods

Prospective cohort study within a UK neonatal specialist referral centre. Infants undergoing 3T MRI were recruited for paired ULF (64mT) portable MRI by convenience sampling from the neonatal unit and post-natal ward. Key inclusion criteria: 1) Infants with risk or suspicion of brain abnormality, or 2) preterm and term infants without suspicion of major genetic, chromosomal or neurological abnormality. Exclusions: presence of contra-indication for MR scanning. ULF sequence parameters were optimised for neonatal brain-tissues by iterative and explorative design. Neuroanatomic and pathologic features were compared by unblinded review, informing optimisation of subsequent sequence generations in a step-wise manner. Main outcome: visual identification of healthy and abnormal brain tissues/structures. ULF MR spectroscopy, diffusion, susceptibility weighted imaging, arteriography, and venography require pre-clinical technical development and have not been tested.

Findings

Between September 23, 2021 and October 25, 2022, 102 paired scans were acquired in 87 infants; 1.17 paired scans per infant. Median age 9 days, median postmenstrual age 40+2 weeks (range: 31+3-53+4). Infants had a range of intensive care requirements. No adverse events observed. Optimised ULF sequences can visualise key neuroanatomy and brain abnormalities. In finalised neonatal sequences: T2w imaging distinguished grey and white matter (7/7 infants), ventricles (7/7), pituitary tissue (5/7), corpus callosum (7/7) and optic nerves (7/7). Signal congruence was seen within the posterior limb of the internal capsule in 10/11 infants on finalised T1w scans. In addition, brain abnormalities visualised on ULF optimised sequences have similar MR signal patterns to 3T imaging, including injury secondary to infarction (6/6 infants on T2w scans), hypoxia-ischaemia (abnormal signal in basal ganglia, thalami and white matter 2/2 infants on T2w scans, cortical highlighting 1/1 infant on T1w scan), and congenital malformations: polymicrogyria 3/3, absent corpus callosum 2/2, and vermian hypoplasia 3/3 infants on T2w scans. Sequences are susceptible to motion corruption, noise, and ULF artefact. Non-identified pathologies were small or subtle.

Interpretation

On unblinded review, optimised portable MR can provide sufficient contrast, signal, and resolution for neuroanatomical identification and detection of a range of clinically important abnormalities. Blinded validation studies are now warranted.

Funding

The Bill and Melinda Gates Foundation, the MRC, the Wellcome/EPSRC Centre for Medical Engineering, the MRC Centre for Neurodevelopmental Disorders, and the National Institute for Health Research (NIHR) Biomedical Research Centres based at Guy's and St Thomas' and South London & Maudsley NHS Foundation Trusts and King's College London.

Multi-echo Acquisition and Thermal Denoising Advances Infant Precision Functional Imaging

The characterization of individual functional brain organization with Precision Functional Mapping has provided important insights in recent years in adults. However, little is known about the ontogeny of inter-individual differences in brain functional organization during human development, but precise characterization of systems organization during periods of high plasticity might be most influential towards discoveries promoting lifelong health. Collecting and analyzing precision fMRI data during early development has unique challenges and emphasizes the importance of novel methods to improve data acquisition, processing, and analysis strategies in infant samples. Here, we investigate the applicability of two such methods from adult MRI research, multi-echo (ME) data acquisition and thermal noise removal with Noise reduction with distribution corrected principal component analysis (NORDIC), in precision fMRI data from three newborn infants. Compared to an adult example subject, T2* relaxation times calculated from ME data in infants were longer and more variable across the brain, pointing towards ME acquisition being a promising tool for optimizing developmental fMRI. The application of thermal denoising via NORDIC increased tSNR and the overall strength of functional connections as well as the split-half reliability of functional connectivity matrices in infant ME data. While our findings related to NORDIC denoising are coherent with the adult literature and ME data acquisition showed high promise, its application in developmental samples needs further investigation. The present work reveals gaps in our understanding of the best techniques for developmental brain imaging and highlights the need for further developmentally-specific methodological advances and optimizations, towards precision functional imaging in infants.

Practical Stepwise Approach to Performing Neonatal Brain MR Imaging in the Research Setting

Magnetic resonance imaging (MRI) is a non-invasive imaging technique that is commonly used for the visualization of newborn infant brains, both for clinical and research purposes. One of the main challenges with scanning newborn infants, particularly when scanning without sedation in a research setting, is movement. Infant movement can affect MR image quality and therewith reliable image assessment and advanced image analysis. Applying a systematic, stepwise approach to MR scanning during the neonatal period, including the use of the feed-and-bundle technique, is effective in reducing infant motion and ensuring high-quality images. We provide recommendations for one such systematic approach, including the step-by-step preparation and infant immobilization, and highlight safety precautions to minimize any potential risks. The recommendations are primarily focused on scanning newborn infants for research purposes but may be used successfully for clinical purposes as well, granted the infant is medically stable. Using the stepwise approach in our local research setting, our success rate of acquiring high-quality, analyzable infant brain MR images during the neonatal period is as high as 91%.

Human white matter myelinates faster in utero than ex utero

The formation of myelin, the fatty sheath that insulates nerve fibers, is critical for healthy brain function. A fundamental open question is what impact being born has on myelin growth. To address this, we evaluated a large (n = 300) cross-sectional sample of newborns from the Developing Human Connectome Project (dHCP). First, we developed software for the automated identification of 20 white matter bundles in individual newborns that is well suited for large samples. Next, we fit linear models that quantify how T1w/T2w (a myelin-sensitive imaging contrast) changes over time at each point along the bundles. We found faster growth of T1w/T2w along the lengths of all bundles before birth than right after birth. Further, in a separate longitudinal sample of preterm infants (N = 34), we found lower T1w/T2w than in full-term peers measured at the same age. By applying the linear models fit on the cross-section sample to the longitudinal sample of preterm infants, we find that their delay in T1w/T2w growth is well explained by the amount of time they spent developing in utero and ex utero. These results suggest that white matter myelinates faster in utero than ex utero. The reduced rate of myelin growth after birth, in turn, explains lower myelin content in individuals born preterm and could account for long-term cognitive, neurological, and developmental consequences of preterm birth. We hypothesize that closely matching the environment of infants born preterm to what they would have experienced in the womb may reduce delays in myelin growth and hence improve developmental outcomes.

Implications of Pediatric Artificial Intelligence Challenges for Artificial Intelligence Education and Curriculum Development

Several radiology artificial intelligence (AI) courses are offered by a variety of institutions and educators. The major radiology societies have developed AI curricula focused on basic AI principles and practices. However, a specific AI curriculum focused on pediatric radiology is needed to offer targeted education material on AI model development and performance evaluation. There are inherent differences between pediatric and adult practice patterns, which may hinder the application of adult AI models in pediatric cohorts. Such differences include the different imaging modality utilization, imaging acquisition parameters, lower radiation doses, the rapid growth of children and changes in their body composition, and the presence of unique pathologies and diseases, which differ in prevalence from adults. Thus, to enhance radiologists' knowledge of the applications of AI models in pediatric patients, curricula should be structured keeping in mind the unique pediatric setting and its challenges, along with methods to overcome these challenges, and pediatric-specific data governance and ethical considerations. In this report, the authors highlight the salient aspects of pediatric radiology that are necessary for AI education in the pediatric setting, including the challenges for research investigation and clinical implementation.

Temporal Evolution of Signal Alterations in the Deep Gray Nuclei in term Neonates With Hypoxic-Ischemic Brain Injury: A Comprehensive Review

The deep gray nuclei are paired interconnected gray nuclei comprising the basal ganglia and thalami. Injury to the deep gray nuclei secondary to hypoxic-ischemic injury is associated with poor short- and long-term clinical outcomes. The signal changes following hypoxic-ischemic injury are dynamic and evolve over a period of time from injury to resolution. Radiologically relevant events following hypoxic-ischemic injury include the onset of anaerobic metabolism immediately following hypoxic-ischemic injury, increase in cytotoxic edema followed by its resolution, and the onset and progression of neuronal necrosis and gliosis. Appearance of lactate peak on proton spectroscopy is the initial radiologic evidence of hypoxic-ischemic injury. Diffusion-weighted imaging has the highest prognostic value and pseudo-normalizes following 1 week of hypoxic-ischemic injury. Recommended timing for magnetic resonance imaging (MRI) is between 4 and 7 days. MR imaging performed between 1 and 6 months underestimates the extent of injury because radiologic changes are subtle. This review provides a detailed timeline of radiologic abnormalities in the deep gray nuclei following hypoxic-ischemic injury.

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.

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

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

Development of cortical folds in the human brain: An attempt to review biological hypotheses, early neuroimaging investigations and functional correlates

The folding of the human brain mostly takes place in utero, making it challenging to study. After a few pioneer studies looking into it in post-mortem foetal specimen, modern approaches based on neuroimaging have allowed the community to investigate the folding process in vivo, its normal progression, its early disturbances, and its relationship to later functional outcomes. In this review article, we aimed to first give an overview of the current hypotheses on the mechanisms governing cortical folding. After describing the methodological difficulties raised by its study in fetuses, neonates and infants with magnetic resonance imaging (MRI), we reported our current understanding of sulcal pattern emergence in the developing brain. We then highlighted the functional relevance of early sulcal development, through recent insights about hemispheric asymmetries and early factors influencing this dynamic such as prematurity. Finally, we outlined how longitudinal studies have started to relate early folding markers and the child's sensorimotor and cognitive outcome. Through this review, we hope to raise awareness on the potential of studying early sulcal patterns both from a fundamental and clinical perspective, as a window into early neurodevelopment and plasticity in relation to growth in utero and postnatal environment of the child.

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

PURPOSE

To develop a new approach to 3D gradient echo-based anatomical imaging of the neonatal brain with a substantially shorter scan time than standard 3D fast spin echo (FSE) methods, while maintaining a high SNR.

METHODS

T2 -prepration was employed immediately prior to image acquisition of 3D balanced steady-state free precession (bSSFP) with a single trajectory of center-out k-space view ordering, which requires no magnetization recovery time between imaging segments during the scan. This approach was compared with 3D FSE, 2D single-shot FSE, and product 3D bSSFP imaging in numerical simulations, plus phantom and in vivo experiments.

RESULTS

T2 -prepared 3D bSSFP generated image contrast of gray matter, white matter, and CSF very similar to that of reference T2 -weighted imaging methods, without major image artifacts. Scan time of T2 -prepared 3D bSSFP was remarkably shorter compared to 3D FSE, whereas SNR was comparable to that of 3D FSE and higher than that of 2D single-shot FSE. Specific absorption rate of T2 -prepared 3D bSSFP remained within the safety limit. Determining an optimal imaging flip angle of T2 -prepared 3D bSSFP was critical to minimizing blurring of images.

CONCLUSION

T2 -prepared 3D bSSFP offers an alternative method for anatomical imaging of the neonatal brain with dramatically reduced scan time compared to standard 3D FSE and higher SNR than 2D single-shot FSE.

Applications of advanced diffusion MRI in early brain development: a comprehensive review

Brain development follows a protracted developmental timeline with foundational processes of neurodevelopment occurring from the third trimester of gestation into the first decade of life. Defining structural maturational patterns of early brain development is a critical step in detecting divergent developmental trajectories associated with neurodevelopmental and psychiatric disorders that arise later in life. While considerable advancements have already been made in diffusion magnetic resonance imaging (dMRI) for pediatric research over the past three decades, the field of neurodevelopment is still in its infancy with remarkable scientific and clinical potential. This comprehensive review evaluates the application, findings, and limitations of advanced dMRI methods beyond diffusion tensor imaging, including diffusion kurtosis imaging (DKI), constrained spherical deconvolution (CSD), neurite orientation dispersion and density imaging (NODDI) and composite hindered and restricted model of diffusion (CHARMED) to quantify the rapid and dynamic changes supporting the underlying microstructural architectural foundations of the brain in early life.

Early brain morphometrics from neonatal MRI predict motor and cognitive outcomes at 2-years corrected age in very preterm infants

Infants born very preterm face a range of neurodevelopmental challenges in cognitive, language, behavioural and/or motor domains. Early accurate identification of those at risk of adverse neurodevelopmental outcomes, through clinical assessment and Magnetic Resonance Imaging (MRI), enables prognostication of outcomes and the initiation of targeted early interventions. This study utilises a prospective cohort of 181 infants born <31 weeks gestation, who had 3T MRIs acquired at 29-35 weeks postmenstrual age and a comprehensive neurodevelopmental evaluation at 2 years corrected age (CA). Cognitive, language and motor outcomes were assessed using the Bayley Scales of Infant and Toddler Development - Third Edition and functional motor outcomes using the Neuro-sensory Motor Developmental Assessment. By leveraging advanced structural MRI pre-processing steps to standardise the data, and the state-of-the-art developing Human Connectome Pipeline, early MRI biomarkers of neurodevelopmental outcomes were identified. Using Least Absolute Shrinkage and Selection Operator (LASSO) regression, significant associations between brain structure on early MRIs with 2-year outcomes were obtained (r = 0.51 and 0.48 for motor and cognitive outcomes respectively) on an independent 25% of the data. Additionally, important brain biomarkers from early MRIs were identified, including cortical grey matter volumes, as well as cortical thickness and sulcal depth across the entire cortex. Adverse outcome on the Bayley-III motor and cognitive composite scores were accurately predicted, with an Area Under the Curve of 0.86 for both scores. These associations between 2-year outcomes and patient prognosis and early neonatal MRI measures demonstrate the utility of imaging prior to term equivalent age for providing earlier commencement of targeted interventions for infants born preterm.

Application of diffusion kurtosis imaging in neonatal brain development

Background

Deviations from the regular pattern of growth and development could lead to early childhood diseases, suggesting the importance of evaluating early brain development. Through this study, we aimed to explore the changing patterns of white matter and gray matter during neonatal brain development using diffusion kurtosis imaging (DKI).

Materials and methods

In total, 42 full-term neonates (within 28 days of birth) underwent conventional brain magnetic resonance imaging (MRI) and DKI. The DKI metrics (including kurtosis parameters and diffusion parameters) of white matter and deep gray matter were measured. DKI metrics from the different regions of interest (ROIs) were evaluated using the Kruskal-Wallis test and Bonferroni method. Spearman rank correlation analysis of the DKI metrics was conducted, and the age at the time of brain MRI acquisition was calculated. The subjects were divided into three groups according to their age at the time of brain MRI acquisition: the first group, neonates aged ≤7 days; the second group, neonates aged 8-14 days; and the third group, neonates aged 15-28 days. The rate of change in DKI metrics relative to the first group was computed.

Results

The mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), and fractional anisotropy (FA) values showed positive correlations, whereas mean diffusion (MD), axial diffusion (Da), and radial diffusion (Dr) values showed negative correlations with the age at the time of brain MRI acquisition. The absolute correlation coefficients between MK values of almost all ROIs (except genu of the corpus callosum and frontal white matter) and the age at the time of brain MRI acquisition were greater than other metrics. The kurtosis parameters and FA values of central white matter were significantly higher than that of peripheral white matter, whereas the MD and Dr values were significantly lower than that of peripheral white matter. The MK value of the posterior limb of the internal capsule was the highest among the white matter areas. The FA value of the splenium of the corpus callosum was significantly higher than that of the other white matter areas. The kurtosis parameters and FA values of globus pallidus and thalamus were significantly higher than those of the caudate nucleus and putamen, whereas the Da and Dr values of globus pallidus and thalamus were significantly lower than those of the caudate nucleus and putamen. The relative change rates of kurtosis parameters and FA values of all ROIs were greater than those of MD, Da, and Dr values. The amplitude of MK values of almost all ROIs (except for the genu of the corpus callosum and central white matter of the centrum semiovale level) was greater than that of other metrics. The relative change rates of the Kr values of most ROIs were greater than those of the Ka value, and the relative change rates of the Dr values of most ROIs were greater than those of the Da value.

Conclusion

DKI parameters showed potential advantages in detecting the changes in brain microstructure during neonatal brain development.

Aberrant claustrum structure in preterm-born neonates: an MRI study

The human claustrum is a gray matter structure in the white matter between insula and striatum. Previous analysis found altered claustrum microstructure in very preterm-born adults associated with lower cognitive performance. As the claustrum development is related to hypoxia-ischemia sensitive transient cell populations being at-risk in premature birth, we hypothesized that claustrum structure is already altered in preterm-born neonates. We studied anatomical and diffusion-weighted MRIs of 83 preterm- and 83 term-born neonates at term-equivalent age. Additionally, claustrum development was analyzed both in a spectrum of 377 term-born neonates and longitudinally in 53 preterm-born subjects. Data was provided by the developing Human Connectome Project. Claustrum development showed increasing volume, increasing fractional anisotropy (FA), and decreasing mean diffusivity (MD) around term both across term- and preterm-born neonates. Relative to term-born ones, preterm-born neonates had (i) increased absolute and relative claustrum volumes, both indicating increased cellular and/or extracellular matter and being in contrast to other subcortical gray matter regions of decreased volumes such as thalamus; (ii) lower claustrum FA and higher claustrum MD, pointing at increased extracellular matrix and impaired axonal integrity; and (iii) aberrant covariance between claustrum FA and MD, respectively, and that of distributed gray matter regions, hinting at relatively altered claustrum microstructure. Results together demonstrate specifically aberrant claustrum structure in preterm-born neonates, suggesting altered claustrum development in prematurity, potentially relevant for later cognitive performance.

Continuous monitoring of neonatal cortical activity: A major step forward

Montazeri Moghadam et al.¹ report an automated algorithm to visually convert EEG recordings to real-time quantified interpretations of EEG in neonates. The resulting measure of the brain state of the newborn (BSN) bridges several gaps in neurocritical care monitoring.

Synthetic MR Imaging-Based WM Signal Suppression Identifies Neonatal Brainstem Pathways in Vivo

BACKGROUND AND PURPOSE

Multidynamic multiecho sequence-based imaging enables investigators to reconstruct multiple MR imaging contrasts on the basis of a single scan. This study investigated the feasibility of synthetic MRI-based WM signal suppression (syWMSS), a synthetic inversion recovery approach in which a short TI suppresses myelin-related signals, for the identification of early myelinating brainstem pathways.

MATERIALS AND METHODS

Thirty-one cases of neonatal MR imaging, which included multidynamic multiecho data and conventionally acquired T1- and T2-weighted sequences, were analyzed. The multidynamic multiecho postprocessing software SyMRI was used to generate syWMSS data (TR/TE/TI = 3000/5/410 ms). Two raters discriminated early myelinating brainstem pathways (decussation of the superior cerebellar peduncle, medial lemniscus, central tegmental tract, and medial longitudinal fascicle [the latter 3 assessed at the level of the pons]) on syWMSS data and reference standard contrasts.

RESULTS

On the basis of syWMSS data, the decussation of the superior cerebellar peduncle (31/31); left/right medial lemniscus (31/31; 30/31); left/right central tegmental tract (19/31; 20/31); and left/right medial longitudinal fascicle (30/31) were reliably identified by both raters. On the basis of T1-weighted contrasts, the decussation of the superior cerebellar peduncle (14/31); left/right medial lemniscus (22/31; 16/31); left/right central tegmental tract (1/31); and left/right medial longitudinal fascicle (9/31; 8/31) were reliably identified by both raters. On the basis of T2-weighted contrasts, the decussation of the superior cerebellar peduncle (28/31); left/right medial lemniscus (16/31; 12/31); left/right central tegmental tract (23/31; 18/31); and left/right medial longitudinal fascicle (15/31; 14/31) were reliably identified by both raters.

CONCLUSIONS

syWMSS data provide a feasible imaging technique with which to study early myelinating brainstem pathways. MR imaging approaches that use myelin signal suppression contribute to a more sensitive assessment of myelination patterns at early stages of cerebral development.

Evaluation of deep gray matter for early brain development using quantitative susceptibility mapping

OBJECTIVES

To evaluate susceptibility values associated with iron accumulation in the deep gray matter during postnatal development and to compare magnetic susceptibility between patients with normal and delayed development.

METHODS

Patients with postmenstrual age (PMA) ≤ 1000 days underwent MR scans between August 2015 and April 2020 at our hospital. Quantitative susceptibility mapping (QSM) was performed, and magnetic susceptibility was measured using three-dimensional volumes of interest (VOIs) for the caudate nucleus (CN), globus pallidus (GP), putamen (PT), and ventrolateral thalamic nucleus (VL). Cross-sectional analysis was performed for 99 patients with normal development and 39 patients with delayed development. Longitudinal analysis was also performed to interpret changes over time in 13 patients with normal development. Correlations between magnetic susceptibility in VOIs and PMA or chronological age (CA) were assessed.

RESULTS

Susceptibility values for CN, GP, PT, and VL showed positive moderate correlations with both PMA (ρ = 0.45, 0.69, 0.62, and 0.33, respectively) and CA (ρ = 0.53, 0.69, 0.66, and 0.39, respectively). The slope of the correlation between susceptibility values and age was highest in the GP among the four gray matter areas. Susceptibility values for the CN, GP, PT, and VL were higher with normal development than with delayed development at early postnatal age, although a significant difference was only observed for the CN. Susceptibility values also increased with age in the longitudinal analysis.

CONCLUSIONS

Magnetic susceptibility values in deep gray matter increased with age ≤ 1000 days. The normal development group showed higher susceptibility values than the delayed development group at early postnatal age (PMA ≤ 285 days).

KEY POINTS

• Magnetic susceptibilities in deep gray matter nuclei increased with age (postmenstrual age ≤ 1000 days) in a large number of pediatric patients. • The normal development group showed higher susceptibility values than the delayed development group in the basal ganglia and ventrolateral thalamic nucleus at early postnatal age (PMA ≤ 285 days).

A comparative study of the superior longitudinal fasciculus subdivisions between neonates and young adults

The superior longitudinal fasciculus (SLF) is a complex associative tract comprising three distinct subdivisions in the frontoparietal cortex, each of which has its own anatomical connectivity and functional roles. However, many studies on white matter development, hampered by limitations of data quality and tractography methods, treated the SLF as a single entity. The exact anatomical trajectory and developmental status of each sub-bundle of the human SLF in neonates remain poorly understood. Here, we compared the morphological and microstructural characteristics of each branch of the SLF at two ages using diffusion MRI data from 40 healthy neonates and 40 adults. A multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) algorithm was used to ensure the successful separation of the three SLF branches (SLF I, SLF II and SLF III). Then, between-group differences in the diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics were investigated in all the SLF branches. Meanwhile, Mahalanobis distances based on all the diffusion metrics were computed to quantify the maturation of neonatal SLF branches, considering the adult brain as the reference. The SLF branches, excluding SLF II, had similar fibre morphology and connectivity between the neonatal and adult groups. The Mahalanobis distance values further supported the notion of heterogeneous maturation among SLF branches. The greatest Mahalanobis distance was observed in SLF II, possibly indicating that it was the least mature. Our findings provide a new anatomical basis for the early diagnosis and treatment of diseases caused by abnormal neonatal SLF development.

Concurrent mapping of brain ontogeny and phylogeny within a common space: Standardized tractography and applications

Developmental and evolutionary effects on brain organization are complex, yet linked, as evidenced by the correspondence in cortical area expansion across these vastly different time scales. However, it is still not possible to study concurrently the ontogeny and phylogeny of cortical areal connections, which is arguably more relevant to brain function than allometric measurements. Here, we propose a novel framework that allows the integration of structural connectivity maps from humans (adults and neonates) and nonhuman primates (macaques) onto a common space. We use white matter bundles to anchor the common space and use the uniqueness of cortical connection patterns to these bundles to probe area specialization. This enabled us to quantitatively study divergences and similarities in connectivity over evolutionary and developmental scales, to reveal brain maturation trajectories, including the effect of premature birth, and to translate cortical atlases between diverse brains. Our findings open new avenues for an integrative approach to imaging neuroanatomy.

MRI Findings of Pituitary Gland in Growth Hormone-Deficient Children and Their Correlation with Growth Hormone Peak during Growth Hormone Stimulation Tests

This study aims to explore the magnetic resonance imaging (MRI) findings of the pituitary gland (PG) in children with growth hormone deficiency (GHD) and their correlation with the growth hormone (GH) peak during clinical GH stimulation tests. Sixty-one children with GHD diagnosed and treated between December 2018 and December 2021 were retrospectively analyzed in terms of clinical and pituitary morphological MRI data. MRI measurements of various diameters of the adenohypophysis (AH) were obtained to analyze the differences of the measured values in different genders and age groups, as well as their relationship with the GH peak in GH stimulation tests. Among the 61 children with GHD, the superior PG margin was protuberant in 2 cases, flat in 13 cases, and concave in 46 cases. The three age groups showed similar pituitary morphology and stalk (P > 0.05). On T1-weighted images, the proportion of isointensity was lower while the proportion of slightly-low signal intensity was higher in the anterior pituitary gland (APG) of children aged >10 compared with those aged 7–10. The comparison of AH linear parameters and GH peak values of male patients among different age groups showed that the anteroposterior (sagittal) diameter of AH and GH peak were the highest in the >10-year-old group and the lowest in the ≤6-year-old group, with those of the 7–10-year-old group in between (P < 0.05). In females, the anteroposterior (sagittal) diameter and GH peak were higher in the 7–10-year-old group and >10-year-old group compared with the ≤6-year-old group (P < 0.05). The MRI coronal and sagittal heights of PG in children with GHD were positively correlated with the GH peak value. In conclusion, in GHD patients, the coronal and sagittal heights as well as the coronal width of AH do not change with sex or age, but the coronal and sagittal heights of PG are positively correlated with the GH peak of GH stimulation tests, which has high application value in the diagnosis of children with GHD.

Biomarker und Neuromonitoring zur Entwicklungsprognose nach perinataler Hirnschädigung

Das sich entwickelnde Gehirn ist in der Perinatalperiode besonders empfindlich für eine Vielzahl von Insulten, wie z. B. Extremfrühgeburtlichkeit und perinatale Asphyxie. Ihre Komplikationen können zu lebenslangen neurokognitiven, sensorischen und psychosozialen Einschränkungen führen; deren Vorhersage bleibt eine Herausforderung. Eine Schlüsselfunktion kommt der möglichst exakten Identifikation von Hirnläsionen und funktionellen Störungen zu. Die Prädiktion stützt sich auf frühe diagnostische Verfahren und die klinische Erfassung der Meilensteine der Entwicklung. Zur klinischen Diagnostik und zum Neuromonitoring in der Neonatal- und frühen Säuglingsperiode stehen bildgebende Verfahren zur Verfügung. Hierzu zählen zerebrale Sonographie, MRT am errechneten Termin, amplitudenintegriertes (a)EEG und/oder klassisches EEG, Nah-Infrarot-Spektroskopie, General Movements Assessment und die frühe klinische Nachuntersuchung z. B. mithilfe der Hammersmith Neonatal/Infant Neurological Examination. Innovative Biomarker und -muster (Omics) sowie (epi)genetische Prädispositionen sind Gegenstand wissenschaftlicher Untersuchungen. Neben der Erfassung klinischer Risiken kommt psychosozialen Faktoren im Umfeld des Kindes eine entscheidende Rolle zu. Eine möglichst akkurate Prognose ist mit hohem Aufwand verbunden, jedoch zur gezielten Beratung der Familien und der Einleitung von frühen Interventionen, insbesondere vor dem Hintergrund der hohen Plastizität des sich entwickelnden Gehirns, von großer Bedeutung. Diese Übersichtsarbeit fokussiert die Charakterisierung der oben genannten Verfahren und ihrer Kombinationsmöglichkeiten. Zudem wird ein Ausblick gegeben, wie innovative Techniken in Zukunft die Prädiktion der Entwicklung und Nachsorge dieser Kinder vereinfachen können.

Neuroprotective Role of Lactoferrin during Early Brain Development and Injury through Lifespan

Early adverse fetal environments can significantly disturb central nervous system (CNS) development and subsequently alter brain maturation. Nutritional status is a major variable to be considered during development and increasing evidence links neonate and preterm infant impaired brain growth with neurological and psychiatric diseases in adulthood. Breastfeeding is one of the main components required for healthy newborn development due to the many "constitutive" elements breastmilk contains. Maternal intake of specific nutrients during lactation may alter milk composition, thus affecting newborn nutrition and, potentially, brain development. Lactoferrin (Lf) is a major protein present in colostrum and the main protein in human milk, which plays an important role in the benefits of breastfeeding during postnatal development. It has been demonstrated that Lf has antimicrobial, as well as anti-inflammatory properties, and is potentially able to reduce the incidence of sepsis and necrotizing enterocolitis (NEC), which are particularly frequent in premature births. The anti-inflammatory effects of Lf can reduce birth-related pathologies by decreasing the release of pro-inflammatory factors and inhibiting premature cervix maturation (also related to commensal microbiome abnormalities) that could contribute to disrupting brain development. Pre-clinical evidence shows that Lf protects the developing brain from neuronal injury, enhances brain connectivity and neurotrophin production, and decreases inflammation in models of perinatal inflammatory challenge, intrauterine growth restriction (IUGR) and neonatal hypoxia-ischemia (HI). In this context, Lf can provide nutritional support for brain development and cognition and prevent the origin of neuropsychiatric diseases later in life. In this narrative review, we consider the role of certain nutrients during neurodevelopment linking to the latest research on lactoferrin with respect to neonatology. We also discuss new evidence indicating that early neuroprotective pathways modulated by Lf could prevent neurodegeneration through anti-inflammatory and immunomodulatory processes.

Altered Cerebral Curvature in Preterm Infants Is Associated with the Common Genetic Variation Related to Autism Spectrum Disorder and Lipid Metabolism

Preterm births are often associated with neurodevelopmental impairment. In the critical developmental period of the fetal brain, preterm birth disrupts cortical maturation. Notably, preterm birth leads to alterations in the fronto-striatal and temporal lobes and the limbic region. Recent advances in MRI acquisition and analysis methods have revealed an integrated approach to the genetic influence on brain structure. Based on imaging studies, we hypothesized that the altered cortical structure observed after preterm birth is associated with common genetic variations. We found that the presence of the minor allele at rs1042778 in OXTR was associated with reduced curvature in the right medial orbitofrontal gyrus (p < 0.001). The presence of the minor allele at rs174576 in FADS2 (p < 0.001) or rs740603 in COMT (p < 0.001) was related to reduced curvature in the left posterior cingulate gyrus. This study provides biological insight into altered cortical curvature at term-equivalent age, suggesting that the common genetic variations related to autism spectrum disorder (ASD) and lipid metabolism may mediate vulnerability to early cortical dysmaturation in preterm infants.

Attention-modulated multi-branch convolutional neural networks for neonatal brain tissue segmentation

Accurate measurement of brain structures is essential for the evaluation of neonatal brain growth and development. The conventional methods use manual segmentation to measure brain tissues, which is very time-consuming and inefficient. Recent deep learning achieves excellent performance in computer vision, but it is still unsatisfactory for segmenting magnetic resonance images of neonatal brains because they are immature with unique attributes. In this paper, we propose a novel attention-modulated multi-branch convolutional neural network for neonatal brain tissue segmentation. The proposed network is built on the encoder-decoder framework by introducing both multi-scale convolutions in the encoding path and multi-branch attention modules in the decoding path. Multi-scale convolutions with different kernels are used to extract rich semantic features across large receptive fields in the encoding path. Multi-branch attention modules are used to capture abundant contextual information in the decoding path for segmenting brain tissues by fusing both local features and their corresponding global dependencies. Spatial attention connections between the encoding and decoding paths are designed to increase feature propagation for both avoiding information loss during downsampling and accelerating model training convergence. The proposed network was implemented in comparison with baseline methods on three neonatal brain datasets. Our network achieves the average Dice similarity coefficients/the average Hausdorff distances of 0.9116/8.1289, 0.9367/9.8212 and 0.8931/8.1612 on the customized dCBP2021 dataset, 0.8786/11.7863, 0.8965/13.4296 and 0.8539/10.462 on the public NBAtlas dataset, as well as 0.9253/7.7968, 0.9448/9.5472 and 0.9132/7.5877 on the public dHCP2017 dataset in partitioning the brain into gray matter, white matter and cerebrospinal fluid, respectively. The experimental results show that the proposed method achieves competitive state-of-the-art performance in neonatal brain tissue segmentation. The code and pre-trained models are available at https://github.com/zhangyongqin/AMCNN.

Growth charts of brain morphometry for preschool children

Brain development from 1 to 6 years of age anchors a wide range of functional capabilities and carries early signs of neurodevelopmental disorders. However, quantitative models for depicting brain morphology changes and making individualized inferences are lacking, preventing the identification of early brain atypicality during this period. With a total sample size of 285, we characterized the age-dependence of the cortical thickness and subcortical volume in neurologically normal children and constructed quantitative growth charts of all brain regions for preschool children. While the cortical thickness of most brain regions decreased with age, the entorhinal and parahippocampal regions displayed an inverted-U shape of age-dependence. Compared to the cortical thickness, the normalized volume of subcortical regions exhibited more divergent trends, with some regions increasing, some decreasing, and some displaying inverted-U-shaped trends. The growth curve models for all brain regions demonstrated utilities in identifying brain atypicality. The percentile measures derived from the growth curves facilitate the identification of children with developmental speech and language disorders with an accuracy of 0.875 (area under the receiver operating characteristic curve: 0.943). Our results fill the knowledge gap in brain morphometrics in a critical development period and provide an avenue for individualized brain developmental status evaluation with demonstrated sensitivity.

An ode to fetal, infant, and toddler neuroimaging: Chronicling early clinical to research applications with MRI, and an introduction to an academic society connecting the field

Fetal, infant, and toddler neuroimaging is commonly thought of as a development of modern times (last two decades). Yet, this field mobilized shortly after the discovery and implementation of MRI technology. Here, we provide a review of the parallel advancements in the fields of fetal, infant, and toddler neuroimaging, noting the shifts from clinical to research use, and the ongoing challenges in this fast-growing field. We chronicle the pioneering science of fetal, infant, and toddler neuroimaging, highlighting the early studies that set the stage for modern advances in imaging during this developmental period, and the large-scale multi-site efforts which ultimately led to the explosion of interest in the field today. Lastly, we consider the growing pains of the community and the need for an academic society that bridges expertise in developmental neuroscience, clinical science, as well as computational and biomedical engineering, to ensure special consideration of the vulnerable mother-offspring dyad (especially during pregnancy), data quality, and image processing tools that are created, rather than adapted, for the young brain.

Advanced Brain Imaging in Preterm Infants: A Narrative Review of Microstructural and Connectomic Disruption

Preterm birth disrupts the in utero environment, preventing the brain from fully developing, thereby causing later cognitive and behavioral disorders. Such cerebral alteration occurs beneath an anatomical scale, and is therefore undetectable by conventional imagery. Prematurity impairs the microstructure and thus the histological process responsible for the maturation, including the myelination. Cerebral MRI diffusion tensor imaging sequences, based on water’s motion into the brain, allows a representation of this maturation process. Similarly, the brain’s connections become disorganized. The connectome gathers structural and anatomical white matter fibers, as well as functional networks referring to remote brain regions connected one over another. Structural and functional connectivity is illustrated by tractography and functional MRI, respectively. Their organizations consist of core nodes connected by edges. This basic distribution is already established in the fetal brain. It evolves greatly over time but is compromised by prematurity. Finally, cerebral plasticity is nurtured by a lifetime experience at microstructural and macrostructural scales. A preterm birth causes a negative and early disruption, though it can be partly mitigated by positive stimuli based on developmental neonatal care.

White matter myelination during early infancy is linked to spatial gradients and myelin content at birth

Development of myelin, a fatty sheath that insulates nerve fibers, is critical for brain function. Myelination during infancy has been studied with histology, but postmortem data cannot evaluate the longitudinal trajectory of white matter development. Here, we obtained longitudinal diffusion MRI and quantitative MRI measures of longitudinal relaxation rate (R1) of white matter in 0, 3 and 6 months-old human infants, and developed an automated method to identify white matter bundles and quantify their properties in each infant's brain. We find that R1 increases from newborns to 6-months-olds in all bundles. R1 development is nonuniform: there is faster development in white matter that is less mature in newborns, and development rate increases along inferior-to-superior as well as anterior-to-posterior spatial gradients. As R1 is linearly related to myelin fraction in white matter bundles, these findings open new avenues to elucidate typical and atypical white matter myelination in early infancy.

Neurobehavioral Phenotype and Dysexecutive Syndrome of Preterm Children: Comorbidity or Trigger? An Update

Premature birth is a worldwide public health priority. One in ten children is born before 37 weeks of gestational age and, in developed countries, survival rates without major neonatal morbidity are increasing. Although severe sequelae associated with these births have decreased, their neurobehavioral difficulties, often associated in multiple fields, remain stable but still widespread. These neurobehavioral difficulties hamper the normal development of academic achievements and societal integration and intensify the children's needs for rehabilitation during their preschool and academic years. Severe sequelae increase when gestational age decreases. This is even truer if the socio-cultural background is impeded by low income, education and language skills as compared with defined averages. However, moderate and/or minor neurocognitive and/or behavioral difficulties are almost identical for a moderate or a late preterm birth. Obtaining a better clinical description of neurobehavioral characteristics of those pretermly born, once they reach preschool age, is essential to detect behavioral issues as well as early specific cognitive difficulties (working memory, planning, inhibition, language expression and reception, attention and fine motor skills, etc.). Such information would provide a better understanding of the executive functions' role in brain connectivity, neurodevelopment and neuroanatomical correlation with premature encephalopathy.

Early structural brain development in infants exposed to HIV and antiretroviral therapy in utero in a South African birth cohort

Introduction

There is a growing population of children who are HIV‐exposed and uninfected (HEU) with the successful expansion of antiretroviral therapy (ART) use in pregnancy. Children who are HEU are at risk of delayed neurodevelopment; however, there is limited research on early brain growth and maturation. We aimed to investigate the effects of in utero exposure to HIV/ART on brain structure of infants who are HEU compared to HIV‐unexposed (HU).

Methods

Magnetic resonance imaging using a T2‐weighted sequence was undertaken in a subgroup of infants aged 2–6 weeks enrolled in the Drakenstein Child Health Study birth cohort, South Africa, between 2012 and 2015. Mother–child pairs received antenatal and postnatal HIV testing and ART per local guidelines. We compared subcortical and total grey matter volumes between HEU and HU groups using multivariable linear regression adjusting for infant age, sex, intracranial volume and socio‐economic variables. We further assessed associations between brain volumes with maternal CD4 cell count and ART exposure.

Results

One hundred forty‐six infants (40 HEU; 106 HU) with high‐resolution images were included in this analysis (mean age 3 weeks; 50.7% male). All infants who were HEU were exposed to ART (88% maternal triple ART). Infants who were HEU had smaller caudate volumes bilaterally (5.4% reduction, p < 0.05) compared to HU infants. There were no group differences in other subcortical volumes (all p > 0.2). Total grey matter volume was also reduced in infants who were HEU (2.1% reduction, p < 0.05). Exploratory analyses showed that low maternal CD4 cell count (<350 cells/mm³) was associated with decreased infant grey matter volumes. There was no relationship between timing of ART exposure and grey matter volumes.

Conclusions

Lower caudate and total grey matter volumes were found in infants who were HEU compared to HU in the first weeks of life, and maternal immunosuppression was associated with reduced volumes. These findings suggest that antenatal HIV exposure may impact early structural brain development and improved antenatal HIV management may have the potential to optimize neurodevelopmental outcomes of children who are HEU.

Expert consensus on the clinical practice of neonatal brain magnetic resonance imaging

In recent years, magnetic resonance imaging (MRI) has been widely used in evaluating neonatal brain development, diagnosing neonatal brain injury, and predicting neurodevelopmental prognosis. Based on current research evidence and clinical experience in China and overseas, the Neonatologist Society of Chinese Medical Doctor Association has developed a consensus on the indications and standardized clinical process of neonatal brain MRI. The consensus has the following main points. (1) Brain MRI should be performed for neonates suspected of hypoxic-ischemic encephalopathy, intracranial infection, stroke and unexplained convulsions; brain MRI is not considered a routine in the management of preterm infants, but it should be performed for further evaluation when cranial ultrasound finds evidence of brain injury; as for extremely preterm or extremely low birth weight infants without abnormal ultrasound findings, it is recommended that they should undergo MRI examination at term equivalent age once. (2) Neonates should undergo MRI examination in a non-sedated state if possible. (3) During MRI examination, vital signs should be closely monitored to ensure safety; the necessity of MRI examination should be strictly evaluated for critically ill neonates, and magnetic resonance compatible incubator and ventilator can be used. (4) At present, 1.5 T or 3.0 T equipment can be used for neonatal brain MRI examination, and the special coil for the neonatal head should be used to improve signal-to-noise ratio; routine neonatal brain MRI sequences should at least include axial T1 weighted image (T1WI), axial T2 weighted imaging (T2WI), diffusion-weighted imaging, and sagittal T1WI or T2WI. (5) It is recommended to use a structured and graded reporting system, and reports by at least two reviewers and multi-center collaboration are recommended to increase the reliability of the report.

Towards a model of language neurobiology in early development

Understanding language neurobiology in early childhood is essential for characterizing the developmental structural and functional changes that lead to the mature adult language network. In the last two decades, the field of language neurodevelopment has received increasing attention, particularly given the rapid advances in the implementation of neuroimaging techniques and analytic approaches that allow detailed investigations into the developing brain across a variety of cognitive domains. These methodological and analytical advances hold the promise of developing early markers of language outcomes that allow diagnosis and clinical interventions at the earliest stages of development. Here, we argue that findings in language neurobiology need to be integrated within an approach that captures the dynamic nature and inherent variability that characterizes the developing brain and the interplay between behavior and (structural and functional) neural patterns. Accordingly, we describe a framework for understanding language neurobiology in early development, which minimally requires an explicit characterization of the following core domains: i) computations underlying language learning mechanisms, ii) developmental patterns of change across neural and behavioral measures, iii) environmental variables that reinforce language learning (e.g., the social context), and iv) brain maturational constraints for optimal neural plasticity, which determine the infant's sensitivity to learning from the environment. We discuss each of these domains in the context of recent behavioral and neuroimaging findings and consider the need for quantitatively modeling two main sources of variation: individual differences or trait-like patterns of variation and within-subject differences or state-like patterns of variation. The goal is to enable models that allow prediction of language outcomes from neural measures that take into account these two types of variation. Finally, we examine how future methodological approaches would benefit from the inclusion of more ecologically valid paradigms that complement and allow generalization of traditional controlled laboratory methods.

Dear reviewers: Responses to common reviewer critiques about infant neuroimaging studies

The field of adult neuroimaging relies on well-established principles in research design, imaging sequences, processing pipelines, as well as safety and data collection protocols. The field of infant magnetic resonance imaging, by comparison, is a young field with tremendous scientific potential but continuously evolving standards. The present article aims to initiate a constructive dialog between researchers who grapple with the challenges and inherent limitations of a nascent field and reviewers who evaluate their work. We address 20 questions that researchers commonly receive from research ethics boards, grant, and manuscript reviewers related to infant neuroimaging data collection, safety protocols, study planning, imaging sequences, decisions related to software and hardware, and data processing and sharing, while acknowledging both the accomplishments of the field and areas of much needed future advancements. This article reflects the cumulative knowledge of experts in the FIT’NG community and can act as a resource for both researchers and reviewers alike seeking a deeper understanding of the standards and tradeoffs involved in infant neuroimaging.

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The field of infant MRI is young with evolving standards.

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We address 20 questions that researchers commonly receive reviewers.

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These come from research ethics boards, grant, and manuscript reviewers.

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This article reflects the cumulative knowledge of experts in the FIT’NG community.

A brain extraction algorithm for infant T2 weighted magnetic resonance images based on fuzzy c-means thresholding

It is challenging to extract the brain region from T2-weighted magnetic resonance infant brain images because conventional brain segmentation algorithms are generally optimized for adult brain images, which have different spatial resolution, dynamic changes of imaging intensity, brain size and shape from infant brain images. In this study, we propose a brain extraction algorithm for infant T2-weighted images. The proposed method utilizes histogram partitioning to separate brain regions from the background image. Then, fuzzy c-means thresholding is performed to obtain a rough brain mask for each image slice, followed by refinement steps. For slices that contain eye regions, an additional eye removal algorithm is proposed to eliminate eyes from the brain mask. By using the proposed method, accurate masks for infant T2-weighted brain images can be generated. For validation, we applied the proposed algorithm and conventional methods to T2 infant images (0–24 months of age) acquired with 2D and 3D sequences at 3T MRI. The Dice coefficients and Precision scores, which were calculated as quantitative measures, showed the highest values for the proposed method as follows: For images acquired with a 2D imaging sequence, the average Dice coefficients were 0.9650 ± 0.006 for the proposed method, 0.9262 ± 0.006 for iBEAT, and 0.9490 ± 0.006 for BET. For the data acquired with a 3D imaging sequence, the average Dice coefficient was 0.9746 ± 0.008 for the proposed method, 0.9448 ± 0.004 for iBEAT, and 0.9622 ± 0.01 for BET. The average Precision was 0.9638 ± 0.009 and 0.9565 ± 0.016 for the proposed method, 0.8981 ± 0.01 and 0.8968 ± 0.008 for iBEAT, and 0.9346 ± 0.014 and 0.9282 ± 0.019 for BET for images acquired with 2D and 3D imaging sequences, respectively, demonstrating that the proposed method could be efficiently used for brain extraction in T2-weighted infant images.

Gradient-Guided Isotropic MRI Reconstruction from Anisotropic Acquisitions

The trade-off between image resolution, signal-to-noise ratio (SNR), and scan time in any magnetic resonance imaging (MRI) protocol is inevitable and unavoidable. Super-resolution reconstruction (SRR) has been shown effective in mitigating these factors, and thus, has become an important approach in addressing the current limitations of MRI. In this work, we developed a novel, image-based MRI SRR approach based on anisotropic acquisition schemes, which utilizes a new gradient guidance regularization method that guides the high-resolution (HR) reconstruction via a spatial gradient estimate. Further, we designed an analytical solution to propagate the spatial gradient fields from the low-resolution (LR) images to the HR image space and exploited these gradient fields over multiple scales with a dynamic update scheme for more accurate edge localization in the reconstruction. We also established a forward model of image formation and inverted it along with the proposed gradient guidance. The proposed SRR method allows subject motion between volumes and is able to incorporate various acquisition schemes where the LR images are acquired with arbitrary orientations and displacements, such as orthogonal and through-plane origin-shifted scans. We assessed our proposed approach on simulated data as well as on the data acquired on a Siemens 3T MRI scanner containing 45 MRI scans from 14 subjects. Our experimental results demonstrate that our approach achieved superior reconstructions compared to state-of-the-art methods, both in terms of local spatial smoothness and edge preservation, while, in parallel, at reduced, or at the same cost as scans delivered with direct HR acquisition.

Early and late development of hub connectivity in the human brain

Human brain networks undergo pronounced changes during development. The emergence of highly connected hub regions that can support integrated brain function is central to this maturational process, with these areas undergoing a particularly protracted period of development that extends into adulthood. The location of cortical network hubs emerges early but connections to and from hubs continue to strengthen throughout childhood and adolescence. Patterns of functional coupling in cortical association hubs are immature and incomplete at birth, but gradually strengthen during development. Early establishment of hub connectivity may provide a stable substrate that is refined by changes in tissue organization and microstructure, resulting in the emergence of complex functional dynamics by adulthood.

Arterial spin labeling in neonatal magnetic resonance imaging - first experience and new observations

Purpose

Arterial spin labeling (ASL) is a noninvasive non-contrast technique of perfusion imaging that uses endogenous water from the blood as the perfusion tracer, with very scant data on its use in neonates. The authors present the added value of ASL in the examined babies in their own material and discuss it in the light of the existing literature.

Material and methods

During the first 10 months after the purchase of a new magnetic resonance imaging (MRI) scanner, 123 neonates were examined using it in an MR-compatible incubator, 117 of them had brain MRI, and in 104 ASL was incorporated in the routine protocol, which resulted in prolongation of the study time by approximately 4 minutes. 3D ASL sequence uses Pulsed Continuous Arterial Spin Labeling (PCASL; aka pseudo continuous) technique.

Results

The quality of the cerebral blood flow (CBF) maps was good in all cases but 2 because all the babies were sedated. Apart from the knowledge about normal perfusion patterns in the preterm and term neonatal brains, the use of ASL sequence provided important additional information in 11 cases (10.8%): increased CBF correlating with electroencephalographic seizure localization in otherwise normal MRI (n = 1), increased CBF in the cortex without clinical information about seizures and with posthaemorrhagic changes (n = 1), increased CBF in the brain stem and decreased in the upper parts of the brain (n = 2), probably reflecting the homeostatic mechanism which allows preferential perfusion of the vital structures of the brain stem, hypoperfusion (n = 1) or hypoperfusion with peripheral hyperperfusion (n = 1) in the area of stroke, hypoperfusion of the posterior areas of the brain in the presence of subarachnoid or epidural haemorrhage (n = 3), significantly increased CBF in the presumed nidus of arteriovenous malformation causing haemorrhage (n = 1), and lack of perfusion in the supratentorial compartment in a case of suspected brain death (n = 1).

Conclusions

Our short experience but relatively large volume of material encourages the use of ASL in routine neonatal MRI as a useful and non-time-consuming tool providing additional important clinical information in a significant percentage of cases.

Fast and High-Resolution Neonatal Brain MRI Through Super-Resolution Reconstruction From Acquisitions With Variable Slice Selection Direction

The brain of neonates is small in comparison to adults. Imaging at typical resolutions such as one cubic mm incurs more partial voluming artifacts in a neonate than in an adult. The interpretation and analysis of MRI of the neonatal brain benefit from a reduction in partial volume averaging that can be achieved with high spatial resolution. Unfortunately, direct acquisition of high spatial resolution MRI is slow, which increases the potential for motion artifact, and suffers from reduced signal-to-noise ratio. The purpose of this study is thus that using super-resolution reconstruction in conjunction with fast imaging protocols to construct neonatal brain MRI images at a suitable signal-to-noise ratio and with higher spatial resolution than can be practically obtained by direct Fourier encoding. We achieved high quality brain MRI at a spatial resolution of isotropic 0.4 mm with 6 min of imaging time, using super-resolution reconstruction from three short duration scans with variable directions of slice selection. Motion compensation was achieved by aligning the three short duration scans together. We applied this technique to 20 newborns and assessed the quality of the images we reconstructed. Experiments show that our approach to super-resolution reconstruction achieved considerable improvement in spatial resolution and signal-to-noise ratio, while, in parallel, substantially reduced scan times, as compared to direct high-resolution acquisitions. The experimental results demonstrate that our approach allowed for fast and high-quality neonatal brain MRI for both scientific research and clinical studies.

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.

Multi-Parametric Evaluation of Cerebral Hemodynamics in Neonatal Piglets Using Non-Contrast-Enhanced Magnetic Resonance Imaging Methods

BACKGROUND

Disruption of brain oxygen delivery and consumption after hypoxic-ischemic injury contributes to neonatal mortality and neurological impairment. Measuring cerebral hemodynamic parameters, including cerebral blood flow (CBF), oxygen extraction fraction (OEF), and cerebral metabolic rate of oxygen (CMRO₂ ), is clinically important.

PURPOSE

Phase-contrast (PC), velocity-selective arterial spin labeling (VSASL), and T₂ -relaxation-under-phase-contrast (TRUPC) are magnetic resonance imaging (MRI) techniques that have shown promising results in assessing cerebral hemodynamics in humans. We aimed to test their feasibility in quantifying CBF, OEF, and CMRO₂ in piglets.

STUDY TYPE

Prospective.

ANIMAL MODEL

Ten neonatal piglets subacutely recovered from global hypoxia-ischemia (N = 2), excitotoxic brain injury (N = 6), or sham procedure (N = 2).

FIELD STRENGTH/SEQUENCE

VSASL, TRUPC, and PC MRI acquired at 3.0 T.

ASSESSMENT

Regional CBF was measured by VSASL. Global CBF was quantified by both PC and VSASL. TRUPC assessed OEF at the superior sagittal sinus (SSS) and internal cerebral veins (ICVs). CMRO₂ was calculated from global CBF and SSS-derived OEF. End-tidal carbon dioxide (EtCO₂ ) levels of the piglets were also measured. Brain damage was assessed in tissue sections postmortem by counting damaged neurons.

STATISTICAL TESTS

Spearman correlations were performed to evaluate associations among CBF (by PC or VSASL), OEF, CMRO₂ , EtCO₂ , and the pathological neuron counts. Paired t-test was used to compare OEF at SSS with OEF at ICV.

RESULTS

Global CBF was 32.1 ± 14.9 mL/100 g/minute and 30.9 ± 8.3 mL/100 g/minute for PC and VSASL, respectively, showing a significant correlation (r = 0.82, P < 0.05). OEF was 54.9 ± 8.8% at SSS and 46.1 ± 5.6% at ICV, showing a significant difference (P < 0.05). Global CMRO₂ was 79.1 ± 26.2 μmol/100 g/minute and 77.2 ± 12.2 μmol/100 g/minute using PC and VSASL-derived CBF, respectively. EtCO₂ correlated positively with PC-based CBF (r = 0.81, P < 0.05) but negatively with OEF at SSS (r = -0.84, P < 0.05). Relative CBF of subcortical brain regions and OEF at ICV did not significantly correlate, respectively, with the ratios of degenerating-to-total neurons (P = 0.30, P = 0.10).

DATA CONCLUSION

Non-contrast MRI can quantify cerebral hemodynamic parameters in normal and brain-injured neonatal piglets.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 2.

Early Diagnostics and Early Intervention in Neurodevelopmental Disorders-Age-Dependent Challenges and Opportunities

This review discusses early diagnostics and early intervention in developmental disorders in the light of brain development. The best instruments for early detection of cerebral palsy (CP) with or without intellectual disability are neonatal magnetic resonance imaging, general movements assessment at 2-4 months and from 2-4 months onwards, the Hammersmith Infant Neurological Examination and Standardized Infant NeuroDevelopmental Assessment. Early detection of autism spectrum disorders (ASD) is difficult; its first signs emerge at the end of the first year. Prediction with the Modified Checklist for Autism in Toddlers and Infant Toddler Checklist is possible to some extent and improves during the second year, especially in children at familial risk of ASD. Thus, prediction improves substantially when transient brain structures have been replaced by permanent circuitries. At around 3 months the cortical subplate has dissolved in primary motor and sensory cortices; around 12 months the cortical subplate in prefrontal and parieto-temporal cortices and cerebellar external granular layer have disappeared. This review stresses that families are pivotal in early intervention. It summarizes evidence on the effectiveness of early intervention in medically fragile neonates, infants at low to moderate risk, infants with or at high risk of CP and with or at high risk of ASD.