Molecular signatures of cortical expansion in the human fetal brain.

The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. A growing catalogue of cells in the prenatal brain has revealed remarkable molecular diversity across cortical areas.1,2 Despite this, little is known about how this translates into the patterns of differential cortical expansion observed in humans during the latter stages of gestation. Here we present a new resource, µBrain, to facilitate knowledge translation between molecular and anatomical descriptions of the prenatal developing brain. Built using generative artificial intelligence, µBrain is a three-dimensional cellular-resolution digital atlas combining publicly-available serial sections of the postmortem human brain at 21 weeks gestation3 with bulk tissue microarray data, sampled across 29 cortical regions and 5 transient tissue zones.4 Using µBrain, we evaluate the molecular signatures of preferentially-expanded cortical regions during human gestation, quantified in utero using magnetic resonance imaging (MRI). We find that differences in the rates of expansion across cortical areas during gestation respect anatomical and evolutionary boundaries between cortical types5 and are founded upon extended periods of upper-layer cortical neuron migration that continue beyond mid-gestation. We identify a set of genes that are upregulated from mid-gestation and highly expressed in rapidly expanding neocortex, which are implicated in genetic disorders with cognitive sequelae. Our findings demonstrate a spatial coupling between areal differences in the timing of neurogenesis and rates of expansion across the neocortical sheet during the prenatal epoch. The µBrain atlas is available from: https://garedaba.github.io/micro-brain/ and provides a new tool to comprehensively map early brain development across domains, model systems and resolution scales.

Longitudinal MRI Evaluation of Brain Development in Fetuses with Congenital Diaphragmatic Hernia around the Time of Fetal Endotracheal Occlusion.

BACKGROUND AND PURPOSE: Congenital diaphragmatic hernia is associated with high mortality and morbidity, including evidence suggesting neurodevelopmental comorbidities after birth. The aim of this study was to document longitudinal changes in brain biometry and the cortical folding pattern in fetuses with congenital diaphragmatic hernia compared with healthy fetuses. MATERIALS AND METHODS: This is a retrospective cohort study including fetuses with isolated congenital diaphragmatic hernia between January 2007 and May 2019, with at least 2 MR imaging examinations. For controls, we used images from fetuses who underwent MR imaging for an unrelated condition that did not compromise fetal brain development and fetuses from healthy pregnant women. Biometric measurements and 3D segmentations of brain structures were used as well as qualitative and quantitative grading of the supratentorial brain. Brain development was correlated with disease-severity markers. RESULTS: Forty-two fetuses were included, with a mean gestational age at first MR imaging of 28.0 (SD, 2.1) weeks and 33.2 (SD, 1.3) weeks at the second imaging. The mean gestational age in controls was 30.7 (SD, 4.2) weeks. At 28 weeks, fetuses with congenital diaphragmatic hernia had abnormal qualitative and quantitative maturation, more extra-axial fluid, and larger total skull volume. By 33 weeks, qualitative grading scores were still abnormal, but quantitative scoring was in the normal range. In contrast, the extra-axial fluid volume remained abnormal with increased ventricular volume. Normal brain parenchymal volumes were found. CONCLUSIONS: Brain development in fetuses with congenital diaphragmatic hernia around 28 weeks appears to be delayed. This feature is less prominent at 33 weeks. At this stage, there was also an increase in ventricular and extra-axial space volume.

Neurodevelopmental Correlates of Fetal Motor Behavior Assessed Using Cine MR Imaging.

BACKGROUND AND PURPOSE: Fetal motor behavior is widely used as a clinical indicator for healthy development; however, our understanding of its potential as a marker for neurologic integrity is underdeveloped. MR imaging allows complete views of the whole fetus, which, combined with brain imaging, may improve the characterization of this relationship. This study aimed to combine an analysis of fetal motor behavior, brain MR imaging, and postnatal outcome, to provide insight into neurodevelopmental correlates of motor behavior. MATERIALS AND METHODS: Cine MR imaging was used to acquire sequences of fetal motor behavior in subjects with normal and abnormal findings on conventional brain MR imaging between 18 weeks' gestation and term. General movement sequences were analyzed using established criteria. Brain MR imaging was reported by an expert fetal neuroradiologist. Subjects were followed for up to 4 years postnatally with standard postnatal assessments. RESULTS: Nineteen of 21 fetuses with normal brain MR imaging findings showed normal general movements, compared with 14 of 22 of the fetuses with abnormal brain MR imaging findings, which, when classified by severity of the malformation, showed a significant relationship with postnatal outcome (P = .021). There was a significant relationship among neurodevelopmental outcome, general movement quality, and MR imaging of the brain (P = .020). CONCLUSIONS: The findings from this study demonstrate that a combined structural and functional imaging approach to the fetus will improve the characterization of early neurologic integrity, with the potential to inform postnatal outcome. This also lays the groundwork for further in vivo research as advanced imaging techniques are developed to study fetal neurologic development.

Altered white matter and cortical structure in neonates with antenatally diagnosed isolated ventriculomegaly.

Ventriculomegaly (VM) is the most common central nervous system abnormality diagnosed antenatally, and is associated with developmental delay in childhood. We tested the hypothesis that antenatally diagnosed isolated VM represents a biological marker for altered white matter (WM) and cortical grey matter (GM) development in neonates. 25 controls and 21 neonates with antenatally diagnosed isolated VM had magnetic resonance imaging at 41.97(± 2.94) and 45.34(± 2.14) weeks respectively. T2-weighted scans were segmented for volumetric analyses of the lateral ventricles, WM and cortical GM. Diffusion tensor imaging (DTI) measures were assessed using voxel-wise methods in WM and cortical GM; comparisons were made between cohorts. Ventricular and cortical GM volumes were increased, and WM relative volume was reduced in the VM group. Regional decreases in fractional anisotropy (FA) and increases in mean diffusivity (MD) were demonstrated in WM of the VM group compared to controls. No differences in cortical DTI metrics were observed. At 2 years, neurodevelopmental delays, especially in language, were observed in 6/12 cases in the VM cohort. WM alterations in isolated VM cases may be consistent with abnormal development of WM tracts involved in language and cognition. Alterations in WM FA and MD may represent neural correlates for later neurodevelopmental deficits.

Construction of a fetal spatio-temporal cortical surface atlas from in utero MRI: Application of spectral surface matching.

In this study, we construct a spatio-temporal surface atlas of the developing cerebral cortex, which is an important tool for analysing and understanding normal and abnormal cortical development. In utero Magnetic Resonance Imaging (MRI) of 80 healthy fetuses was performed, with a gestational age range of 21.7 to 38.9 weeks. Topologically correct cortical surface models were extracted from reconstructed 3D MRI volumes. Accurate correspondences were obtained by applying a joint spectral analysis to cortices for sets of subjects close to a specific age. Sulcal alignment was found to be accurate in comparison to spherical demons, a state of the art registration technique for aligning 2D cortical representations (average Fréchet distance≈0.4 mm at 30 weeks). We construct consistent, unbiased average cortical surface templates, for each week of gestation, from age-matched groups of surfaces by applying kernel regression in the spectral domain. These were found to accurately capture the average cortical shape of individuals within the cohort, suggesting a good alignment of cortical geometry. Each spectral embedding and its corresponding cortical surface template provide a dual reference space where cortical geometry is aligned and a vertex-wise morphometric analysis can be undertaken.

Automated fetal brain segmentation from 2D MRI slices for motion correction.

Motion correction is a key element for imaging the fetal brain in-utero using Magnetic Resonance Imaging (MRI). Maternal breathing can introduce motion, but a larger effect is frequently due to fetal movement within the womb. Consequently, imaging is frequently performed slice-by-slice using single shot techniques, which are then combined into volumetric images using slice-to-volume reconstruction methods (SVR). For successful SVR, a key preprocessing step is to isolate fetal brain tissues from maternal anatomy before correcting for the motion of the fetal head. This has hitherto been a manual or semi-automatic procedure. We propose an automatic method to localize and segment the brain of the fetus when the image data is acquired as stacks of 2D slices with anatomy misaligned due to fetal motion. We combine this segmentation process with a robust motion correction method, enabling the segmentation to be refined as the reconstruction proceeds. The fetal brain localization process uses Maximally Stable Extremal Regions (MSER), which are classified using a Bag-of-Words model with Scale-Invariant Feature Transform (SIFT) features. The segmentation process is a patch-based propagation of the MSER regions selected during detection, combined with a Conditional Random Field (CRF). The gestational age (GA) is used to incorporate prior knowledge about the size and volume of the fetal brain into the detection and segmentation process. The method was tested in a ten-fold cross-validation experiment on 66 datasets of healthy fetuses whose GA ranged from 22 to 39 weeks. In 85% of the tested cases, our proposed method produced a motion corrected volume of a relevant quality for clinical diagnosis, thus removing the need for manually delineating the contours of the brain before motion correction. Our method automatically generated as a side-product a segmentation of the reconstructed fetal brain with a mean Dice score of 93%, which can be used for further processing.

Automatic quantification of normal cortical folding patterns from fetal brain MRI.

We automatically quantify patterns of normal cortical folding in the developing fetus from in utero MR images (N=80) over a wide gestational age (GA) range (21.7 to 38.9weeks). This work on data from healthy subjects represents a first step towards characterising abnormal folding that may be related to pathology, facilitating earlier diagnosis and intervention. The cortical boundary was delineated by automatically segmenting the brain MR image into a number of key structures. This utilised a spatio-temporal atlas as tissue priors in an expectation-maximization approach with second order Markov random field (MRF) regularization to improve the accuracy of the cortical boundary estimate. An implicit high resolution surface was then used to compute cortical folding measures. We validated the automated segmentations with manual delineations and the average surface discrepancy was of the order of 1mm. Eight curvature-based folding measures were computed for each fetal cortex and used to give summary shape descriptors. These were strongly correlated with GA (R(2)=0.99) confirming the close link between neurological development and cortical convolution. This allowed an age-dependent non-linear model to be accurately fitted to the folding measures. The model supports visual observations that, after a slow initial start, cortical folding increases rapidly between 25 and 30weeks and subsequently slows near birth. The model allows the accurate prediction of fetal age from an observed folding measure with a smaller error where growth is fastest. We also analysed regional patterns in folding by parcellating each fetal cortex using a nine-region anatomical atlas and found that Gompertz models fitted the change in lobar regions. Regional differences in growth rate were detected, with the parietal and posterior temporal lobes exhibiting the fastest growth, while the cingulate, frontal and medial temporal lobes developed more slowly.