Automatic segmentation of MR brain images with a convolutional neural network

Automatic segmentation in MR brain images is important for quantitative analysis in large-scale studies with images acquired at all ages. This paper presents a method for the automatic segmentation of MR brain images into a number of tissue classes using a convolutional neural network. To ensure that the method obtains accurate segmentation details as well as spatial consistency, the network uses multiple patch sizes and multiple convolution kernel sizes to acquire multi-scale information about each voxel. The method is not dependent on explicit features, but learns to recognise the information that is important for the classification based on training data. The method requires a single anatomical MR image only. The segmentation method is applied to five different data sets: coronal T2-weighted images of preterm infants acquired at 30 weeks postmenstrual age (PMA) and 40 weeks PMA, axial T2- weighted images of preterm infants acquired at 40 weeks PMA, axial T1-weighted images of ageing adults acquired at an average age of 70 years, and T1-weighted images of young adults acquired at an average age of 23 years. The method obtained the following average Dice coefficients over all segmented tissue classes for each data set, respectively: 0.87, 0.82, 0.84, 0.86 and 0.91. The results demonstrate that the method obtains accurate segmentations in all five sets, and hence demonstrates its robustness to differences in age and acquisition protocol

Early Brain Activity Relates to Subsequent Brain Growth in Premature Infants

Recent experimental studies have shown that early brain activity is crucial for neuronal survival and the development of brain networks; however, it has been challenging to assess its role in the developing human brain. We employed serial quantitative magnetic resonance imaging to measure the rate of growth in circumscribed brain tissues from preterm to term age, and compared it with measures of electroencephalographic (EEG) activity during the first postnatal days by 2 different methods. EEG metrics of functional activity were computed: EEG signal peak-to-peak amplitude and the occurrence of developmentally important spontaneous activity transients (SATs). We found that an increased brain activity in the first postnatal days correlates with a faster growth of brain structures during subsequent months until term age. Total brain volume, and in particular subcortical gray matter volume, grew faster in babies with less cortical electrical quiescence and with more SAT events. The present findings are compatible with the idea that (1) early cortical network activity is important for brain growth, and that (2) objective measures may be devised to follow early human brain activity in a biologically reasoned way in future research as well as during intensive care treatmen

Origin and dynamics of oligodendrocytes in the developing brain: Implications for perinatal white matter injury.

Infants born prematurely are at high risk to develop white matter injury (WMI), due to exposure to hypoxic and/or inflammatory insults. Such perinatal insults negatively impact the maturation of oligodendrocytes (OLs), thereby causing deficits in myelination. To elucidate the precise pathophysiology underlying perinatal WMI, it is essential to fully understand the cellular mechanisms contributing to healthy/normal white matter development. OLs are responsible for myelination of axons. During brain development, OLs are generally derived from neuroepithelial zones, where neural stem cells committed to the OL lineage differentiate into OL precursor cells (OPCs). OPCs, in turn, develop into premyelinating OLs and finally mature into myelinating OLs. Recent studies revealed that OPCs develop in multiple waves and form potentially heterogeneous populations. Furthermore, it has been shown that myelination is a dynamic and plastic process with an excess of OPCs being generated and then abolished if not integrated into neural circuits. Myelination patterns between rodents and humans show high spatial and temporal similarity. Therefore, experimental studies on OL biology may provide novel insights into the pathophysiology of WMI in the preterm infant and offers new perspectives on potential treatments for these patients.This work was funded by the Wilhelmina Children's Hospital Research Fund and the Brain Foundation Netherlands

Automated cot-side tracking of functional brain age in preterm infants

Objective A major challenge in the care of preterm infants is the early identification of compromised neurological development. While several measures are routinely used to track anatomical growth, there is a striking lack of reliable and objective tools for tracking maturation of early brain function; a cornerstone of lifelong neurological health. We present a cot-side method for measuring the functional maturity of the newborn brain based on routinely available neurological monitoring with electroencephalography (EEG). Methods We used a dataset of 177 EEG recordings from 65 preterm infants to train a multivariable prediction of functional brain age (FBA) from EEG. The FBA was validated on an independent set of 99 EEG recordings from 42 preterm infants. The difference between FBA and postmenstrual age (PMA) was evaluated as a predictor for neurodevelopmental outcome. Results The FBA correlated strongly with the PMA of an infant, with a median prediction error of less than 1 week. Moreover, individual babies follow well-defined individual trajectories. The accuracy of the FBA applied to the validation set was statistically equivalent to the training set accuracy. In a subgroup of infants with repeated EEG recordings, a persistently negative predicted age difference was associated with poor neurodevelopmental outcome. Interpretation The FBA enables the tracking of functional neurodevelopment in preterm infants. This establishes proof of principle for growth charts for brain function, a new tool to assist clinical management and identify infants who will benefit most from early intervention.Peer reviewe

Neuromonitoring, neuroimaging, and neurodevelopmental follow-up practices in neonatal congenital heart disease: a European survey

BACKGROUND Brain injury and neurodevelopmental impairment remain a concern in children with complex congenital heart disease (CHD). A practice guideline on neuromonitoring, neuroimaging, and neurodevelopmental follow-up in CHD patients undergoing cardiopulmonary bypass surgery is lacking. The aim of this survey was to systematically evaluate the current practice in centers across Europe. METHODS An online-based structured survey was sent to pediatric cardiac surgical centers across Europe between April 2019 and June 2020. Results were summarized by descriptive statistics. RESULTS Valid responses were received by 25 European centers, of which 23 completed the questionnaire to the last page. Near-infrared spectroscopy was the most commonly used neuromonitoring modality used in 64, 80, and 72% preoperatively, intraoperatively, and postoperatively, respectively. Neuroimaging was most commonly performed by means of cranial ultrasound in 96 and 84% preoperatively and postoperatively, respectively. Magnetic resonance imaging was obtained in 72 and 44% preoperatively and postoperatively, respectively, but was predominantly reserved for clinically symptomatic patients (preoperatively 67%, postoperatively 64%). Neurodevelopmental follow-up was implemented in 40% of centers and planned in 24%. CONCLUSIONS Heterogeneity in perioperative neuromonitoring and neuroimaging practice in CHD in centers across Europe is large. The need for neurodevelopmental follow-up has been recognized. A clear practice guideline is urgently needed. IMPACT There is large heterogeneity in neuromonitoring, neuroimaging, and neurodevelopmental follow-up practices among European centers caring for neonates with complex congenital heart disease. This study provides a systematic evaluation of the current neuromonitoring, neuroimaging, and neurodevelopmental follow-up practice in Europe. The results of this survey may serve as the basis for developing a clear practice guideline that could help to early detect and prevent neurological and neurodevelopmental sequelae in neonates with complex congenital heart disease

Early human brain development:insights into macroscale connectome wiring

BACKGROUND: Early brain development is closely dictated by distinct neurobiological principles. Here, we aimed to map early trajectories of structural brain wiring in the neonatal brain. METHODS: We investigated structural connectome development in 44 newborns, including 23 preterm infants and 21 full-term neonates scanned between 29 and 45 postmenstrual weeks. Diffusion-weighted imaging data were combined with cortical segmentations derived from T2 data to construct neonatal connectome maps. RESULTS: Projection fibers interconnecting primary cortices and deep gray matter structures were noted to mature faster than connections between higher-order association cortices (fractional anisotropy (FA) F = 58.9, p < 0.001, radial diffusivity (RD) F = 28.8, p < 0.001). Neonatal FA-values resembled adult FA-values more than RD, while RD approximated the adult brain faster (F = 358.4, p < 0.001). Maturational trajectories of RD in neonatal white matter pathways revealed substantial overlap with what is known about the sequence of subcortical white matter myelination from histopathological mappings as recorded by early neuroanatomists (mean RD 68 regions r = 0.45, p = 0.008). CONCLUSION: Employing postnatal neuroimaging we reveal that early maturational trajectories of white matter pathways display discriminative developmental features of the neonatal brain network. These findings provide valuable insight into the early stages of structural connectome development

Early motor outcomes in infants with critical congenital heart disease are related to neonatal brain development and brain injury

Aim To assess the relationship between neonatal brain development and injury with early motor outcomes in infants with critical congenital heart disease (CCHD). Method Neonatal brain magnetic resonance imaging was performed after open-heart surgery with cardiopulmonary bypass. Cortical grey matter (CGM), unmyelinated white matter, and cerebellar volumes, as well as white matter motor tract fractional anisotropy and mean diffusivity were assessed. White matter injury (WMI) and arterial ischaemic stroke (AIS) with corticospinal tract (CST) involvement were scored. Associations with motor outcomes at 3, 9, and 18 months were corrected for repeated cardiac surgery. Results Fifty-one infants (31 males, 20 females) were included prospectively. Median age at neonatal surgery and postoperative brain magnetic resonance imaging was 7 days (interquartile range [IQR] 5-11d) and 15 days (IQR 12-21d) respectively. Smaller CGM and cerebellar volumes were associated with lower fine motor scores at 9 months (CGM regression coefficient=0.51, 95% confidence interval [CI]=0.15-0.86; cerebellum regression coefficient=3.08, 95% CI=1.07-5.09) and 18 months (cerebellum regression coefficient=2.08, 95% CI=0.47-5.12). The fractional anisotropy and mean diffusivity of white matter motor tracts were not related with motor scores. WMI was related to lower gross motor scores at 9 months (mean difference -0.8SD, 95% CI=-1.5 to -0.2). AIS with CST involvement increased the risk of gross motor problems and muscle tone abnormalities. Cerebral palsy (n=3) was preceded by severe ischaemic brain injury. Interpretation Neonatal brain development and injury are associated with fewer favourable early motor outcomes in infants with CCHD