Ventricular shape and relative position abnormalities in preterm neonates

abstract: Recent neuroimaging findings have highlighted the impact of premature birth on subcortical development and morphological changes in the deep grey nuclei and ventricular system. To help characterize subcortical microstructural changes in preterm neonates, we recently implemented a multivariate tensor-based method (mTBM). This method allows to precisely measure local surface deformation of brain structures in infants. Here, we investigated ventricular abnormalities and their spatial relationships with surrounding subcortical structures in preterm neonates. We performed regional group comparisons on the surface morphometry and relative position of the lateral ventricles between 19 full-term and 17 preterm born neonates at term-equivalent age. Furthermore, a relative pose analysis was used to detect individual differences in translation, rotation, and scale of a given brain structure with respect to an average. Our mTBM results revealed broad areas of alterations on the frontal horn and body of the left ventricle, and narrower areas of differences on the temporal horn of the right ventricle. A significant shift in the rotation of the left ventricle was also found in preterm neonates. Furthermore, we located significant correlations between morphology and pose parameters of the lateral ventricles and that of the putamen and thalamus. These results show that regional abnormalities on the surface and pose of the ventricles are also associated with alterations on the putamen and thalamus. The complementarity of the information provided by the surface and pose analysis may help to identify abnormal white and grey matter growth, hinting toward a pattern of neural and cellular dysmaturation.The final version of this article, as published in NeuroImage: Clinical, can be viewed online at: http://www.sciencedirect.com/science/article/pii/S221315821730130

Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

Motion robust acquisition and reconstruction of quantitative T2* maps in the developing brain

The goal of the research presented in this thesis was to develop methods for quantitative T2* mapping of the developing brain. Brain maturation in the early period of life involves complex structural and physiological changes caused by synaptogenesis, myelination and growth of cells. Molecular structures and biological processes give rise to varying levels of T2* relaxation time, which is an inherent contrast mechanism in magnetic resonance imaging. The knowledge of T2* relaxation times in the brain can thus help with evaluation of pathology by establishing its normative values in the key areas of the brain. T2* relaxation values are a valuable biomarker for myelin microstructure and iron concentration, as well as an important guide towards achievement of optimal fMRI contrast. However, fetal MR imaging is a significant step up from neonatal or adult MR imaging due to the complexity of the acquisition and reconstruction techniques that are required to provide high quality artifact-free images in the presence of maternal respiration and unpredictable fetal motion. The first contribution of this thesis, described in Chapter 4, presents a novel acquisition method for measurement of fetal brain T2* values. At the time of publication, this was the first study of fetal brain T2* values. Single shot multi-echo gradient echo EPI was proposed as a rapid method for measuring fetal T2* values by effectively freezing intra-slice motion. The study concluded that fetal T2* values are higher than those previously reported for pre-term neonates and decline with a consistent trend across gestational age. The data also suggested that longer than usual echo times or direct T2* measurement should be considered when performing fetal fMRI in order to reach optimal BOLD sensitivity. For the second contribution, described in Chapter 5, measurements were extended to a higher field strength of 3T and reported, for the first time, both for fetal and neonatal subjects at this field strength. The technical contribution of this work is a fully automatic segmentation framework that propagates brain tissue labels onto the acquired T2* maps without the need for manual intervention. The third contribution, described in Chapter 6, proposed a new method for performing 3D fetal brain reconstruction where the available data is sparse and is therefore limited in the use of current state of the art techniques for 3D brain reconstruction in the presence of motion. To enable a high resolution reconstruction, a generative adversarial network was trained to perform image to image translation between T2 weighted and T2* weighted data. Translated images could then be served as a prior for slice alignment and super resolution reconstruction of 3D brain image.Open Acces

Neuropathology and cognitive dysfunction after early hypoglycaemia

Hypoglycaemia is the most common metabolic problem in neonatal medicine, occurring during the first days of life and usually resolving within the same time frame. However, some neonates and infants experience severe and recurrent episodes of hypoglycaemia, the most common aetiologies being congenital hyperinsulinism (CHI) and ketotic hypoglycaemia (KH). Children with CHI are at risk of lasting brain injury, while children with KH are considered to be protected from adverse sequelae owing to the presence of ketone bodies during hypoglycaemia. This thesis investigated the neuropsychological and neuroimaging profiles of these two patient groups in neurologically normal school-aged children. Thirty-one patients with CHI and twenty-one patients with KH participated in the study alongside a cohort of healthy controls. A comprehensive battery of neuropsychological tests revealed specific impairments in attention and motor skills in both patient groups, with additional impairments observed in children with CHI. Automated and manual measurements of subcortical volumes, as well as whole brain analyses (voxel based morphometry and tract based spatial statistics) were conducted. Compared to controls, patients with CHI have reduced volume of subcortical structures, as well as extensive white matter volume loss (accompanied by decreased intracranial volume) and reduced white matter integrity across the entire brain. Patients with KH did not significantly differ from controls on any brain measures, but the only significant difference between patient groups was in thalamic and intracranial volumes. Integrity of subcortical structures and white matter was found to be predictive of scores in memory, motor skills and attention. This study is the first to show the extent of brain abnormality as a result of CHI in neurologically normal children. Furthermore, the finding that both patient groups share a similar cognitive profile refutes the notion that children with KH are protected from adverse sequelae. The implications of these findings are discussed

Retrieval of germinal zone neural stem cells from the cerebrospinal fluid of premature infants with intraventricular hemorrhage

Intraventricular hemorrhage is a common cause of morbidity and mortality in premature infants. The rupture of the germinal zone into the ventricles entails loss of neural stem cells and disturbs the normal cytoarchitecture of the region, compromising late neurogliogenesis. Here we demonstrate that neural stem cells can be easily and robustly isolated from the hemorrhagic cerebrospinal fluid obtained during therapeutic neuroendoscopic lavage in preterm infants with severe intraventricular hemorrhage. Our analyses demonstrate that these neural stem cells, although similar to human fetal cell lines, display distinctive hallmarks related to their regional and developmental origin in the germinal zone of the ventral forebrain, the ganglionic eminences that give rise to interneurons and oligodendrocytes. These cells can be expanded, cryopreserved, and differentiated in vitro and in vivo in the brain of nude mice and show no sign of tumoral transformation 6 months after transplantation. This novel class of neural stem cells poses no ethical concerns, as the fluid is usually discarded, and could be useful for the development of an autologous therapy for preterm infants, aiming to restore late neurogliogenesis and attenuate neurocognitive deficits. Furthermore, these cells represent a valuable tool for the study of the final stages of human brain development and germinal zone biology

A COMPUTATIONAL FRAMEWORK FOR NEONATAL BRAIN MRI STRUCTURE SEGMENTATION AND CLASSIFICATION

Deep Learning is increasingly being used in both supervised and unsupervised learning to derive complex patterns from data. However, the successful implementation of deep learning using medical imaging requires careful consideration for the quality and availability of data. Infants diagnosed with CHD are at a higher risk for neurodevelopmental impairment. Many of these deficits may be attenuated by early detection and intervention. However, we currently lack effective diagnostic tools for the reliable detection of these disorders at the neonatal period. We believe that the structural correlates of the cognitive deficits associated with developmental abnormalities can be measured within the first few months of life. Based on this assumption, we hypothesize that we can use an atlas registration based structural segmentation pipeline to sufficiently reduce the search space of neonatal structural brain MRI to viably implement convolutional neural networks for dysplasia classification. Secondly, we hypothesize that convolutional neural networks can successfully identify morphological biomarkers capable of detecting structurally abnormal brain substructures. In this study, we develop a computational framework for the automated classification of dysplastic substructures from neonatal MRI. We validate our implementation on a dataset of neonates born with CHD, as this is a vulnerable population for structural dysmaturation. We chose the cerebellum as the initial test substructure because of its relatively simple structure and known vulnerability to structural dysplasia in infants born with CHD. We then apply the same method to the hippocampus, a more challenging substructure due to its complex morphological properties. We attempt to overcome the limited availability of clinical data in neonatal populations by first extracting each brain substructure of interest and individually registering them into a standard space. This greatly reduces the search space required to learn the subtle abnormalities associated with a given pathology, making it feasible to implement a 3-D CNN as the classification algorithm. We achieved excellent classification accuracy in detecting dysplastic cerebelli, and demonstrate a viable computational framework for search space reduction using limited clinical datasets. All methods developed in this work are designed to be extensible, reproducible, and generalizable diagnostic tools for future neuroimaging problems

Pharmacokinetics of melatonin as a neuroprotectant In preterm infants

Background and purpose: Advances in perinatal care have increased survival rates of infants but long-term neurodisability and social consequences have remained unchanged over the last decade. Preterm infants are deprived of the normal intrauterine exposure to maternal melatonin and experimental studies suggest that melatonin has a neuroprotective effect on cerebral white matter injury. However, pharmacokinetic data on melatonin in preterm infants are lacking, which hinders potential therapeutic trials. The aims of this study were to determine the pharmacokinetics of melatonin in the relevant preterm population, assess the tolerability of melatonin and determine a dose regime that would allow replication of adult melatonin levels. Methods: In a multi-centre, single dose escalation/de-escalation, open label study in preterm infants less than 31 weeks gestation, melatonin was administered to eighteen infants in doses ranging from 0.04-0.6 micrograms/kilograms, over 0.5-6 hours. Pharmacokinetic profiles were analysed individually and by population methods. Results: Baseline melatonin was largely undetectable. At the highest and lowest doses half-life could not be calculated due to blood concentrations not reaching a consistent steady state, but infants receiving melatonin at 0.1 micrograms/kilogram/hour for 2 hours showed a median half-life of 15.82 hours and median maximum plasma concentration of 203.3 picograms/millilitre. Population pharmacokinetic analysis showed that clearance was 0.045 litre/hour, volume of distribution 1.098 litres and elimination half-life 16.91 hours with gender (p=0.047) and race (p<0.0001) as significant covariates. Melatonin infusion appeared to be well tolerated in preterm infants. Conclusions: The pharmacokinetic profile of melatonin in preterm infants differs from that of adults. Slow clearance makes replication of adult and thus fetal concentrations of melatonin problematic. Further studies are needed to confirm these findings.Open acces

Neuroplasticity in Young Age: Computer-Based Early Neurodevelopment Classifier

Neurodevelopmental syndromes, a continuously growing issue, are impairments in the growth and development of the brain and CNS which are pronounced in a variety of emotional, cognitive, motor and social skills. Early assessment and detection of typical, clinically correlated early signs of developmental abnormalities is crucial for early and effective intervention, supporting initiation of early treatment and minimizing neurological and functional deficits. Successful early interventions would then direct to early time windows of higher neural plasticity. Various syndromes are reflected in early vocal and motor characteristics, making them suitable indicators of an infant’s neural development. Performance of the computerized classifiers we developed shows approximately 90% accuracy on a database of diagnosed babies. The results demonstrate the potential of vocal and motor analysis for computer-assisted early detection of neurodevelopmental insults

Early brain activity : Translations between bedside and laboratory

Neural activity is both a driver of brain development and a readout of developmental processes. Changes in neuronal activity are therefore both the cause and consequence of neurodevelopmental compromises. Here, we review the assessment of neuronal activities in both preclinical models and clinical situations. We focus on issues that require urgent translational research, the challenges and bottlenecks preventing translation of biomedical research into new clinical diagnostics or treatments, and possibilities to overcome these barriers. The key questions are (i) what can be measured in clinical settings versus animal experiments, (ii) how do measurements relate to particular stages of development, and (iii) how can we balance practical and ethical realities with methodological compromises in measurements and treatments.Peer reviewe

A Single Neonatal Injury Induces Life-Long Adaptations In Stress And Pain Responsiveness

Approximately 1 in 6 infants are born prematurely each year. Typically, these infants spend 25 days in the Neonatal Intensive Care Unit (NICU) where they experience 10-18 painful and inflammatory procedures each day. Remarkably, pre-emptive analgesics and/or anesthesia are administered less than 30% of the time. Unalleviated pain during the perinatal period is associated with permanent decreases in pain sensitivity, blunted cortisol responses and high rates of neuropsychiatric disorders. To date, the mechanism(s) by which these long-term changes in stress and pain behavior occur, and whether such alterations can be prevented by appropriate analgesia at the time of injury, remains unclear. We have previously reported in rats that inflammation experienced on the day of birth permanently upregulates central opioid tone, resulting in a significant reduction in adult pain sensitivity. However, the impact on early life pain on anxiety- and stress-related behavior and HPA axis regulation is not known. Therefore the goal of this dissertation was to determine the long-term impact of a single neonatal inflammatory pain experience on adult anxiety- and stress-related responses. Neuroanatomical changes in stress-associated neurocircuits were also examined. As the endogenous pain control system and HPA axis are in a state of exaggerated developmental plasticity early in postnatal life, and these systems work in concert to respond to noxious or aversive stimuli, this dissertation research aimed to answer the following questions: (1) Does neonatal injury produce deficits in adult stress-related behavior and alter stress-related neuroanatomy through an opioid-dependent mechanism? (2) Does neonatal injury alter receptor systems regulating the activation and termination of the stress response in adulthood? (3) Are stress- and pain-related neurotransmitters altered within the first week following early life pain? (4) Is early activation of the pain system necessary for the long-term changes in anxiety- and stress-related behavior? Together these studies demonstrate the degree, severity and preventability of the long-term deficits in stress responding associated with a single painful experience early in life. The goal of this research is to promote change in the treatment of infant pain in the NICU to reduce long-term sensory and mental health complications associated with prematurity