Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation

Impact of early nutrition on brain development and neurocognitive outcomes in very preterm infants

BACKGROUND

Malnutrition of preterm infants may negatively affect brain growth and later neurocognitive function. We aimed to investigate the association between very preterm infants' macronutrient intakes, and brain MRI at term and neurodevelopment at 2 years.

METHODS

Single-center, retrospective cohort including extremely (22-27w) and very (28-31w) preterm infants born 2011-2014. The intakes of fluid, protein, carbohydrate, fat, and total calories during days 0-28 together with body weights were assessed in relation to brain MRI (morphology, volumetry, diffusion-weighted imaging) at term, and cognition (BSID-III) at 2 years, using adjusted multivariable regression analyses.

RESULTS

Seventy-two infants were included. A lower (p < 0.001) caloric intake in extremely preterm (n = 26) than in very preterm (n = 46) infants did not translate to any differences in brain volumes. While bivariate correlations (p < 0.01) were found between the enteral intakes of all macronutrients, and white matter volume and apparent diffusion coefficients, none of the correlations remained significant after adjusting for covariates in the multivariable analysis. Similarly, no associations between nutrient intakes and cognitive development remained after covariate adjustment.

CONCLUSION

In a cohort of preterm infants receiving macronutrient intakes meeting current recommendations, individual variations in nutrition did not influence brain growth or neurodevelopment.

IMPACT

Early postnatal macronutrient intake was not associated with brain volumes at term or neurocognitive outcomes at 2 years in very preterm infants All infants received nutritional intakes meeting current recommendations Adequate macronutrient intake based on a standardized protocol may eliminate the need for further minor adjustments in the pursuit of supporting brain growth and neurodevelopment in preterm infants.

Subject-specific atlas for automatic brain tissue segmentation of neonatal magnetic resonance images

Developing advanced systems for 3D brain tissue segmentation from neonatal magnetic resonance (MR) images is vital for newborn structural analysis. However, automatic segmentation of neonatal brain tissues is challenging due to smaller head size and inverted T1/T2 tissue contrast compared to adults. In this work, a subject-specific atlas based technique is presented for segmentation of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) from neonatal MR images. It involves atlas selection, subject-specific atlas creation using random forest (RF) classifier, and brain tissue segmentation using the expectation maximization-Markov random field (EM-MRF) method. To increase the segmentation accuracy, different tissue intensity- and gradient-based features were used. Evaluation on 40 neonatal MR images (gestational age of 37-44 weeks) demonstrated an overall accuracy of 94.3% and an average Dice similarity coefficient (DSC) of 0.945 (GM), 0.947 (WM), and 0.912 (CSF). Compared to multi-atlas segmentation methods like SEGMA and EM-MRF with multiple atlases, our method improved accuracy by up to 4%, particularly in complex tissue regions. Our proposed method allows accurate brain tissue segmentation, a crucial step in brain magnetic resonance imaging (MRI) applications including brain surface reconstruction and realistic head model creation in neonates.

Lactoferrin intake from maternal milk during the neonatal hospitalization and early brain development among preterm infants

BACKGROUND

Lactoferrin is an immuno-modulatory nutrient in human milk that may be neuroprotective.

METHODS

In 36 infants born <32 weeks' gestation, we sampled human milk at 14 and 28 days of chronologic age and measured lactoferrin by electrochemiluminescence multiplex immunoassay. Using 3T quantitative brain magnetic resonance imaging scans obtained at term equivalent, we estimated total and regional brain volumes. We compared outcomes between infants exposed to low (bottom tertile, range 0.06-0.13 mg/mL) vs. high (top tertile, range 0.22-0.35 mg/mL) lactoferrin using median regression in models adjusted for gestational age, birth weight z-score, sex, and postmenstrual age.

RESULTS

Compared to infants exposed to low lactoferrin, infants exposed to high lactoferrin had 43.9 cc (95% CI: 7.6, 80.4) larger total brain volume, 48.3 cc (95% CI: 12.1, 84.6) larger cortical gray matter, and 3.8 cc (95% CI: 0.7, 7.0) larger deep gray matter volume at term equivalent age. Other regional brain volumes were not statistically different between groups.

CONCLUSION

Higher lactoferrin exposure during the neonatal hospitalization was associated with larger total brain and gray matter volumes, suggesting that lactoferrin may have potential as a dietary supplement to enhance brain growth in the neonatal intensive care unit setting.

IMPACT

This study suggests that lactoferrin, a whey protein found in human milk, may be beneficial for preterm infant brain development, and therefore has potential as a dietary supplement in the neonatal intensive care unit setting.

VINNA for neonates: Orientation independence through latent augmentations

A robust, fast, and accurate segmentation of neonatal brain images is highly desired to better understand and detect changes during development and disease, specifically considering the rise in imaging studies for this cohort. Yet, the limited availability of ground truth datasets, lack of standardized acquisition protocols, and wide variations of head positioning in the scanner pose challenges for method development. A few automated image analysis pipelines exist for newborn brain Magnetic Resonance Image (MRI) segmentation, but they often rely on time-consuming non-linear spatial registration procedures and require resampling to a common resolution, subject to loss of information due to interpolation and down-sampling. Without registration and image resampling, variations with respect to head positions and voxel resolutions have to be addressed differently. In deep learning, external augmentations such as rotation, translation, and scaling are traditionally used to artificially expand the representation of spatial variability, which subsequently increases both the training dataset size and robustness. However, these transformations in the image space still require resampling, reducing accuracy specifically in the context of label interpolation. We recently introduced the concept of resolution-independence with the Voxel-size Independent Neural Network framework, VINN. Here, we extend this concept by additionally shifting all rigid-transforms into the network architecture with a four degree of freedom (4-DOF) transform module, enabling resolution-aware internal augmentations (VINNA) for deep learning. In this work, we show that VINNA (i) significantly outperforms state-of-the-art external augmentation approaches, (ii) effectively addresses the head variations present specifically in newborn datasets, and (iii) retains high segmentation accuracy across a range of resolutions (0.5-1.0 mm). Furthermore, the 4-DOF transform module together with internal augmentations is a powerful, general approach to implement spatial augmentation without requiring image or label interpolation. The specific network application to newborns will be made publicly available as VINNA4neonates.

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.

Predicting 2-year neurodevelopmental outcomes in preterm infants using multimodal structural brain magnetic resonance imaging with local connectivity

The neurodevelopmental outcomes of preterm infants can be stratified based on the level of prematurity. We explored brain structural networks in extremely preterm (EP; < 28 weeks of gestation) and very-to-late (V-LP; ≥ 28 and < 37 weeks of gestation) preterm infants at term-equivalent age to predict 2-year neurodevelopmental outcomes. Using MRI and diffusion MRI on 62 EP and 131 V-LP infants, we built a multimodal feature set for volumetric and structural network analysis. We employed linear and nonlinear machine learning models to predict the Bayley Scales of Infant and Toddler Development, Third Edition (BSID-III) scores, assessing predictive accuracy and feature importance. Our findings revealed that models incorporating local connectivity features demonstrated high predictive performance for BSID-III subsets in preterm infants. Specifically, for cognitive scores in preterm (variance explained, 17%) and V-LP infants (variance explained, 17%), and for motor scores in EP infants (variance explained, 15%), models with local connectivity features outperformed others. Additionally, a model using only local connectivity features effectively predicted language scores in preterm infants (variance explained, 15%). This study underscores the value of multimodal feature sets, particularly local connectivity, in predicting neurodevelopmental outcomes, highlighting the utility of machine learning in understanding microstructural changes and their implications for early intervention.

Updates to the Melbourne Children's Regional Infant Brain Software Package (M-CRIB-S)

The delineation of cortical areas on magnetic resonance images (MRI) is important for understanding the complexities of the developing human brain. The previous version of the Melbourne Children's Regional Infant Brain (M-CRIB-S) (Adamson et al. Scientific Reports, 10(1), 10, 2020) is a software package that performs whole-brain segmentation, cortical surface extraction and parcellation of the neonatal brain. Available cortical parcellation schemes in the M-CRIB-S are the adult-compatible 34- and 31-region per hemisphere Desikan-Killiany (DK) and Desikan-Killiany-Tourville (DKT), respectively. We present a major update to the software package which achieves two aims: 1) to make the voxel-based segmentation outputs derived from the Freesurfer-compatible M-CRIB scheme, and 2) to improve the accuracy of whole-brain segmentation and cortical surface extraction. Cortical surface extraction has been improved with additional steps to improve penetration of the inner surface into thin gyri. The improved cortical surface extraction is shown to increase the robustness of measures such as surface area, cortical thickness, and cortical volume.

The past, current, and future of neonatal intensive care units with artificial intelligence: a systematic review

Machine learning and deep learning are two subsets of artificial intelligence that involve teaching computers to learn and make decisions from any sort of data. Most recent developments in artificial intelligence are coming from deep learning, which has proven revolutionary in almost all fields, from computer vision to health sciences. The effects of deep learning in medicine have changed the conventional ways of clinical application significantly. Although some sub-fields of medicine, such as pediatrics, have been relatively slow in receiving the critical benefits of deep learning, related research in pediatrics has started to accumulate to a significant level, too. Hence, in this paper, we review recently developed machine learning and deep learning-based solutions for neonatology applications. We systematically evaluate the roles of both classical machine learning and deep learning in neonatology applications, define the methodologies, including algorithmic developments, and describe the remaining challenges in the assessment of neonatal diseases by using PRISMA 2020 guidelines. To date, the primary areas of focus in neonatology regarding AI applications have included survival analysis, neuroimaging, analysis of vital parameters and biosignals, and retinopathy of prematurity diagnosis. We have categorically summarized 106 research articles from 1996 to 2022 and discussed their pros and cons, respectively. In this systematic review, we aimed to further enhance the comprehensiveness of the study. We also discuss possible directions for new AI models and the future of neonatology with the rising power of AI, suggesting roadmaps for the integration of AI into neonatal intensive care units.

Maternal pre-pregnancy obesity affects the uncinate fasciculus white matter tract in preterm infants

Background

A growing body of evidence suggests an association between a higher maternal pre-pregnancy body mass index (BMI) and adverse long-term neurodevelopmental outcomes for their offspring. Despite recent attention to the effects of maternal obesity on fetal and neonatal brain development, changes in the brain microstructure of preterm infants born to mothers with pre-pregnancy obesity are still not well understood. This study aimed to detect the changes in the brain microstructure of obese mothers in pre-pregnancy and their offspring born as preterm infants using diffusion tensor imaging (DTI).

Methods

A total of 32 preterm infants (born to 16 mothers with normal BMI and 16 mothers with a high BMI) at <32 weeks of gestation without brain injury underwent brain magnetic resonance imaging at term-equivalent age (TEA). The BMI of all pregnant women was measured within approximately 12 weeks before pregnancy or the first 2 weeks of gestation. We analyzed the brain volume using a morphologically adaptive neonatal tissue segmentation toolbox and calculated the major white matter (WM) tracts using probabilistic maps of the Johns Hopkins University neonatal atlas. We investigated the differences in brain volume and WM microstructure between preterm infants of mothers with normal and high BMI. The DTI parameters were compared among groups using analysis of covariance adjusted for postmenstrual age at scan and multiple comparisons.

Results

Preterm infants born to mothers with a high BMI showed significantly increased cortical gray matter volume (p = 0.001) and decreased WM volume (p = 0.003) after controlling for postmenstrual age and multiple comparisons. We found a significantly lower axial diffusivity in the uncinate fasciculus (UNC) in mothers with high BMI than that in mothers with normal BMI (1.690 ± 0.066 vs. 1.762 ± 0.101, respectively; p = 0.005).

Conclusion

Our study is the first to demonstrate that maternal obesity impacts perinatal brain development patterns in preterm infants at TEA, even in the absence of apparent brain injury. These findings provide evidence for the detrimental effects of maternal obesity on brain developmental trajectories in offspring and suggest potential neurodevelopmental outcomes based on an altered UNC WM microstructure, which is known to be critical for language and social-emotional functions.

Serial neuroimaging of brain growth and development in very preterm infants receiving tailored neuropromotive support in the NICU. Protocol for a prospective cohort study

Introduction

Children born very preterm (VP) remain at risk for long-term neurodevelopmental impairment. Patterns of brain growth and injury, and how early neuropromotive therapies might mitigate developmental risk in VP infants remain insufficiently understood.

Methods

This is a prospective cohort study of VP infants born at/before 32 weeks gestation. The study will enroll n = 75 consecutively-born VP infants in a level-III NICU. Exposed infants will be categorized into two groups (group 1: low-risk, n = 25 or group 2: high-risk, n = 25) based on the degree of neurological injury on early brain magnetic resonance imaging (MRI) at enrollment. Infants in the low-risk group (i.e., without significant injury defined as intraventricular hemorrhage with dilation, moderate or severe white matter injury, or cerebellar hemorrhage) will receive neurodevelopmental support utilizing the Supporting and Enhancing NICU Sensory Experiences (SENSE) program, while infants in the high-risk group (with neurological injury) will receive more intensive neurorehabilitative support (SENSE-plus). Age-specific, tailored sensory experiences will be facilitated contingently, preferentially by the infant's family with coaching from NICU staff. VP infants in exposure groups will undergo a brain MRI approximately every 2 weeks from enrollment until term-equivalent to monitor brain growth and evolution of injury. Exposed infants will be compared with a reference group (group 3: n = 25), i.e. VP infants whose families decline initial enrollment in SENSE, and subsequently undergo a term-equivalent brain MRI for other purposes. The primary aim of this study is characterization of term-equivalent brain growth and development among VP infants receiving NICU-based neuropromotive interventions compared to VP infants receiving the standard of care. Secondary aims include defining the timing and factors associated with total and regional brain growth on serial brain MRI among VP infants, (Aim 2), and using early imaging to tailor developmental intervention in the NICU while exploring associations with outcomes in VP infants at discharge and at two years corrected age (Aim 3).

Discussion

This study will address gaps in understanding patterns of brain growth and injury drawing on serial MRI of hospitalized VP infants. These data will also explore the impact of intensive, tailored neuropromotive support delivered prior to term-equivalent on child and family outcomes.

Association of Acute Infarct Topography With Development of Cerebral Palsy and Neurologic Impairment in Neonates With Stroke

BACKGROUND AND OBJECTIVES

Research investigating neonatal arterial ischemic stroke (NAIS) outcomes have shown that combined cortical and basal ganglia infarction or involvement of the corticospinal tract predict cerebral palsy (CP). The research question was whether voxel-based lesion-symptom mapping (VLSM) on acute MRI can identify brain regions associated with CP and neurodevelopmental impairments in NAIS.

METHODS

Newborns were recruited from prospective Australian and Swiss pediatric stroke registries. CP diagnosis was based on clinical examination. Language and cognitive-behavioral impairments were assessed using the Pediatric Stroke Outcome Measure, dichotomized to good (0-0.5) or poor (≥1), at ≥18 months of age. Infarcts were manually segmented using diffusion-weighted imaging, registered to a neonatal-specific brain template. VLSM was conducted using MATLAB SPM12 toolbox. A general linear model was used to correlate lesion masks with motor, language, and cognitive-behavioral outcomes. Voxel-wise t-statistics were calculated, correcting for multiple comparisons using family-wise error (FWE) rate.

RESULTS

Eighty-five newborns met the inclusion criteria. Infarct lateralization was left hemisphere (62%), right (8%), and bilateral (30%). At a median age of 2.1 years (interquartile range 1.9-2.6), 33% developed CP and 42% had neurologic impairments. Fifty-four grey and white matter regions correlated with CP (t > 4.33; FWE < 0.05), including primary motor pathway regions, such as the precentral gyrus, and cerebral peduncle, and regions functionally connected to the primary motor pathway, such as the pallidum, and corpus callosum motor segment. No significant correlations were found for language or cognitive-behavioral outcomes.

DISCUSSION

CP after NAIS correlates with infarct regions directly involved in motor control and in functionally connected regions. Areas associated with language or cognitive-behavioral impairment are less clear.

Brain MRI segmentation of Zika-Exposed normocephalic infants shows smaller amygdala volumes

BACKGROUND

Infants with congenital Zika syndrome (CZS) are known to exhibit characteristic brain abnormalities. However, the brain anatomy of Zika virus (ZIKV)-exposed infants, born to ZIKV-positive pregnant mothers, who have normal-appearing head characteristics at birth, has not been evaluated in detail. The aim of this prospective study is, therefore, to compare the cortical and subcortical brain structural volume measures of ZIKV-exposed normocephalic infants to age-matched healthy controls.

METHODS AND FINDINGS

We acquired T2-MRI of the whole brain of 18 ZIKV-exposed infants and 8 normal controls on a 3T MRI scanner. The MR images were auto-segmented into eight tissue types and anatomical regions including the white matter, cortical grey matter, deep nuclear grey matter, corticospinal fluid, amygdala, hippocampus, cerebellum, and brainstem. We determined the volumes of these regions and calculated the total intracranial volume (TICV) and head circumference (HC). We compared these measurements between the two groups, controlling for infant age at scan, by first comparing results for all subjects in each group and secondly performing a subgroup analysis for subjects below 8 weeks of postnatal age at scan. ZIKV-exposed infants demonstrated a significant decrease in amygdala volume compared to the control group in both the group and subgroup comparisons (p<0.05, corrected for multiple comparisons using FDR). No significant volume differences were observed in TICV, HC, or any specific brain tissue structures or regions. Study limitations include small sample size, which was due to abrupt cessation of extramural funding as the ZIKV epidemic waned.

CONCLUSION

ZIKV-exposed infants exhibited smaller volumes in the amygdala, a brain region primarily involved in emotional and behavioral processing. This brain MRI finding may lead to poorer behavioral outcomes and warrants long-term monitoring of pediatric cases of infants with gestational exposure to Zika virus as well as other neurotropic viruses.

An automatic and accurate deep learning-based neuroimaging pipeline for the neonatal brain

BACKGROUND

Accurate segmentation of neonatal brain tissues and structures is crucial for studying normal development and diagnosing early neurodevelopmental disorders. However, there is a lack of an end-to-end pipeline for automated segmentation and imaging analysis of the normal and abnormal neonatal brain.

OBJECTIVE

To develop and validate a deep learning-based pipeline for neonatal brain segmentation and analysis of structural magnetic resonance images (MRI).

MATERIALS AND METHODS

Two cohorts were enrolled in the study, including cohort 1 (582 neonates from the developing Human Connectome Project) and cohort 2 (37 neonates imaged using a 3.0-tesla MRI scanner in our hospital).We developed a deep leaning-based architecture capable of brain segmentation into 9 tissues and 87 structures. Then, extensive validations were performed for accuracy, effectiveness, robustness and generality of the pipeline. Furthermore, regional volume and cortical surface estimation were measured through in-house bash script implemented in FSL (Oxford Centre for Functional MRI of the Brain Software Library) to ensure reliability of the pipeline. Dice similarity score (DSC), the 95th percentile Hausdorff distance (H95) and intraclass correlation coefficient (ICC) were calculated to assess the quality of our pipeline. Finally, we finetuned and validated our pipeline on 2-dimensional thick-slice MRI in cohorts 1 and 2.

RESULTS

The deep learning-based model showed excellent performance for neonatal brain tissue and structural segmentation, with the best DSC and the 95th percentile Hausdorff distance (H95) of 0.96 and 0.99 mm, respectively. In terms of regional volume and cortical surface analysis, our model showed good agreement with ground truth. The ICC values for the regional volume were all above 0.80. Considering the thick-slice image pipeline, the same trend was observed for brain segmentation and analysis. The best DSC and H95 were 0.92 and 3.00 mm, respectively. The regional volumes and surface curvature had ICC values just below 0.80.

CONCLUSIONS

We propose an automatic, accurate, stable and reliable pipeline for neonatal brain segmentation and analysis from thin and thick structural MRI. The external validation showed very good reproducibility of the pipeline.

Infant Perioperative Risk Factors and Adverse Brain Findings Following Long-Gap Esophageal Atresia Repair

Recent findings implicate brain vulnerability following long-gap esophageal atresia (LGEA) repair. We explored the relationship between easily quantifiable clinical measures and previously reported brain findings in a pilot cohort of infants following LGEA repair. MRI measures (number of qualitative brain findings; normalized brain and corpus callosum volumes) were previously reported in term-born and early-to-late premature infants (n = 13/group) <1 year following LGEA repair with the Foker process. The severity of underlying disease was classified by an (1) American Society of Anesthesiologist (ASA) physical status and (2) Pediatric Risk Assessment (PRAm) scores. Additional clinical end-point measures included: anesthesia exposure (number of events; cumulative minimal alveolar concentration (MAC) exposure in hours), length (in days) of postoperative intubated sedation, paralysis, antibiotic, steroid, and total parenteral nutrition (TPN) treatment. Associations between clinical end-point measures and brain MRI data were tested using Spearman rho and multivariable linear regression. Premature infants were more critically ill per ASA scores, which showed a positive association with the number of cranial MRI findings. Clinical end-point measures together significantly predicted the number of cranial MRI findings for both term-born and premature infant groups, but none of the individual clinical measures did on their own. Listed easily quantifiable clinical end-point measures could be used together as indirect markers in assessing the risk of brain abnormalities following LGEA repair.

Growth of prefrontal and limbic brain regions and anxiety disorders in children born very preterm

BACKGROUND

Children born very preterm (VP) display altered growth in corticolimbic structures compared with full-term peers. Given the association between the cortiocolimbic system and anxiety, this study aimed to compare developmental trajectories of corticolimbic regions in VP children with and without anxiety diagnosis at 13 years.

METHODS

MRI data from 124 VP children were used to calculate whole brain and corticolimbic region volumes at term-equivalent age (TEA), 7 and 13 years. The presence of an anxiety disorder was assessed at 13 years using a structured clinical interview.

RESULTS

VP children who met criteria for an anxiety disorder at 13 years (n = 16) displayed altered trajectories for intracranial volume (ICV, p < 0.0001), total brain volume (TBV, p = 0.029), the right amygdala (p = 0.0009) and left hippocampus (p = 0.029) compared with VP children without anxiety (n = 108), with trends in the right hippocampus (p = 0.062) and left medial orbitofrontal cortex (p = 0.079). Altered trajectories predominantly reflected slower growth in early childhood (0-7 years) for ICV (β = -0.461, p = 0.020), TBV (β = -0.503, p = 0.021), left (β = -0.518, p = 0.020) and right hippocampi (β = -0.469, p = 0.020) and left medial orbitofrontal cortex (β = -0.761, p = 0.020) and did not persist after adjusting for TBV and social risk.

CONCLUSIONS

Region- and time-specific alterations in the development of the corticolimbic system in children born VP may help to explain an increase in anxiety disorders observed in this population.

Body size and brain volumetry in the rat following prolonged morphine administration in infancy and adulthood

Background

Prolonged morphine treatment in infancy is associated with a high incidence of opioid tolerance and dependence, but our knowledge of the long-term consequences of this treatment is sparse. Using a rodent model, we examined the (1) short- and (2) long-term effects of prolonged morphine administration in infancy on body weight and brain volume, and (3) we evaluated if subsequent dosing in adulthood poses an increased brain vulnerability.

Methods

Newborn rats received subcutaneous injections of either morphine or equal volume of saline twice daily for the first two weeks of life. In adulthood, animals received an additional two weeks of saline or morphine injections before undergoing structural brain MRI. After completion of treatment, structural T2-weigthed MRI images were acquired on a 7 T preclinical scanner (Bruker) using a RARE FSE sequence. Total and regional brain volumes were manually extracted from the MRI images using ITK-SNAP (v.3.6). Regions of interest included the brainstem, the cerebellum, as well as the forebrain and its components: the cerebral cortex, hippocampus, and deep gray matter (including basal ganglia, thalamus, hypothalamus, ventral tegmental area). Absolute (cm³) and normalized (as % total brain volume) values were compared using a one-way ANOVA with Tukey HSD post-hoc test.

Results

Prolonged morphine administration in infancy was associated with lower body weight and globally smaller brain volumes, which was not different between the sexes. In adulthood, females had lower body weights than males, but no difference was observed in brain volumes between treatment groups. Our results are suggestive of no long-term effect of prolonged morphine treatment in infancy with respect to body weight and brain size in either sex. Interestingly, prolonged morphine administration in adulthood was associated with smaller brain volumes that differed by sex only in case of previous exposure to morphine in infancy. Specifically, we report significantly smaller total brain volume of female rats on account of decreased volumes of forebrain and cortex.

Conclusions

Our study provides insight into the short- and long-term consequences of prolonged morphine administration in an infant rat model and suggests brain vulnerability to subsequent exposure in adulthood that might differ with sex.

Associations of body composition with regional brain volumes and white matter microstructure in very preterm infants

OBJECTIVE

To determine associations between body composition and concurrent measures of brain development including (1) Tissue-specific brain volumes and (2) White matter microstructure, among very preterm infants at term equivalent age.

DESIGN

Prospective observational study.

SETTING

Single-centre academic level III neonatal intensive care unit.

PATIENTS

We studied 85 infants born <33 weeks' gestation.

METHODS

At term equivalent age, infants underwent air displacement plethysmography to determine body composition, and brain MRI from which we quantified tissue-specific brain volumes and fractional anisotropy (FA) of white matter tracts. We estimated associations of fat and lean mass Z-scores with each brain outcome, using linear mixed models adjusted for intrafamilial correlation among twins and potential confounding variables.

RESULTS

Median gestational age was 29 weeks (range 23.4-32.9). One unit greater lean mass Z-score was associated with larger total brain volume (10.5 cc, 95% CI 3.8 to 17.2); larger volumes of the cerebellum (1.2 cc, 95% CI 0.5 to 1.9) and white matter (4.5 cc, 95% CI 0.7 to 8.3); and greater FA in the left cingulum (0.3%, 95% CI 0.1% to 0.6%), right uncinate fasciculus (0.2%, 95% CI 0.0% to 0.5%), and right posterior limb of the internal capsule (0.3%, 95% CI 0.03% to 0.6%). Fat Z-scores were not associated with any outcome.

CONCLUSIONS

Lean mass-but not fat-at term was associated with larger brain volume and white matter microstructure differences that suggest improved maturation. Lean mass accrual may index brain growth and development.

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.

NeoRS: A Neonatal Resting State fMRI Data Preprocessing Pipeline

Resting state functional MRI (rsfMRI) has been shown to be a promising tool to study intrinsic brain functional connectivity and assess its integrity in cerebral development. In neonates, where functional MRI is limited to very few paradigms, rsfMRI was shown to be a relevant tool to explore regional interactions of brain networks. However, to identify the resting state networks, data needs to be carefully processed to reduce artifacts compromising the interpretation of results. Because of the non-collaborative nature of the neonates, the differences in brain size and the reversed contrast compared to adults due to myelination, neonates can’t be processed with the existing adult pipelines, as they are not adapted. Therefore, we developed NeoRS, a rsfMRI pipeline for neonates. The pipeline relies on popular neuroimaging tools (FSL, AFNI, and SPM) and is optimized for the neonatal brain. The main processing steps include image registration to an atlas, skull stripping, tissue segmentation, slice timing and head motion correction and regression of confounds which compromise functional data interpretation. To address the specificity of neonatal brain imaging, particular attention was given to registration including neonatal atlas type and parameters, such as brain size variations, and contrast differences compared to adults. Furthermore, head motion was scrutinized, and motion management optimized, as it is a major issue when processing neonatal rsfMRI data. The pipeline includes quality control using visual assessment checkpoints. To assess the effectiveness of NeoRS processing steps we used the neonatal data from the Baby Connectome Project dataset including a total of 10 neonates. NeoRS was designed to work on both multi-band and single-band acquisitions and is applicable on smaller datasets. NeoRS also includes popular functional connectivity analysis features such as seed-to-seed or seed-to-voxel correlations. Language, default mode, dorsal attention, visual, ventral attention, motor and fronto-parietal networks were evaluated. Topology found the different analyzed networks were in agreement with previously published studies in the neonate. NeoRS is coded in Matlab and allows parallel computing to reduce computational times; it is open-source and available on GitHub (https://github.com/venguix/NeoRS). NeoRS allows robust image processing of the neonatal rsfMRI data that can be readily customized to different datasets.

Improved neonatal brain MRI segmentation by interpolation of motion corrupted slices

BACKGROUND AND PURPOSE

To apply and evaluate an intensity-based interpolation technique, enabling segmentation of motion-affected neonatal brain MRI.

METHODS

Moderate-late preterm infants were enrolled in a prospective cohort study (Brain Imaging in Moderate-late Preterm infants "BIMP-study") between August 2017 and November 2019. T2-weighted MRI was performed around term equivalent age on a 3T MRI. Scans without motion (n = 27 [24%], control group) and with moderate-severe motion (n = 33 [29%]) were included. Motion-affected slices were re-estimated using intensity-based shape-preserving cubic spline interpolation, and automatically segmented in eight structures. Quality of interpolation and segmentation was visually assessed for errors after interpolation. Reliability was tested using interpolated control group scans (18/54 axial slices). Structural similarity index (SSIM) was used to compare T2-weighted scans, and Sørensen-Dice was used to compare segmentation before and after interpolation. Finally, volumes of brain structures of the control group were used assessing sensitivity (absolute mean fraction difference) and bias (confidence interval of mean difference).

RESULTS

Visually, segmentation of 25 scans (22%) with motion artifacts improved with interpolation, while segmentation of eight scans (7%) with adjacent motion-affected slices did not improve. Average SSIM was .895 and Sørensen-Dice coefficients ranged between .87 and .97. Absolute mean fraction difference was ≤0.17 for less than or equal to five interpolated slices. Confidence intervals revealed a small bias for cortical gray matter (0.14-3.07 cm3 ), cerebrospinal fluid (0.39-1.65 cm3 ), deep gray matter (0.74-1.01 cm3 ), and brainstem volumes (0.07-0.28 cm3 ) and a negative bias in white matter volumes (-4.47 to -1.65 cm3 ).

CONCLUSION

According to qualitative and quantitative assessment, intensity-based interpolation reduced the percentage of discarded scans from 29% to 7%.

Brain White Matter Development Over the First 13 Years in Very Preterm and Typically Developing Children Based on the T 1-w/T 2-w Ratio

BACKGROUND AND OBJECTIVES

To investigate brain regional white matter development in full-term (FT) and very preterm (VP) children at term equivalent and 7 and 13 years of age based on the ratio of T 1- and T 2-weighted MRI (T 1-w/T 2-w), including (1) whether longitudinal changes differ between birth groups or sexes, (2) associations with perinatal risk factors in VP children, and (3) relationships with neurodevelopmental outcomes at 13 years.

METHODS

Prospective longitudinal cohort study of VP (born <30 weeks' gestation or <1,250 g) and FT infants born between 2001 and 2004 and followed up at term equivalent and 7 and 13 years of age, including MRI studies and neurodevelopmental assessments. T 1-w/T 2-w images were parcellated into 48 white matter regions of interest.

RESULTS

Of 224 VP participants and 76 FT participants, 197 VP and 55 FT participants had useable T 1-w/T 2-w data from at least one timepoint. T 1-w/T 2-w values increased between term equivalent and 13 years of age, with little evidence that longitudinal changes varied between birth groups or sexes. VP birth, neonatal brain abnormalities, being small for gestational age, and postnatal infection were associated with reduced regional T 1-w/T 2-w values in childhood and adolescence. Increased T 1-w/T 2-w values across the white matter at 13 years were associated with better motor and working memory function for all children. Within the FT group only, larger increases in T 1-w/T 2-w values from term equivalent to 7 years were associated with poorer attention and executive function, and higher T 1-w/T 2-w values at 7 years were associated with poorer mathematics performance.

DISCUSSION

VP birth and multiple known perinatal risk factors are associated with long-term reductions in the T 1-w/T 2-w ratio in white matter regions in childhood and adolescence, which may relate to alterations in microstructure and myelin content. Increased T 1-w/T 2-w ratio at 13 years appeared to be associated with better motor and working memory function and there appeared to be developmental differences between VP and FT children in the associations for attention, executive functioning, and mathematics performance.

Altered microstructure of the splenium of corpus callosum is associated with neurodevelopmental impairment in preterm infants with necrotizing enterocolitis

Background

Necrotizing enterocolitis (NEC) is a devastating disease in preterm infants with significant morbidities, including neurodevelopmental impairment (NDI). This study aimed to investigate whether NEC is associated with (1) brain volume expansion and white matter maturation using diffusion tensor imaging analysis and (2) NDI compared with preterm infants without NEC.

Methods

We included 86 preterm infants (20 with NEC and 66 without NEC) with no evidence of brain abnormalities on trans-fontanelle ultrasonography and magnetic resonance imaging at term-equivalent age (TEA). Regional brain volume analysis and white matter tractography were performed to study brain microstructure alterations. NDI was assessed using the Bayley Scales of Infant and Toddler Development-III (BSID-III) at 18 months of corrected age (CA).

Results

Preterm infants with NEC showed significantly high risk of motor impairment (odds ratio 58.26, 95% confidence interval 7.80–435.12, p < 0.001). We found significantly increased mean diffusivity (MD) in the splenium of corpus callosum (sCC) (p = 0.001) and the left corticospinal tract (p = 0.001) in preterm infants with NEC. The sCC with increased MD showed a negative association with the BSID-III language (p = 0.025) and motor scores (p = 0.002) at 18 months of CA, implying the relevance of sCC integrity with later NDI.

Conclusion

The white matter microstructure differed between preterm infants with and without NEC. The prognostic value of network parameters of sCC at TEA may provide better information for the early detection of NDI in preterm infants.

Does ventricle size contribute to cognitive outcomes in posthemorrhagic hydrocephalus? Role of early definitive intervention

OBJECTIVE

Posthemorrhagic hydrocephalus (PHH) is associated with significant morbidity, smaller hippocampal volumes, and impaired neurodevelopment in preterm infants. The timing of temporary CSF (tCSF) diversion has been studied; however, the optimal time for permanent CSF (pCSF) diversion is unknown. The objective of this study was to determine whether cumulative ventricle size or timing of pCSF diversion is associated with neurodevelopmental outcome and hippocampal size in preterm infants with PHH.

METHODS

Twenty-five very preterm neonates (born at ≤ 32 weeks' gestational age) with high-grade intraventricular hemorrhage (IVH), subsequent PHH, and pCSF diversion with a ventriculoperitoneal shunt (n = 20) or endoscopic third ventriculostomy (n = 5) were followed until 2 years of age. Infants underwent serial cranial ultrasounds from birth until 1 year after pCSF diversion, brain MRI at term-equivalent age, and assessment based on the Bayley Scales of Infant and Toddler Development, Third Edition, at 2 years of age. Frontooccipital horn ratio (FOHR) measurements were derived from cranial ultrasounds and term-equivalent brain MRI. Hippocampal volumes were segmented and calculated from term-equivalent brain MRI. Cumulative ventricle size until the time of pCSF diversion was estimated using FOHR measurements from each cranial ultrasound performed prior to permanent intervention.

RESULTS

The average gestational ages at tCSF and pCSF diversion were 28.9 and 39.0 weeks, respectively. An earlier chronological age at the time of pCSF diversion was associated with larger right hippocampal volumes on term-equivalent MRI (Pearson's r = -0.403, p = 0.046) and improved cognitive (r = -0.554, p = 0.047), motor (r = -0.487, p = 0.048), and language (r = -0.414, p = 0.021) outcomes at 2 years of age. Additionally, a smaller cumulative ventricle size from birth to pCSF diversion was associated with larger right hippocampal volumes (r = -0.483, p = 0.014) and improved cognitive (r = -0.711, p = 0.001), motor (r = -0.675, p = 0.003), and language (r = -0.618, p = 0.011) outcomes. There was no relationship between time to tCSF diversion or cumulative ventricle size prior to tCSF diversion and neurodevelopmental outcome or hippocampal size. Finally, a smaller cumulative ventricular size prior to either tCSF diversion or pCSF diversion was associated with a smaller ventricular size 1 year after pCSF diversion (r = 0.422, p = 0.040, R2 = 0.178 and r = 0.519, p = 0.009, R2 = 0.269, respectively).

CONCLUSIONS

In infants with PHH, a smaller cumulative ventricular size and shorter time to pCSF diversion were associated with larger right hippocampal volumes, improved neurocognitive outcomes, and reduced long-term ventriculomegaly. Future prospective randomized studies are needed to confirm these findings.

Infant study of hemispheric asymmetry after long-gap esophageal atresia repair

OBJECTIVES

Previous studies have demonstrated that infants are typically born with a left-greater-than-right forebrain asymmetry that reverses throughout the first year of life. We hypothesized that critically ill term-born and premature patients following surgical and critical care for long-gap esophageal atresia (LGEA) would exhibit alteration in expected forebrain asymmetry.

METHODS

Term-born (n = 13) and premature (n = 13) patients, and term-born controls (n = 23) <1 year corrected age underwent non-sedated research MRI following completion of LGEA treatment via Foker process. Structural T1- and T2-weighted images were collected, and ITK-SNAP was used for forebrain tissue segmentation and volume acquisition. Data were presented as absolute (cm³ ) and normalized (% total forebrain) volumes of the hemispheres. All measures were checked for normality, and group status was assessed using a general linear model with age at scan as a covariate.

RESULTS

Absolute volumes of both forebrain hemispheres were smaller in term-born and premature patients in comparison to controls (p < 0.001). Normalized hemispheric volume group differences were detected by T1-weighted analysis, with premature patients demonstrating right-greater-than-left hemisphere volumes in comparison to term-born patients and controls (p < 0.01). While normalized group differences were very subtle (a right hemispheric predominance of roughly 2% of forebrain volume), they represent a deviation from the expected pattern of hemispheric brain asymmetry.

INTERPRETATION

Our pilot quantitative MRI study of hemispheric volumes suggests that premature patients might be at risk of altered expected left-greater-than-right forebrain asymmetry following repair of LGEA. Future neurobehavioral studies in infants born with LGEA are needed to elucidate the functional significance of presented anatomical findings.

Mild brain lesions do not affect brain volumes in moderate-late preterm infants

PURPOSE

It is unknown whether frequently occurring mild brain lesions affect brain volumes in moderate (MP²; 32⁺⁰-33⁺⁶ weeks' gestation) and late (LP³; 34⁺⁰-35⁺⁶ weeks' gestation) preterm infants. Therefore, we aimed to investigate the effect of mild brain lesions on brain volumes in moderate-late preterm (MLPT⁴) infants and to compare brain volumes between MP and LP infants.

METHODS

From August 2017 to November 2019, eligible MLPT infants born at Isala Women and Children's Hospital were enrolled in a prospective cohort study (Brain Imaging in Moderate-late Preterm infants 'BIMP-study'). MRI was performed around term equivalent age (TEA⁵). MRI scans were assessed for (mild) brain lesions. T2-weighted images were used for automatic segmentation of eight brain structures. Linear regression analysis was performed to compare absolute and relative brain volumes between infants with and without mild brain lesions and between MP and LP infants.

RESULTS

36 MP and 68 LP infants were included. In infants with mild brain lesions, intracranial volume (B = 27.4 cm³, p = 0.02), cerebrospinal fluid (B = 8.78 cm³, p = 0.01) and cerebellar volumes (B = 1.70 cm³, p = 0.03) were significantly larger compared to infants without mild brain lesions. After correction for weight and postmenstrual age at MRI, these volumes were no longer significantly different. LP infants had larger brain volumes than MP infants, but differences were not significant. Relative brain volumes showed no significant differences in both analyses.

CONCLUSION

Neither having mild brain lesions, nor being born moderate prematurely affected brain volumes at TEA in MLPT infants.

Neonatal brain abnormalities and brain volumes associated with goal setting outcomes in very preterm 13-year-olds

Executive dysfunction including impaired goal setting (i.e., planning, organization skills, strategic reasoning) is documented in children born very preterm (VP; <30 weeks/<1250 g), however the neurological basis for this impairment is unknown. This study sought to examine the relationship between brain abnormalities and brain volumes on neonatal magnetic resonance imaging (MRI) and goal setting abilities of VP 13-year-olds. Participants were 159 children born VP in a prospective longitudinal study. Qualitative brain abnormality scores and quantitative brain volumes were derived from neonatal MRI brain scans (40 weeks' gestational age ± 2 weeks). Goal setting at 13 years was assessed using the Delis-Kaplan Executive Function Systems Tower Test, the Rey Complex Figure, and the Behavioural Assessment of the Dysexecutive System for Children Zoo Map and Six Part Test. A composite score was generated denoting overall performance on these goal setting measures. Separate regression models examined the association of neonatal brain abnormality scores and brain volumes with goal setting performance. There was evidence that higher neonatal white matter, deep grey matter and cerebellum abnormality scores were associated with poorer goal setting scores at 13 years. There was also evidence of positive associations between total brain volume, cerebellum, thalamic and cortical grey matter volumes and goal setting performance. Evidence for the associations largely persisted after controlling for potential confounders. Neonatal brain abnormality and brain volumes are associated with goal setting outcome in VP 13-year-olds. Used in conjunction with other clinical indicators, neonatal MRI may help to identify VP children at risk for later executive dysfunction.

Multiparametric Analysis of Cerebral Development in Preterm Infants Using Magnetic Resonance Imaging

Objectives

The severity of neurocognitive impairment increases with prematurity. However, its mechanisms remain poorly understood. Our aim was firstly to identify multiparametric magnetic resonance imaging (MRI) markers that differ according to the degree of prematurity, and secondly to evaluate the impact of clinical complications on these markers.

Materials and Methods

We prospectively enrolled preterm infants who were divided into two groups according to their degree of prematurity: extremely preterm (<28 weeks' gestational age) and very preterm (28-32 weeks' gestational age). They underwent a multiparametric brain MRI scan at term-equivalent age including morphological, diffusion tensor and arterial spin labeling (ASL) perfusion sequences. We quantified overall and regional volumes, diffusion parameters, and cerebral blood flow (CBF). We then compared the parameters for the two groups. We also assessed the effects of clinical data and potential MRI morphological abnormalities on those parameters.

Results

Thirty-four preterm infants were included. Extremely preterm infants (n = 13) had significantly higher frontal relative volumes (p = 0.04), frontal GM relative volumes (p = 0.03), and regional CBF than very preterm infants, but they had lower brainstem and insular relative volumes (respectively p = 0.008 and 0.04). Preterm infants with WM lesions on MRI had significantly lower overall GM CBF (13.3 ± 2 ml/100 g/min versus 17.7 ± 2.5, < ml/100 g/min p = 0.03).

Conclusion

Magnetic resonance imaging brain scans performed at term-equivalent age in preterm infants provide quantitative imaging parameters that differ with respect to the degree of prematurity, related to brain maturation.

Targeting human milk fortification to improve very preterm infant growth and brain development: study protocol for Nourish, a single-center randomized, controlled clinical trial

Background

Human milk is recommended for very preterm infants, but its variable macronutrient content may contribute to undernutrition during a critical period in development. We hypothesize that individually targeted human milk fortification is more effective in meeting macronutrient requirements than the current standard of care.

Methods

We designed a single-center randomized, controlled trial enrolling 130 infants born < 31 completed weeks’ gestation. Participants will receive fortified maternal and/or pasteurized donor milk but no formula. For participants in the intervention group, milk will be individually fortified with protein and fat modulars to achieve target levels based on daily point-of-care milk analysis with mid-infrared spectroscopy, in addition to standard fortification. The study diet will continue through 36 weeks’ postmenstrual age (PMA). Clinical staff and parents will be masked to study group. Primary outcomes include: 1) body length and lean body mass by air displacement plethysmography at 36 weeks’ PMA; 2) quantitative magnetic resonance imaging-based measures of brain size and microstructure at term equivalent age; and 3) Bayley-IV scales at 2 years’ corrected age.

Discussion

We expect this trial to provide important data regarding the effectiveness of individually targeted human milk fortification in the neonatal intensive care unit (NICU).

Trial registration

NCT03977259, registered 6 June, 2019.

Robust Cortical Thickness Morphometry of Neonatal Brain and Systematic Evaluation Using Multi-Site MRI Datasets

The human brain grows the most dramatically during the perinatal and early post-natal periods, during which pre-term birth or perinatal injury that may alter brain structure and lead to developmental anomalies. Thus, characterizing cortical thickness of developing brains remains an important goal. However, this task is often complicated by inaccurate cortical surface extraction due to small-size brains. Here, we propose a novel complex framework for the reconstruction of neonatal WM and pial surfaces, accounting for large partial volumes due to small-size brains. The proposed approach relies only on T1-weighted images unlike previous T2-weighted image-based approaches while only T1-weighted images are sometimes available under the different clinical/research setting. Deep neural networks are first introduced to the neonatal magnetic resonance imaging (MRI) pipeline to address the mis-segmentation of brain tissues. Furthermore, this pipeline enhances cortical boundary delineation using combined models of the cerebrospinal fluid (CSF)/GM boundary detection with edge gradient information and a new skeletonization of sulcal folding where no CSF voxels are seen due to the limited resolution. We also proposed a systematic evaluation using three independent datasets comprising 736 pre-term and 97 term neonates. Qualitative assessment for reconstructed cortical surfaces shows that 86.9% are rated as accurate across the three site datasets. In addition, our landmark-based evaluation shows that the mean displacement of the cortical surfaces from the true boundaries was less than a voxel size (0.532 ± 0.035 mm). Evaluating the proposed pipeline (namely NEOCIVET 2.0) shows the robustness and reproducibility across different sites and different age-groups. The mean cortical thickness measured positively correlated with post-menstrual age (PMA) at scan (p < 0.0001); Cingulate cortical areas grew the most rapidly whereas the inferior temporal cortex grew the least rapidly. The range of the cortical thickness measured was biologically congruent (1.3 mm at 28 weeks of PMA to 1.8 mm at term equivalent). Cortical thickness measured on T1 MRI using NEOCIVET 2.0 was compared with that on T2 using the established dHCP pipeline. It was difficult to conclude that either T1 or T2 imaging is more ideal to construct cortical surfaces. NEOCIVET 2.0 has been open to the public through CBRAIN (https://mcin-cnim.ca/technology/cbrain/), a web-based platform for processing brain imaging data.

A randomized controlled trial investigating the impact of maternal dietary supplementation with pomegranate juice on brain injury in infants with IUGR

Animal studies have demonstrated the therapeutic potential of polyphenol-rich pomegranate juice. We recently reported altered white matter microstructure and functional connectivity in the infant brain following in utero pomegranate juice exposure in pregnancies with intrauterine growth restriction (IUGR). This double-blind exploratory randomized controlled trial further investigates the impact of maternal pomegranate juice intake on brain structure and injury in a second cohort of IUGR pregnancies diagnosed at 24–34 weeks’ gestation. Ninety-nine mothers and their eligible fetuses (n = 103) were recruited from Brigham and Women’s Hospital and randomly assigned to 8 oz pomegranate (n = 56) or placebo (n = 47) juice to be consumed daily from enrollment to delivery. A subset of participants underwent fetal echocardiogram after 2 weeks on juice with no evidence of ductal constriction. 57 infants (n = 26 pomegranate, n = 31 placebo) underwent term-equivalent MRI for assessment of brain injury, volumes and white matter diffusion. No significant group differences were found in brain volumes or white matter microstructure; however, infants whose mothers consumed pomegranate juice demonstrated lower risk for brain injury, including any white or cortical grey matter injury compared to placebo. These preliminary findings suggest pomegranate juice may be a safe in utero neuroprotectant in pregnancies with known IUGR warranting continued investigation.

Clinical trial registration: NCT04394910, https://clinicaltrials.gov/ct2/show/NCT04394910, Registered May 20, 2020, initial participant enrollment January 16, 2016.

Artificial intelligence for automatic cerebral ventricle segmentation and volume calculation: a clinical tool for the evaluation of pediatric hydrocephalus

OBJECTIVE

Imaging evaluation of the cerebral ventricles is important for clinical decision-making in pediatric hydrocephalus. Although quantitative measurements of ventricular size, over time, can facilitate objective comparison, automated tools for calculating ventricular volume are not structured for clinical use. The authors aimed to develop a fully automated deep learning (DL) model for pediatric cerebral ventricle segmentation and volume calculation for widespread clinical implementation across multiple hospitals.

METHODS

The study cohort consisted of 200 children with obstructive hydrocephalus from four pediatric hospitals, along with 199 controls. Manual ventricle segmentation and volume calculation values served as "ground truth" data. An encoder-decoder convolutional neural network architecture, in which T2-weighted MR images were used as input, automatically delineated the ventricles and output volumetric measurements. On a held-out test set, segmentation accuracy was assessed using the Dice similarity coefficient (0 to 1) and volume calculation was assessed using linear regression. Model generalizability was evaluated on an external MRI data set from a fifth hospital. The DL model performance was compared against FreeSurfer research segmentation software.

RESULTS

Model segmentation performed with an overall Dice score of 0.901 (0.946 in hydrocephalus, 0.856 in controls). The model generalized to external MR images from a fifth pediatric hospital with a Dice score of 0.926. The model was more accurate than FreeSurfer, with faster operating times (1.48 seconds per scan).

CONCLUSIONS

The authors present a DL model for automatic ventricle segmentation and volume calculation that is more accurate and rapid than currently available methods. With near-immediate volumetric output and reliable performance across institutional scanner types, this model can be adapted to the real-time clinical evaluation of hydrocephalus and improve clinician workflow.

Imaging the rapidly developing brain: Current challenges for MRI studies in the first five years of life

Rapid and widespread changes in brain anatomy and physiology in the first five years of life present substantial challenges for developmental structural, functional, and diffusion MRI studies. One persistent challenge is that methods best suited to earlier developmental stages are suboptimal for later stages, which engenders a trade-off between using different, but age-appropriate, methods for different developmental stages or identical methods across stages. Both options have potential benefits, but also biases, as pipelines for each developmental stage can be matched on methods or the age-appropriateness of methods, but not both. This review describes the data acquisition, processing, and analysis challenges that introduce these potential biases and attempts to elucidate decisions and make recommendations that would optimize developmental comparisons.

Synthetic MRI demonstrates prolonged regional relaxation times in the brain of preterm born neonates with severe postnatal morbidity

BACKGROUND

To identify preterm infants at risk for neurodevelopment impairment that might benefit from early neurorehabilitation, early prognostic biomarkers of future outcomes are needed.

OBJECTIVE

To determine whether synthetic MRI is sensitive to age-related changes in regional tissue relaxation times in the brain of preterm born neonates when scanned at term equivalent age (TEA, 37-42 weeks), and to investigate whether severe postnatal morbidity results in prolonged regional tissue relaxation times.

MATERIALS AND METHODS

This retrospective study included 70 very preterm born infants scanned with conventional and synthetic MRI between January 2017 and June 2019 at TEA. Infants with severe postnatal morbidity were allocated to a high-risk group (n = 22). All other neonates were allocated to a low-risk group (n = 48). Linear regression analysis was performed to determine the relationship between relaxation times and postmenstrual age (PMA) at scan. Analysis of covariance was used to evaluate the impact of severe postnatal morbidity in the high-risk group on T1 and T2 relaxation times. Receiver operating characteristic (ROC) curves were plotted and analysed with area under the ROC curve (AUC) to evaluate the accuracy of classifying high-risk patients based on regional relaxation times.

RESULTS

A linear age-related decrease of T1 and T2 relaxation times correlating with PMA at scan (between 37 and 42 weeks) was found in the deep gray matter, the cerebellum, the cortex, and the posterior limb of the internal capsule (PLIC) (p < .005 each), but not in the global, frontal, parietal, or central white matter. Analysis of covariance for both risk groups, adjusted for PMA, revealed significantly prolonged regional tissue relaxation times in neonates with severe postnatal morbidity, which was best illustrated in the central white matter of the centrum semiovale (T1 Δ = 11.5%, T2 Δ = 13.4%, p < .001) and in the PLIC (T1 Δ = 9.2%, T2 Δ = 6.9%, p < .001). The relaxation times in the PLIC and the central white matter predicted high-risk status with excellent accuracy (AUC range 0.82-0.86).

CONCLUSION

Synthetic MRI-based relaxometry in the brain of preterm born neonates is sensitive to age-related maturational changes close to TEA. Severe postnatal morbidity correlated with a significant delay in tissue relaxation. Synthetic MRI may provide early prognostic biomarkers for neurodevelopment impairment.

Regional brain volumes, microstructure and neurodevelopment in moderate-late preterm children

OBJECTIVE

To explore whether regional brain volume and white matter microstructure at term-equivalent age (TEA) are associated with development at 2 years of age in children born moderate-late preterm (MLPT).

STUDY DESIGN

A cohort of MLPT infants had brain MRI at approximately TEA (38-44 weeks' postmenstrual age) and had a developmental assessment (Bayley Scales of Infant and Toddler Development and Infant Toddler Social Emotional Assessment) at 2 years' corrected age. Relationships between cortical grey matter and white matter volumes and 2-year developmental outcomes were explored using voxel-based morphometry. Relationships between diffusion tensor measures of white matter microstructure (fractional anisotropy (FA) and axial (AD), radial (RD) and mean (MD) diffusivities) and 2-year developmental outcomes were explored using tract-based spatial statistics.

RESULTS

189 MLPT children had data from at least one MRI modality (volumetric or diffusion) and data for at least one developmental domain. Larger cortical grey and white matter volumes in many brain regions, and higher FA and lower AD, RD and MD in several major white matter regions, were associated with better cognitive and language scores. There was little evidence that cortical grey matter and white matter volumes and white matter microstructure were associated with motor and behavioural outcomes.

CONCLUSIONS

Regional cortical grey matter and white matter volumes and white matter microstructure are associated with cognitive and language development at 2 years of age in MLPT children. Thus, early alterations to brain volumes and microstructure may contribute to some of the developmental deficits described in MLPT children.

Infant FreeSurfer: An automated segmentation and surface extraction pipeline for T1-weighted neuroimaging data of infants 0-2 years

The development of automated tools for brain morphometric analysis in infants has lagged significantly behind analogous tools for adults. This gap reflects the greater challenges in this domain due to: 1) a smaller-scaled region of interest, 2) increased motion corruption, 3) regional changes in geometry due to heterochronous growth, and 4) regional variations in contrast properties corresponding to ongoing myelination and other maturation processes. Nevertheless, there is a great need for automated image-processing tools to quantify differences between infant groups and other individuals, because aberrant cortical morphologic measurements (including volume, thickness, surface area, and curvature) have been associated with neuropsychiatric, neurologic, and developmental disorders in children. In this paper we present an automated segmentation and surface extraction pipeline designed to accommodate clinical MRI studies of infant brains in a population 0-2 year-olds. The algorithm relies on a single channel of T1-weighted MR images to achieve automated segmentation of cortical and subcortical brain areas, producing volumes of subcortical structures and surface models of the cerebral cortex. We evaluated the algorithm both qualitatively and quantitatively using manually labeled datasets, relevant comparator software solutions cited in the literature, and expert evaluations. The computational tools and atlases described in this paper will be distributed to the research community as part of the FreeSurfer image analysis package.

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.

Using Deep Convolutional Neural Networks for Neonatal Brain Image Segmentation

INTRODUCTION

Deep learning neural networks are especially potent at dealing with structured data, such as images and volumes. Both modified LiviaNET and HyperDense-Net performed well at a prior competition segmenting 6-month-old infant magnetic resonance images, but neonatal cerebral tissue type identification is challenging given its uniquely inverted tissue contrasts. The current study aims to evaluate the two architectures to segment neonatal brain tissue types at term equivalent age.

METHODS

Both networks were retrained over 24 pairs of neonatal T1 and T2 data from the Developing Human Connectome Project public data set and validated on another eight pairs against ground truth. We then reported the best-performing model from training and its performance by computing the Dice similarity coefficient (DSC) for each tissue type against eight test subjects.

RESULTS

During the testing phase, among the segmentation approaches tested, the dual-modality HyperDense-Net achieved the best statistically significantly test mean DSC values, obtaining 0.94/0.95/0.92 for the tissue types and took 80 h to train and 10 min to segment, including preprocessing. The single-modality LiviaNET was better at processing T2-weighted images than processing T1-weighted images across all tissue types, achieving mean DSC values of 0.90/0.90/0.88 for gray matter, white matter, and cerebrospinal fluid, respectively, while requiring 30 h to train and 8 min to segment each brain, including preprocessing.

DISCUSSION

Our evaluation demonstrates that both neural networks can segment neonatal brains, achieving previously reported performance. Both networks will be continuously retrained over an increasingly larger repertoire of neonatal brain data and be made available through the Canadian Neonatal Brain Platform to better serve the neonatal brain imaging research community.

Parcellation of the neonatal cortex using Surface-based Melbourne Children's Regional Infant Brain atlases (M-CRIB-S)

Longitudinal studies measuring changes in cortical morphology over time are best facilitated by parcellation schemes compatible across all life stages. The Melbourne Children’s Regional Infant Brain (M-CRIB) and M-CRIB 2.0 atlases provide voxel-based parcellations of the cerebral cortex compatible with the Desikan-Killiany (DK) and the Desikan-Killiany-Tourville (DKT) cortical labelling schemes. This study introduces surface-based versions of the M-CRIB and M-CRIB 2.0 atlases, termed M-CRIB-S(DK) and M-CRIB-S(DKT), with a pipeline for automated parcellation utilizing FreeSurfer and developing Human Connectome Project (dHCP) tools. Using T₂-weighted magnetic resonance images of healthy neonates (n = 58), we created average spherical templates of cortical curvature and sulcal depth. Manually labelled regions in a subset (n = 10) were encoded into the spherical template space to construct M-CRIB-S(DK) and M-CRIB-S(DKT) atlases. Labelling accuracy was assessed using Dice overlap and boundary discrepancy measures with leave-one-out cross-validation. Cross-validated labelling accuracy was high for both atlases (average regional Dice = 0.79–0.83). Worst-case boundary discrepancy instances ranged from 9.96–10.22 mm, which appeared to be driven by variability in anatomy for some cases. The M-CRIB-S atlas data and automatic pipeline allow extraction of neonatal cortical surfaces labelled according to the DK or DKT parcellation schemes.

White matter extension of the Melbourne Children's Regional Infant Brain atlas: M-CRIB-WM

Brain atlases providing standardised identification of neonatal brain regions are key in investigating neurological disorders of early childhood. Our previously developed Melbourne Children's Regional Infant Brain (M-CRIB) and M-CRIB 2.0 neonatal brain atlases provide standardised parcellation of 100 brain regions including cortical, subcortical, and cerebellar regions. The aim of this study was to extend M-CRIB atlas coverage to include 54 white matter (WM) regions. Participants were 10 healthy term-born neonates that were used to create the initial M-CRIB atlas. WM regions were manually segmented based on T₂ images and co-registered diffusion tensor imaging-based, direction-encoded colour maps. Our labelled regions imitate the Johns Hopkins University neonatal atlas, with minor anatomical modifications. All segmentations were reviewed and approved by a paediatric radiologist and a neurosurgery research fellow for anatomical accuracy. The resulting neonatal WM atlas comprises 54 WM regions: 24 paired regions, and six unpaired regions comprising five corpus callosum subdivisions, and one pontine crossing tract. Detailed protocols for manual WM parcellations are provided, and the M-CRIB-WM atlas is presented together with the existing M-CRIB cortical, subcortical, and cerebellar parcellations in 10 individual neonatal MRI data sets. The novel M-CRIB-WM atlas, along with the M-CRIB cortical and subcortical atlases, provide neonatal whole brain MRI coverage in the first multi-subject manually parcellated neonatal atlas compatible with atlases commonly used at older time points. The M-CRIB-WM atlas is publicly available, providing a valuable tool that will help facilitate neuroimaging research into neonatal brain development in both healthy and diseased states.

Maternal and family factors differentiate profiles of psychiatric impairments in very preterm children at age 5-years

BACKGROUND

Very preterm (VPT; <30 weeks gestation) children are a heterogeneous group, yet the co-occurrence of psychiatric and neurodevelopmental impairments remains unclear. Moreover, the clinical and socio-environmental factors that promote resilient developmental outcomes among VPT children are poorly understood.

METHODS

One hundred and twenty five children (85 VPT and 40 full-term) underwent neurodevelopmental evaluation at age 5-years. Parents and teachers completed measures of internalizing, externalizing, attention-deficit/hyperactivity (ADHD), and autism symptoms. Psychiatric and neurodevelopmental measures were analyzed using Latent Profile Analysis. Multinomial regression examined the extent that infant, sociodemographic, and family factors, collected prospectively from birth to follow-up, independently differentiated resilient and impaired children.

RESULTS

Four latent profiles were identified, including a Typically Developing Group which represented 27.1% of the VPT group and 65.0% of the full-term group, an At-Risk Group with mild psychiatric and neurodevelopmental problems (VPT 44.7%, full-term 22.5%), a Psychiatric Group with moderate-to-severe psychiatric ratings (VPT 12.9%, full-term 10.0%), and a school-based Inattentive/Hyperactive Group (VPT 15.3%, full-term 2.5%). Clinical diagnoses were highest among the Psychiatric Group (80%). Factors that differentiated resilient and impaired subgroups of VPT children included prolonged exposure to maternal psychosocial distress (p ≤ .04), current family dysfunction (p ≤ .05), and maternal ADHD symptoms (p ≤ .02), whereas social risk index scores differentiated resilient and impaired full-term children (p < .03).

CONCLUSIONS

Lower levels of maternal distress, family dysfunction, and maternal ADHD symptoms were associated with resilience among VPT children. Maternal distress and family dysfunction are modifiable factors to be targeted as part of psychiatric interventions embedded in the long-term care of VPT children.

Macrocerebellum in Achondroplasia: A Further CNS Manifestation of FGFR3 Mutations?

Achondroplasia is the result of a mutation in the fibroblast growth factor receptor 3 gene (FGFR3). Appearances suggestive of macrocerebellum have not been described in this patient group. We retrospectively reviewed MR imaging studies of the brain in 23 children with achondroplasia. A constellation of imaging findings that are recognized in macrocerebellum was observed, including cerebellar hemisphere enlargement (inferior and superior extension, wrapping around the brainstem); an effaced retro- and infravermian cerebellar subarachnoid CSF space; a shortened midbrain; distortion of the tectal plate; and mass effect on the brainstem. All MR imaging studies exhibited some of these findings. Quantitative analysis confirmed an increased cerebellar volume compared with age- and sex-matched controls. We hypothesized that this may be due to direct effects of the FGFR3 mutation on cerebellar morphogenesis.

Evaluation of cortical segmentation pipelines on clinical neonatal MRI data

Magnetic Resonance Imaging (MRI) can provide 3D morphological information on brain structures. Such information is particularly relevant for carrying out morphometric brain analysis, especially in the newborn and in the case of prematurity. However, 3D neonatal MRI acquired in clinical environments are low-resolution, anisotropic images, making segmentation a challenging task. In this context, preprocessing techniques aim to increase the image resolution. Interpolation techniques were classically used; super-resolution (SR) techniques have recently appeared as an emerging alternative. In this paper, we evaluate the performance of different SR methods against the classical interpolation in the application of neonatal cortex segmentation. Additionally, we assess the robustness of different segmentation methods for each estimation of high resolution MRI input. Results are evaluated both qualitatively and quantitatively with neonatal clinical MRI.

Neurologic Injury and Brain Growth in the Setting of Long-Gap Esophageal Atresia Perioperative Critical Care: A Pilot Study

We previously showed that infants born with long-gap esophageal atresia (LGEA) demonstrate clinically significant brain MRI findings following repair with the Foker process. The current pilot study sought to identify any pre-existing (PRE-Foker process) signs of brain injury and to characterize brain and corpus callosum (CC) growth. Preterm and full-term infants (n = 3/group) underwent non-sedated brain MRI twice: before (PRE-Foker scan) and after (POST-Foker scan) completion of perioperative care. A neuroradiologist reported on qualitative brain findings. The research team quantified intracranial space, brain, cerebrospinal fluid (CSF), and CC volumes. We report novel qualitative brain findings in preterm and full-term infants born with LGEA before undergoing Foker process. Patients had a unique hospital course, as assessed by secondary clinical end-point measures. Despite increased total body weight and absolute intracranial and brain volumes (cm3) between scans, normalized brain volume was decreased in 5/6 patients, implying delayed brain growth. This was accompanied by both an absolute and relative CSF volume increase. In addition to qualitative findings of CC abnormalities in 3/6 infants, normative CC size (% brain volume) was consistently smaller in all infants, suggesting delayed or abnormal CC maturation. A future larger study group is warranted to determine the impact on the neurodevelopmental outcomes of infants born with LGEA.

Role of deep learning in infant brain MRI analysis

Deep learning algorithms and in particular convolutional networks have shown tremendous success in medical image analysis applications, though relatively few methods have been applied to infant MRI data due numerous inherent challenges such as inhomogenous tissue appearance across the image, considerable image intensity variability across the first year of life, and a low signal to noise setting. This paper presents methods addressing these challenges in two selected applications, specifically infant brain tissue segmentation at the isointense stage and presymptomatic disease prediction in neurodevelopmental disorders. Corresponding methods are reviewed and compared, and open issues are identified, namely low data size restrictions, class imbalance problems, and lack of interpretation of the resulting deep learning solutions. We discuss how existing solutions can be adapted to approach these issues as well as how generative models seem to be a particularly strong contender to address them.

Nutrition, Growth, Brain Volume, and Neurodevelopment in Very Preterm Children

OBJECTIVE

To explore the associations between nutrition in the first 28 days after birth with somatic growth from birth to term-equivalent age, brain volumes at term-equivalent age, and neurodevelopment at 24 months of corrected age.

STUDY DESIGN

Prospective cohort study of 149 infants born from 2011 to 2014 at <30 weeks of gestation in a tertiary neonatal nursery in Australia. The following data were collected: average daily energy, protein, fat, and carbohydrate intakes from birth until 28 days, and the difference in weight and head circumference z scores between birth and term-equivalent. Total brain tissue volumes were calculated from brain magnetic resonance imaging at term-equivalent age. Children were assessed at 2 years of corrected age with the Bayley Scales of Infant and Toddler Development-Third Edition. Relationships of nutritional variables with growth, brain volumes, and cognitive, language, and motor development were explored using linear regression.

RESULTS

Complete nutritional data were available for 116 (78%) of the cohort. A 1 g/kg/day higher mean protein intake was associated with a mean increase in weight z score per week of 0.05 (95% CI 0.05, 0.10; P = .04). There was a lack of evidence for associations of any nutritional variables with head circumference growth, with brain volumes at term-equivalent age, or with 2-year neurodevelopment.

CONCLUSIONS

Only higher protein intakes in the first 28 days after birth were associated with better weight growth between birth and term-equivalent age in very preterm infants. Nutrition in the first 28 days was otherwise not substantially related to brain size or to neurodevelopmental outcomes.

TRActs constrained by UnderLying INfant anatomy (TRACULInA): An automated probabilistic tractography tool with anatomical priors for use in the newborn brain

The ongoing myelination of white-matter fiber bundles plays a significant role in brain development. However, reliable and consistent identification of these bundles from infant brain MRIs is often challenging due to inherently low diffusion anisotropy, as well as motion and other artifacts. In this paper we introduce a new tool for automated probabilistic tractography specifically designed for newborn infants. Our tool incorporates prior information about the anatomical neighborhood of white-matter pathways from a training data set. In our experiments, we evaluate this tool on data from both full-term and prematurely born infants and demonstrate that it can reconstruct known white-matter tracts in both groups robustly, even in the presence of differences between the training set and study subjects. Additionally, we evaluate it on a publicly available large data set of healthy term infants (UNC Early Brain Development Program). This paves the way for performing a host of sophisticated analyses in newborns that we have previously implemented for the adult brain, such as pointwise analysis along tracts and longitudinal analysis, in both health and disease.

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.

A Novel Approach for Manual Segmentation of the Amygdala and Hippocampus in Neonate MRI

The gross anatomy of the infant brain at term is fairly similar to that of the adult brain, but structures are immature, and the brain undergoes rapid growth during the first 2 years of life. Neonate magnetic resonance (MR) images have different contrasts compared to adult images, and automated segmentation of brain magnetic resonance imaging (MRI) can thus be considered challenging as less software options are available. Despite this, most anatomical regions are identifiable and thus amenable to manual segmentation. In the current study, we developed a protocol for segmenting the amygdala and hippocampus in T2-weighted neonatal MR images. The participants were 31 healthy infants between 2 and 5 weeks of age. Intra-rater reliability was measured in 12 randomly selected MR images, where 6 MR images were segmented at 1-month intervals between the delineations, and another 6 MR images at 6-month intervals. The protocol was also tested by two independent raters in 20 randomly selected T2-weighted images, and finally with T1 images. Intraclass correlation coefficient (ICC) and Dice similarity coefficient (DSC) for intra-rater, inter-rater, and T1 vs. T2 comparisons were computed. Moreover, manual segmentations were compared to automated segmentations performed by iBEAT toolbox in 10 T2-weighted MR images. The intra-rater reliability was high ICC ≥ 0.91, DSC ≥ 0.89, the inter-rater reliabilities were satisfactory ICC ≥ 0.90, DSC ≥ 0.75 for hippocampus and DSC ≥ 0.52 for amygdalae. Segmentations for T1 vs. T2-weighted images showed high consistency ICC ≥ 0.90, DSC ≥ 0.74. The manual and iBEAT segmentations showed no agreement, DSC ≥ 0.39. In conclusion, there is a clear need to improve and develop the procedures for automated segmentation of infant brain MR images.

Very preterm children at risk for developmental coordination disorder have brain alterations in motor areas

AIM

Brain alterations in very preterm children at risk for developmental coordination disorder were investigated.

METHODS

Infants born very preterm with gestation age <30 weeks or birthweight <1250 g were recruited from Royal Women's Hospital Melbourne from 2001 to 2003. Volumetric imaging was performed at term equivalent age; at seven years, volumetric imaging and diffusion tensor imaging were performed. At seven years, 53 of 162 children without cerebral palsy had scores ≤16th percentile on the Movement Assessment Battery for Children-Second Edition and were considered at risk for developmental coordination disorder.

RESULTS

At term equivalent age, smaller brain volumes were found for total brain tissue, cortical grey matter, cerebellum, caudate accumbens, pallidum and thalamus in children at risk for developmental coordination disorder (p < 0.05); similar patterns were present at seven years. There was no evidence for catch-up brain growth in at-risk children. At seven years, at-risk children displayed altered microstructural organisation in many white matter tracts (p < 0.05).

CONCLUSION

Infants born very preterm at risk for developmental coordination disorder displayed smaller brain volumes at term equivalent age and seven years, and altered white matter microstructure at seven years, particularly in motor areas. There was no catch-up growth from infancy to seven years.