Mapping connections in the neonatal brain with magnetic resonance imaging

The neonatal brain undergoes rapid development after birth, including the growth and maturation of the white matter fibre bundles that connect brain regions. Diffusion MRI (dMRI) is a unique tool for mapping these bundles in vivo, providing insight into factors that impact the development of white matter and how its maturation influences other developmental processes. However, most studies of neonatal white matter do not use specialised analysis tools, instead using tools that have been developed for the adult brain. However, the neonatal brain is not simply a small adult brain, as differences in geometry and tissue decomposition cause considerable differences in dMRI contrast. In this thesis, methods are developed to map white matter connections during this early stage of neurodevelopment. First, two contrasting approaches are explored: ROI-constrained protocols for mapping individual tracts, and the generation of whole-brain connectomes that capture the developing brain's full connectivity profile. The impact of the gyral bias, a methodological confound of tractography, is quantified and compared with the equivalent measurements for adult data. These connectomes form the basis for a novel, data-driven framework, in which they are decomposed into white matter bundles and their corresponding grey matter terminations. Independent component analysis and non-negative matrix factorisation are compared for the decomposition, and are evaluated against in-silico simulations. Data-driven components of dMRI tractography data are compared with manual tractography, and networks obtained from resting-state functional MRI. The framework is further developed to provide corresponding components between groups and individuals. The data-driven components are used to generate cortical parcellations, which are stable across subjects. Finally, some future applications are outlined that extend the use of these methods beyond the context of neonatal imaging, in order to bridge the gap between functional and structural analysis paradigms, and to chart the development of white matter throughout the lifespan and across species

Brain structural connectivity and neurodevelopment in post-Fontan adolescents

Congenital heart disease (CHD) is the most common congenital anomaly, with single ventricle (SV) defects accounting for nearly 10% of all CHD. SV defects tend to be the most severe forms of CHD: all patients born with SV require multiple open heart surgeries, often beginning in the neonatal period, ultimately leading to the Fontan procedure. Due to improvements in surgical procedures and medical care, more patients are surviving into adolescence and adulthood. Brain imaging and pathology studies have shown that patients with SV have differences in brain structure and metabolism even before the first surgery, and as early as in utero. Furthermore, a significant number of patients have new or more severe lesions after the initial surgery, and many still have brain abnormalities into early childhood. However, there are no detailed brain structural data of SV patients in adolescence. Our group recruited a large cohort of post-Fontan SV patients aged 10-19 years. Separate analyses of neuropsychological and behavioral outcomes in these patients show deficits in multiple areas of cognition, increased rates of attention deficit-hyperactivity disorder (ADHD), and increased use of remedial and/or special education services compared to a control group. Post-Fontan adolescents have more gross brain abnormalities, including evidence of chronic ischemic stroke. Furthermore, there are widespread reductions in cortical and subcortical gray matter volume and cortical thickness, some of which are associated with medical and surgical variables. Diffusion tensor imaging (DTI) analyses show widespread areas of altered white matter microstructure in deep subcortical and cerebellar white matter. In this dissertation, I use graph theory methods to characterize structural connectivity based on gray matter (cortical thickness covariance) and white matter (DTI tractography), and examine associations between brain structure and neurodevelopment. I found that brain network connectivity differs in post-Fontan patients compared with controls, both at the global and regional level. Additionally, deficits in overall network structure were associated with impaired neurodevelopment in several domains, including general intelligence, executive function, and visuospatial skills. These data suggest that early neuroprotection should be a major focus in the care of SV patients, with the goal of improving long-term neurodevelopmental outcomes

Examining the development of brain structure in utero with fetal MRI, acquired as part of the Developing Human Connectome Project

The human brain is an incredibly complex organ, and the study of it traverses many scales across space and time. The development of the brain is a protracted process that begins embryonically but continues into adulthood. Although neural circuits have the capacity to adapt and are modulated throughout life, the major structural foundations are laid in utero during the fetal period, through a series of rapid but precisely timed, dynamic processes. These include neuronal proliferation, migration, differentiation, axonal pathfinding, and myelination, to name a few. The fetal origins of disease hypothesis proposed that a variety of non-communicable diseases emerging in childhood and adulthood could be traced back to a series of risk factors effecting neurodevelopment in utero (Barker 1995). Since this publication, many studies have shown that the structural scaffolding of the brain is vulnerable to external environmental influences and the perinatal developmental window is a crucial determinant of neurological health later in life. However, there remain many fundamental gaps in our understanding of it. The study of human brain development is riddled with biophysical, ethical, and technical challenges. The Developing Human Connectome Project (dHCP) was designed to tackle these specific challenges and produce high quality open-access perinatal MRI data, to enable researchers to investigate normal and abnormal neurodevelopment (Edwards et al., 2022). This thesis will focus on investigating the diffusion-weighted and anatomical (T2) imaging data acquired in the fetal period, between the second to third trimester (22 – 37 gestational weeks). The limitations of fetal MR data are ill-defined due to a lack of literature and therefore this thesis aims to explore the data through a series of critical and strategic analysis approaches that are mindful of the biophysical challenges associated with fetal imaging. A variety of analysis approaches are optimised to quantify structural brain development in utero, exploring avenues to relate the changes in MR signal to possible neurobiological correlates. In doing so, the work in this thesis aims to improve mechanistic understanding about how the human brain develops in utero, providing the clinical and medical imaging community with a normative reference point. To this aim, this thesis investigates fetal neurodevelopment with advanced in utero MRI methods, with a particular emphasis on diffusion MRI. Initially, the first chapter outlines a descriptive, average trajectory of diffusion metrics in different white matter fiber bundles across the second to third trimester. This work identified unique polynomial trajectories in diffusion metrics that characterise white matter development (Wilson et al., 2021). Guided by previous literature on the sensitivity of DWI to cellular processes, I formulated a hypothesis about the biophysical correlates of diffusion signal components that might underpin this trend in transitioning microstructure. This hypothesis accounted for the high sensitivity of the diffusion signal to a multitude of simultaneously occurring processes, such as the dissipating radial glial scaffold, commencement of pre-myelination and arborization of dendritic trees. In the next chapter, the methods were adapted to address this hypothesis by introducing another dimension, and charting changes in diffusion properties along developing fiber pathways. With this approach it was possible to identify compartment-specific microstructural maturation, refining the spatial and temporal specificity (Wilson et al., 2023). The results reveal that the dynamic fluctuations in the components of the diffusion signal correlate with observations from previous histological work. Overall, this work allowed me to consolidate my interpretation of the changing diffusion signal from the first chapter. It also serves to improve understanding about how diffusion signal properties are affected by processes in transient compartments of the fetal brain. The third chapter of this thesis addresses the hypothesis that cortical gyrification is influenced by both underlying fiber connectivity and cytoarchitecture. Using the same fetal imaging dataset, I analyse the tissue microstructural change underlying the formation of cortical folds. I investigate correlations between macrostructural surface features (curvature, sulcal depth) and tissue microstructural measures (diffusion tensor metrics, and multi-shell multi-tissue decomposition) in the subplate and cortical plate across gestational age, exploring this relationship both at the population level and within subjects. This study provides empirical evidence to support the hypotheses that microstructural properties in the subplate and cortical plate are altered with the development of sulci. The final chapter explores the data without anatomical priors, using a data-driven method to extract components that represent coordinated structural maturation. This analysis aims to examine if brain regions with coherent patterns of growth over the fetal period converge on neonatal functional networks. I extract spatially independent features from the anatomical imaging data and quantify the spatial overlap with pre-defined neonatal resting state networks. I hypothesised that coherent spatial patterns of anatomical development over the fetal period would map onto the functional networks observed in the neonatal period. Overall, this thesis provides new insight about the developmental contrast over the second to third trimester of human development, and the biophysical correlates affecting T2 and diffusion MR signal. The results highlight the utility of fetal MRI to research critical mechanisms of structural brain maturation in utero, including white matter development and cortical gyrification, bridging scales from neurobiological processes to whole brain macrostructure. their gendered constructions relating to women

Mapping connections in the neonatal brain with magnetic resonance imaging

The neonatal brain undergoes rapid development after birth, including the growth and maturation of the white matter fibre bundles that connect brain regions. Diffusion MRI (dMRI) is a unique tool for mapping these bundles in vivo, providing insight into factors that impact the development of white matter and how its maturation influences other developmental processes. However, most studies of neonatal white matter do not use specialised analysis tools, instead using tools that have been developed for the adult brain. However, the neonatal brain is not simply a small adult brain, as differences in geometry and tissue decomposition cause considerable differences in dMRI contrast. In this thesis, methods are developed to map white matter connections during this early stage of neurodevelopment. First, two contrasting approaches are explored: ROI-constrained protocols for mapping individual tracts, and the generation of whole-brain connectomes that capture the developing brain's full connectivity profile. The impact of the gyral bias, a methodological confound of tractography, is quantified and compared with the equivalent measurements for adult data. These connectomes form the basis for a novel, data-driven framework, in which they are decomposed into white matter bundles and their corresponding grey matter terminations. Independent component analysis and non-negative matrix factorisation are compared for the decomposition, and are evaluated against in-silico simulations. Data-driven components of dMRI tractography data are compared with manual tractography, and networks obtained from resting-state functional MRI. The framework is further developed to provide corresponding components between groups and individuals. The data-driven components are used to generate cortical parcellations, which are stable across subjects. Finally, some future applications are outlined that extend the use of these methods beyond the context of neonatal imaging, in order to bridge the gap between functional and structural analysis paradigms, and to chart the development of white matter throughout the lifespan and across species

Diffusion Weighted Imaging of the Neonatal Brain

Although in the last decades advances in fetal and neonatal medicine have reduced mortality in neonatal intensive care units in the Western world, the morbidity due to brain injury remains high. Patterns of neonatal brain injury can be roughly divided in (1) term and (2) preterm patterns. Table 1 shows the number of infants admitted to the NICU in the Sophia Children’s Hospital between March 2008 and March 2010 with a typical ‘neurological’ diagnosis. The table highlights differences in diagnoses between preterm and term infants in relation to gender. In preterm infants the most common diagnoses are: persistent flaring (hypersignal intensity seen in periventricluar white matter using cranial ultrasound), intraventricular haemorrhage and venous infarction. In term infants perinatal asphyxia and perinatal stroke are most often reported

The neurostructural effects of prenatal exposure to methamphetamine in an infant population in the Western Cape

Prenatal methamphetamine exposure is associated with functional and neurostructural alterations, but neuroimaging investigations of these effects in infants are almost non-existent. Studies in neonates permit a degree of separation of drug exposure effects from potential confounders in the postnatal environment. Magnetic resonance imaging (MRI) was used to investigate the neurostructural effects of prenatal methamphetamine exposure on neonates recruited from a Cape Town community. Mothers were recruited during pregnancy and interviewed regarding methamphetamine use. Women in the exposure group used methamphetamine at least twice per month during pregnancy, while control mothers did not use methamphetamine. MRI scans were acquired within the first postnatal month. Anatomical images were processed using FreeSurfer and subcortical and cerebellar structures manually segmented with Freeview. Volumes were regressed with methamphetamine exposure (days/month of pregnancy) and related confounding variables, including total brain volume, gestational age at scan, exposure to cigarette smoking and infant sex. Diffusion data were processed with FSL, and diffusion tensors and tensor parameters determined using AFNI. Probabilistic tractography defined white matter connections between target regions. For the first analysis, five major white matter networks (commissural, and bilateral projection and association networks) were defined between spherical targets. For the second analysis, regions traced in the anatomical study were used as targets. Averaged DTI parameters were then calculated for each connection, and multiple regression analysis determined associations between DTI parameters and methamphetamine exposure at network level and in the individual connections. Methamphetamine exposure was associated with reduced caudate nucleus volume bilaterally, and in the right caudate following adjustment for confounders. Exposure was associated with reduced fractional anisotropy in all major white matter networks, and in individual connections within the limbic meso-cortico-striatal circuit. Exposure was associated with increased radial diffusivity in a subset of these. These results support findings in older children of methamphetamine-induced neurostructural damage, and demonstrate that such effects are already measurable in neonates. Corticostriatal circuit changes may underlie the impaired executive function observed in prenatally exposed children, and suggest a specific mechanism of damage in dopaminergic-related circuits that is consistent with the neurotoxic actions of methamphetamine

Diffusion Tensor Imaging as a Diagnostic and Research Tool: A Study on Preterm Infants

Diffusion tensor imaging (DTI) is an advanced magnetic resonance imaging (MRI) technique. DTI is based on free thermal motion (diffusion) of water molecules. The properties of diffusion can be represented using parameters such as fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, which are calculated from DTI data. These parameters can be used to study the microstructure in fibrous structure such as brain white matter. The aim of this study was to investigate the reproducibility of region-of-interest (ROI) analysis and determine associations between white matter integrity and antenatal and early postnatal growth at term age using DTI. Antenatal growth was studied using both the ROI and tract-based spatial statistics (TBSS) method and postnatal growth using only the TBSS method. The infants included to this study were born below 32 gestational weeks or birth weight less than 1,501 g and imaged with a 1.5 T MRI system at term age. Total number of 132 infants met the inclusion criteria between June 2004 and December 2006. Due to exclusion criteria, a total of 76 preterm infants (ROI) and 36 preterm infants (TBSS) were accepted to this study. The ROI analysis was quite reproducible at term age. Reproducibility varied between white matter structures and diffusion parameters. Normal antenatal growth was positively associated with white matter maturation at term age. The ROI analysis showed associations only in the corpus callosum. Whereas, TBSS revealed associations in several brain white matter areas. Infants with normal antenatal growth showed more mature white matter compared to small for gestational age infants. The gestational age at birth had no significant association with white matter maturation at term age. It was observed that good early postnatal growth associated negatively with white matter maturation at term age. Growth-restricted infants seemed to have delayed brain maturation that was not fully compensated at term, despite catchup growth.Diffuusiotensorikuvaus diagnostisena ja tutkimustyökaluna keskostutkimuksessa Diffuusiotensorikuvaus (DTI) on magneettikuvauksen erikoistekniikka. DTI perustuu veden vapaaseen lämpöliikkeeseen (diffuusioon). Diffuusion ominaisuuksia voidaan esittää DTI-datasta laskettavien parametrien avulla. Tällaisia parametreja ovat esimerkiksi fraktionaalinen anisotropia, keskimääräinen diffusiviteetti, aksiaalinen ja radiaalinen diffusiviteetti. Näitä parametrejä voidaan käyttää säikeisten rakenteiden esimerkiksi aivojen valkoisen aineen tutkimiseen. Tässä tutkimuksessa selvitettiin keskosten aivojen diffuusiotensorikuvista tehtyjen mielenkiintoalueisiin (ROI) perustuvien mittausten toistettavuutta sekä tutkittiin valkoisen aineen kypsyyden ja raskauden aikaisen sekä varhaisen postnataalisen kasvun välistä yhteyttä. Raskauden aikaisen kasvun vaikutusta tutkittiin käyttäen sekä ROI- että TBSS-tekniikoita. Postnataalista kasvua tarkasteltiin ainoastaan TBSS-tekniikalla. Tähän tutkimukseen otettiin mukaan keskoset, jotka syntyivät ennen 32 raskausviikkoa tai joiden syntymäpaino oli alle 1,501 g sekä MRI kuvaus oli tehty lasketunajan kohdalla. Tutkimukseen hyväksyttiin kesäkuun 2004 ja joulukuun 2006 välillä 132 keskosta. Poissulkukriteerien takia 76 keskosta (ROI) ja 36 (TBSS) hyväksyttiin tähän tutkimukseen. ROI-analyysi osoittautui melko toistettavaksi lasketun ajan iässä. Toistettavuus vaihteli sekä valkoisen aineen rakenteiden että diffuusioparametrien välillä. Normaali raskauden aikainen kasvu liittyi hyvään valkoisen aineen kehitykseen lasketunajan kohdalla. ROI-tekniikalla yhteys havaittiin corpus callosumin alueella. TBSS-menetelmä puolestaan näytti yhteyden usealla eri valkoisen aineen alueella. Syntymähetken gestaatioiällä ei havaittu yhteyttä valkoisen aineen kehitysasteeseen lasketun ajan kohdalla. Hyvän varhaisen vaiheen postnataalisen kasvun havaittiin liittyvän heikompaan valkoisen aineen kehitysasteeseen lasketunajan kohdalla. Saavutuskasvu ei ollut korjannut raskauden aikaisen kasvuhäiriön vaikutusta aivojen kypsyyteen laskettuun aikaan mennessä.Siirretty Doriast

MR Imaging of the Preterm Brain: safer better faster stronger

__Abstract__ Human brain development and maturation consist of complex processes that span from the first trimester of pregnancy to adult life. These processes include: 1) neuronal proliferation, characterized by generation of neurons in the dorsal subventricular zone and ventral germinative epithelium of the ganglionic eminence; 2) migration, where neurons move from these zones to specific sites where they will reside for life; 3) organization, in which neurons differentiate to subplate neurons, align, orientate and connect through their axons and dendrites. Glial cells differentiate into astrocytes, oligodendrocytes and microglia, and 4) myelination, where oligodendrocytes produce myelin that will be deposited around axons. Preterm infants are born in this critical period, in which the brain is particularly vulnerable to exogenous and endogenous events. Perinatal hypoxia-ischemia, hyperoxia, infection and hypocarbia can result in fluctuations in cerebral blood flow, inflammation, increased excitotoxicity and oxidative stress, all of which can affect normal brain ontogenesis and cause irreversible injury. In general, the two most commonly recognized variants of preterm brain injury are: periventricular white matter (WM) injury and hemorrhage in the germinal matrix and lateral ventricle. These injury patterns will be discussed separately in the following sections