The Cerebrospinal Fluid Inflammatory Response to Preterm Birth.

Background: Preterm birth is the leading risk factor for perinatal white matter injury, which can lead to motor and neuropsychiatric impairment across the life course. There is an unmet clinical need for therapeutics. White matter injury is associated with an altered inflammatory response in the brain, primarily led by microglia, and subsequent hypomyelination. However, microglia can release both damaging and trophic factors in response to injury, and a comprehensive assessment of these factors in the preterm central nervous system (CNS) has not been carried out. Method: A custom antibody array was used to assess relative levels of 50 inflammation- and myelination-associated proteins in the cerebrospinal fluid (CSF) of preterm infants in comparison to term controls. Results: Fifteen proteins differed between the groups: BDNF, BTC, C5a, FasL, Follistatin, IL-1ß, IL-2, IL-4, IL-9, IL-17A, MIP-1α, MMP8, SPP1, TGFß, and TNFß (p < 0.05). To investigate the temporal regulation of these proteins after injury, we mined a gene expression dataset of microglia isolated from a mouse model of developmental white matter injury. Microglia in the experimental model showed dynamic temporal expression of genes encoding these proteins, with an initial and sustained pro-inflammatory response followed by a delayed anti-inflammatory response, and a continuous expression of genes predicted to inhibit healthy myelination. Conclusion: Preterm CSF shows a distinct neuroinflammatory profile compared to term controls, suggestive of a complex neural environment with concurrent damaging and reparative signals. We propose that limitation of pro-inflammatory responses, which occur early after perinatal insult, may prevent expression of myelination-suppressive genes and support healthy white matter development.

Diffusion MRI parameters of corpus callosum and corticospinal tract in neonates: Comparison between region-of-interest and whole tract averaged measurements.

PURPOSE: Measures of white matter (WM) microstructure inferred from diffusion magnetic resonance imaging (dMRI) are useful for studying brain development. There is uncertainty about agreement between FA and MD values obtained from region-of-interest (ROI) versus whole tract approaches. We investigated agreement between dMRI measures using ROI and Probabilistic Neighbourhood Tractography (PNT) in genu of corpus callosum (gCC) and corticospinal tracts (CST). MATERIALS AND METHODS: 81 neonates underwent 64 direction DTI at term equivalent age. FA and MD values were extracted from a 8 mm3 ROI placed within the gCC, right and left posterior limbs of internal capsule. PNT was used to segment gCC and CSTs to calculate whole tract-averaged FA and MD. Agreement between values obtained by each method was compared using Bland-Altman statistics and Pearson's correlation. RESULTS: Across the 3 tracts the mean difference in FA measured by PNT and ROI ranged between 0.13 and 0.17, and the 95% limits of agreement did not include the possibility of no difference. For MD, the mean difference in values obtained from PNT and ROI ranged between 0.101 and 0.184 mm2/s × 10-3 mm2/s: the mean difference in gCC was 0.101 × 10-3 mm2/s with 95% limits of agreement that included the possibility of no difference, but there was significant disagreement in MD values measured in the CSTs. CONCLUSION: Agreement between dMRI measures of neonatal WM microstructure calculated from ROI and whole tract averaged methods is weak. ROI approaches may not provide sufficient representation of tract microstructure at the level of neural systems in newborns.

A latent measure explains substantial variance in white matter microstructure across the newborn human brain.

A latent measure of white matter microstructure (g WM) provides a neural basis for information processing speed and intelligence in adults, but the temporal emergence of g WM during human development is unknown. We provide evidence that substantial variance in white matter microstructure is shared across a range of major tracts in the newborn brain. Based on diffusion MRI scans from 145 neonates [gestational age (GA) at birth range 23+2-41+5 weeks], the microstructural properties of eight major white matter tracts were calculated using probabilistic neighborhood tractography. Principal component analyses (PCAs) were carried out on the correlations between the eight tracts, separately for four tract-averaged water diffusion parameters: fractional anisotropy, and mean, radial and axial diffusivities. For all four parameters, PCAs revealed a single latent variable that explained around half of the variance across all eight tracts, and all tracts showed positive loadings. We considered the impact of early environment on general microstructural properties, by comparing term-born infants with preterm infants at term equivalent age. We found significant associations between GA at birth and the latent measure for each water diffusion measure; this effect was most apparent in projection and commissural fibers. These data show that a latent measure of white matter microstructure is present in very early life, well before myelination is widespread. Early exposure to extra-uterine life is associated with altered general properties of white matter microstructure, which could explain the high prevalence of cognitive impairment experienced by children born preterm.

SEGMA: An Automatic SEGMentation Approach for Human Brain MRI Using Sliding Window and Random Forests.

Quantitative volumes from brain magnetic resonance imaging (MRI) acquired across the life course may be useful for investigating long term effects of risk and resilience factors for brain development and healthy aging, and for understanding early life determinants of adult brain structure. Therefore, there is an increasing need for automated segmentation tools that can be applied to images acquired at different life stages. We developed an automatic segmentation method for human brain MRI, where a sliding window approach and a multi-class random forest classifier were applied to high-dimensional feature vectors for accurate segmentation. The method performed well on brain MRI data acquired from 179 individuals, analyzed in three age groups: newborns (38-42 weeks gestational age), children and adolescents (4-17 years) and adults (35-71 years). As the method can learn from partially labeled datasets, it can be used to segment large-scale datasets efficiently. It could also be applied to different populations and imaging modalities across the life course.

Complement C5a is present in CSF of human newborns and is elevated in association with preterm birth.

Neuroinflammation contributes to developmental brain injury associated with preterm birth, but the mediators that drive it are incompletely understood. Previous studies have shown that complement C5a is present and injurious in the brains of foetal mice exposed to preterm labour. Here, we demonstrate that C5a is present in the cerebrospinal fluid of newborn human infants and that levels are elevated in those born preterm. The difference is not explained by systemic infection. Complement activation in the neonatal brain and its role as a potential therapeutic target in preterm brain injury warrant further study. Activation in the neonatal brain and its role as a potential therapeutic target for preterm brain injury warrants further study.

Association between preterm brain injury and exposure to chorioamnionitis during fetal life.

Preterm infants are susceptible to inflammation-induced white matter injury but the exposures that lead to this are uncertain. Histologic chorioamnionitis (HCA) reflects intrauterine inflammation, can trigger a fetal inflammatory response, and is closely associated with premature birth. In a cohort of 90 preterm infants with detailed placental histology and neonatal brain magnetic resonance imaging (MRI) data at term equivalent age, we used Tract-based Spatial Statistics (TBSS) to perform voxel-wise statistical comparison of fractional anisotropy (FA) data and computational morphometry analysis to compute the volumes of whole brain, tissue compartments and cerebrospinal fluid, to test the hypothesis that HCA is an independent antenatal risk factor for preterm brain injury. Twenty-six (29%) infants had HCA and this was associated with decreased FA in the genu, cingulum cingulate gyri, centrum semiovale, inferior longitudinal fasciculi, limbs of the internal capsule, external capsule and cerebellum (p < 0.05, corrected), independent of degree of prematurity, bronchopulmonary dysplasia and postnatal sepsis. This suggests that diffuse white matter injury begins in utero for a significant proportion of preterm infants, which focuses attention on the development of methods for detecting fetuses and placentas at risk as a means of reducing preterm brain injury.

Parcellation of the Healthy Neonatal Brain into 107 Regions Using Atlas Propagation through Intermediate Time Points in Childhood.

Neuroimage analysis pipelines rely on parcellated atlases generated from healthy individuals to provide anatomic context to structural and diffusion MRI data. Atlases constructed using adult data introduce bias into studies of early brain development. We aimed to create a neonatal brain atlas of healthy subjects that can be applied to multi-modal MRI data. Structural and diffusion 3T MRI scans were acquired soon after birth from 33 typically developing neonates born at term (mean postmenstrual age at birth 39(+5) weeks, range 37(+2)-41(+6)). An adult brain atlas (SRI24/TZO) was propagated to the neonatal data using temporal registration via childhood templates with dense temporal samples (NIH Pediatric Database), with the final atlas (Edinburgh Neonatal Atlas, ENA33) constructed using the Symmetric Group Normalization (SyGN) method. After this step, the computed final transformations were applied to T2-weighted data, and fractional anisotropy, mean diffusivity, and tissue segmentations to provide a multi-modal atlas with 107 anatomical regions; a symmetric version was also created to facilitate studies of laterality. Volumes of each region of interest were measured to provide reference data from normal subjects. Because this atlas is generated from step-wise propagation of adult labels through intermediate time points in childhood, it may serve as a useful starting point for modeling brain growth during development.

Accurate Learning with Few Atlases (ALFA): an algorithm for MRI neonatal brain extraction and comparison with 11 publicly available methods.

Accurate whole-brain segmentation, or brain extraction, of magnetic resonance imaging (MRI) is a critical first step in most neuroimage analysis pipelines. The majority of brain extraction algorithms have been developed and evaluated for adult data and their validity for neonatal brain extraction, which presents age-specific challenges for this task, has not been established. We developed a novel method for brain extraction of multi-modal neonatal brain MR images, named ALFA (Accurate Learning with Few Atlases). The method uses a new sparsity-based atlas selection strategy that requires a very limited number of atlases 'uniformly' distributed in the low-dimensional data space, combined with a machine learning based label fusion technique. The performance of the method for brain extraction from multi-modal data of 50 newborns is evaluated and compared with results obtained using eleven publicly available brain extraction methods. ALFA outperformed the eleven compared methods providing robust and accurate brain extraction results across different modalities. As ALFA can learn from partially labelled datasets, it can be used to segment large-scale datasets efficiently. ALFA could also be applied to other imaging modalities and other stages across the life course.

Preterm birth is associated with atypical social orienting in infancy detected using eye tracking.

BACKGROUND: Preterm birth is closely associated with neurocognitive impairment in childhood including increased risk for social difficulties. Eye tracking objectively assesses eye-gaze behaviour in response to visual stimuli, which permits inference about underlying cognitive processes. We tested the hypothesis that social orienting in infancy is altered by preterm birth. METHODS: Fifty preterm infants with mean (range) gestational age (GA) at birth of 29(+1) (23(+2) -33(+0) ) weeks and 50 term infants with mean (range) GA at birth 40(+2) (37(+0) -42(+3) ) weeks underwent eye tracking at median age of 7 months. Infants were presented with three categories of social stimuli of increasing complexity. Time to first fixate (TFF) and looking time (LT) on areas of interest (AoIs) were recorded using remote eye tracking. RESULTS: Preterm infants consistently fixated for a shorter time on social content than term infants across all three tasks: face-scanning (fixation to eyes minus mouth 0.61s vs. 1.47s, p = .013); face pop-out task (fixation to face 0.8s vs. 1.34s, p = .023); and social preferential looking (1.16s vs. 1.5s p = .02). Time given to AoIs containing social content as a proportion of LT at the whole stimulus was lower in preterm infants across all three tasks. These results were not explained by differences in overall looking time between the groups. CONCLUSIONS: Eye tracking provides early evidence of atypical cognition after preterm birth, and may be a useful tool for stratifying infants at risk of impairment for early interventions designed to improve outcome.

Tract shape modeling detects changes associated with preterm birth and neuroprotective treatment effects.

Preterm birth is associated with altered connectivity of neural circuits. We developed a tract segmentation method that provides measures of tract shape and integrity (probabilistic neighborhood tractography, PNT) from diffusion MRI (dMRI) data to test the hypotheses: 1) preterm birth is associated with alterations in tract topology (R), and tract-averaged mean diffusivity (〈D〉) and fractional anisotropy (FA); 2) neural systems are separable based on tract-averaged dMRI parameters; and 3) PNT can detect neuroprotective treatment effects. dMRI data were collected from 87 preterm infants (mean gestational age 29(+1) weeks, range 23(+2) -34(+6)) at term equivalent age and 24 controls (mean gestational age 39(+6) weeks). PNT was used to segment eight major fasciculi, characterize topology, and extract tract-averaged〈D〉and FA. Tract topology was altered by preterm birth in all tracts except the splenium (p < 0.05, false discovery rate [FDR] corrected). After adjustment for age at scan, tract-averaged〈D〉was increased in the genu and splenium, right corticospinal tract (CST) and the left and right inferior longitudinal fasciculi (ILF) in preterm infants compared with controls (p < 0.05, FDR), while tract-averaged FA was decreased in the splenium and left ILF (p < 0.05, FDR). Specific fasciculi were separable based on tract-averaged〈D〉and FA values. There was a modest decrease in tract-averaged〈D〉in the splenium of preterm infants who had been exposed to antenatal MgSO4 for neuroprotection (p = 0.002). Tract topology is a biomarker of preterm brain injury. The data provide proof of concept that tract-averaged dMRI parameters have utility for evaluating tissue effects of perinatal neuroprotective strategies.