Maternal obesity alters fetal neuroinflammation in a murine model of preterm birth.

BACKGROUND: Preterm birth from intrauterine infection is a leading cause of neonatal neurologic morbidity. Likewise, maternal obesity is associated with intra-amniotic infection and inflammation. Whether maternal obesity is a risk factor for fetal brain injury that occurs with premature birth remains unknown. This study hypothesized that maternal obesity intensifies fetal neuroinflammation in the setting of premature delivery. OBJECTIVE: This study aimed to examine the influence of maternal obesity on perinatal neuroinflammatory responses that arise with preterm birth using a murine model. STUDY DESIGN: Dams with obesity were generated via a high-fat diet that was maintained throughout pregnancy. In parallel, dams without obesity (normal) received a control diet. All dams were paired with males on normal diet. Pregnant dams were randomized to receive an intrauterine administration of bacterial endotoxin (lipopolysaccharide) or the vehicle (phosphate-buffered saline) on embryo day 15.5 of what is typically a 19- to 21-day gestation. Fetal brains were harvested 6 hours after intrauterine administrations, and the expressions of key inflammatory cytokines (Il1b, Il6, and Tnf) and panels of metabolic, immune, and inflammatory genes were analyzed. RESULTS: With the phosphate-buffered saline, there was no difference in gene expression related to maternal obesity. There were substantial differences in Il6 and immune/inflammatory expression profiles in fetal brains from dams with obesity vs normal dams that received lipopolysaccharide. Few differences were observed among the metabolic genes examined under these conditions. The gene expression pattern associated with maternal obesity correlated with pathways related to white matter injury. CONCLUSION: The expression of neuroinflammatory markers instigated by bacterial endotoxin via intrauterine lipopolysaccharide was greater in embryo brains obtained from dams with obesity. Expression profiles suggest that in combination with intrauterine inflammation, maternal obesity may increase the risk of fetal white matter injury. Further investigation is warranted to understand the relationship between maternal health and neurologic outcomes associated with prematurity.

Efficient segmentation of fetal brain MRI based on the physical resolution.

BACKGROUND: The image resolution of fetal brain magnetic resonance imaging (MRI) is a critical factor in brain development measures, which is mainly determined by the physical resolution configured in the MRI sequence. However, fetal brain MRI are commonly reconstructed to 3D images with a higher apparent resolution, compared to the original physical resolution. PURPOSE: This work is to demonstrate that accurate segmentation can be achieved based on the MRI physical resolution, and the high apparent resolution segmentation can be achieved by a simple deep learning module. METHODS: This retrospective study included 150 adult and 80 fetal brain MRIs. The adult brain MRIs were acquired at a high physical resolution, which were downsampled to visualize and quantify its impacts on the segmentation accuracy. The physical resolution of fetal images was estimated based on MRI acquisition settings and the images were downsampled accordingly before segmentation and restored using multiple upsampling strategies. Segmentation accuracy of ConvNet models were evaluated on the original and downsampled images. Dice coefficients were calculated, and compared to the original data. RESULTS: When the apparent resolution was higher than the physical resolution, the accuracy of fetal brain segmentation had negligible degradation (accuracy reduced by 0.26%, 1.1%, and 1.8% with downsampling factors of 4/3, 2, and 4 in each dimension, without significant differences from the original data). Using a downsampling factor of 4 in each dimension, the proposed method provided 7× smaller and 10× faster models. CONCLUSION: Efficient and accurate fetal brain segmentation models can be developed based on the physical resolution of MRI acquisitions.

Dynamic stress- and inflammatory-based regulation of psychiatric risk loci in human neurons.

The prenatal environment can alter neurodevelopmental and clinical trajectories, markedly increasing risk for psychiatric disorders in childhood and adolescence. To understand if and how fetal exposures to stress and inflammation exacerbate manifestation of genetic risk for complex brain disorders, we report a large-scale context-dependent massively parallel reporter assay (MPRA) in human neurons designed to catalogue genotype x environment (GxE) interactions. Across 240 genome-wide association study (GWAS) loci linked to ten brain traits/disorders, the impact of hydrocortisone, interleukin 6, and interferon alpha on transcriptional activity is empirically evaluated in human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons. Of ~3,500 candidate regulatory risk elements (CREs), 11% of variants are active at baseline, whereas cue-specific CRE regulatory activity range from a high of 23% (hydrocortisone) to a low of 6% (IL-6). Cue-specific regulatory activity is driven, at least in part, by differences in transcription factor binding activity, the gene targets of which show unique enrichments for brain disorders as well as co-morbid metabolic and immune syndromes. The dynamic nature of genetic regulation informs the influence of environmental factors, reveals a mechanism underlying pleiotropy and variable penetrance, and identifies specific risk variants that confer greater disorder susceptibility after exposure to stress or inflammation. Understanding neurodevelopmental GxE interactions will inform mental health trajectories and uncover novel targets for therapeutic intervention.

Anatomically constrained tractography of the fetal brain.

Diffusion-weighted Magnetic Resonance Imaging (dMRI) is increasingly used to study the fetal brain in utero. An important computation enabled by dMRI is streamline tractography, which has unique applications such as tract-specific analysis of the brain white matter and structural connectivity assessment. However, due to the low fetal dMRI data quality and the challenging nature of tractography, existing methods tend to produce highly inaccurate results. They generate many false streamlines while failing to reconstruct the streamlines that constitute the major white matter tracts. In this paper, we advocate for anatomically constrained tractography based on an accurate segmentation of the fetal brain tissue directly in the dMRI space. We develop a deep learning method to compute the segmentation automatically. Experiments on independent test data show that this method can accurately segment the fetal brain tissue and drastically improve the tractography results. It enables the reconstruction of highly curved tracts such as optic radiations. Importantly, our method infers the tissue segmentation and streamline propagation direction from a diffusion tensor fit to the dMRI data, making it applicable to routine fetal dMRI scans. The proposed method can facilitate the study of fetal brain white matter tracts with dMRI.

FetMRQC: A robust quality control system for multi-centric fetal brain MRI.

Fetal brain MRI is becoming an increasingly relevant complement to neurosonography for perinatal diagnosis, allowing fundamental insights into fetal brain development throughout gestation. However, uncontrolled fetal motion and heterogeneity in acquisition protocols lead to data of variable quality, potentially biasing the outcome of subsequent studies. We present FetMRQC, an open-source machine-learning framework for automated image quality assessment and quality control that is robust to domain shifts induced by the heterogeneity of clinical data. FetMRQC extracts an ensemble of quality metrics from unprocessed anatomical MRI and combines them to predict experts' ratings using random forests. We validate our framework on a pioneeringly large and diverse dataset of more than 1600 manually rated fetal brain T2-weighted images from four clinical centers and 13 different scanners. Our study shows that FetMRQC's predictions generalize well to unseen data while being interpretable. FetMRQC is a step towards more robust fetal brain neuroimaging, which has the potential to shed new insights on the developing human brain.

T2*-Relaxometry MRI to Assess Third Trimester Placental and Fetal Brain Oxygenation and Placental Characteristics in Healthy Fetuses and Fetuses With Congenital Heart Disease.

BACKGROUND: Congenital heart disease (CHD) has been linked to impaired placental and fetal brain development. Assessing the placenta and fetal brain in parallel may help further our understanding of the relationship between development of these organs. HYPOTHESIS: 1) Placental and fetal brain oxygenation are correlated, 2) oxygenation in these organs is reduced in CHD compared to healthy controls, and 3) placental structure is altered in CHD. STUDY TYPE: Retrospective case-control. POPULATION: Fifty-one human fetuses with CHD (32 male; median [IQR] gestational age [GA] = 32.0 [30.9-32.9] weeks) and 30 from uncomplicated pregnancies with normal birth outcomes (18 male; median [IQR] GA = 34.5 [31.9-36.7] weeks). FIELD STRENGTH/SEQUENCE: 1.5 T single-shot multi-echo-gradient-echo echo-planar imaging. ASSESSMENT: Masking was performed using an automated nnUnet model. Mean brain and placental T2* and quantitative measures of placental texture, volume, and morphology were calculated. STATISTICAL TESTS: Spearman's correlation coefficient for determining the association between brain and placental T2*, and between brain and placental characteristics with GA. P-values for comparing brain T2*, placenta T2*, and placental characteristics between groups derived from ANOVA. Significance level P < 0.05. RESULTS: There was a significant positive association between placental and fetal brain T2* (⍴ = 0.46). Placental and fetal brain T2* showed a significant negative correlation with GA (placental T2* ⍴ = -0.65; fetal brain T2* ⍴ = -0.32). Both placental and fetal brain T2* values were significantly reduced in CHD, after adjusting for GA (placental T2*: control = 97 [±24] msec, CHD = 83 [±23] msec; brain T2*: control = 218 [±26] msec, CHD = 202 [±25] msec). Placental texture and morphology were also significantly altered in CHD (Texture: control = 0.84 [0.83-0.87], CHD = 0.80 [0.78-0.84]; Morphology: control = 9.9 [±2.2], CHD = 10.8 [±2.0]). For all fetuses, there was a significant positive association between placental T2* and placental texture (⍴ = 0.46). CONCLUSION: Placental and fetal brain T2* values are associated in healthy fetuses and those with CHD. Placental and fetal brain oxygenation are reduced in CHD. Placental appearance is significantly altered in CHD and shows associations with placental oxygenation, suggesting altered placental development and function may be related. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Correlating maternal and cord-blood inflammatory markers and BDNF with human fetal brain activity recorded by magnetoencephalography: An exploratory study.

Background: During gestation, the brain development of the fetus is affected by many biological markers, where inflammatory processes and neurotrophic factors have been of particular interest in the past decade. Aim: This exploratory study is the first attempt to explore the relationships between biomarker levels in maternal and cord-blood samples and human fetal brain activity measured with non-invasive fetal magnetoencephalography (fMEG). Method: Twenty-three women were enrolled in this study for collection of maternal serum and fMEG tracings immediately prior to their scheduled cesarean delivery. Twelve of these women had a preexisting diabetic condition. At the time of delivery, umbilical cord blood was also collected. Biomarker levels from both maternal and cord blood were measured and subsequently analyzed for correlations with fetal brain activity in four frequency bands extracted from fMEG power spectral densities. Results: Relative power in the delta, alpha, and beta frequency bands exhibited moderate-sized correlations with maternal BDNF and cord-blood CRP levels before and after adjusting for confounding diabetic status. These correlations were negative for the delta band, and positive for the alpha and beta bands. Maternal CRP and cord-blood BDNF and IL-6 exhibited negligible correlations with relative power in all four bands. Diabetes did not appear to be a strong confounding factor affecting the studied biomarkers. Conclusions: Maternal BDNF levels and cord-blood CRP levels appear to have a direct correlation to fetal brain activity. Our findings indicate the potential use of these biomarkers in conjunction with fetal brain electrophysiology to track fetal neurodevelopment.

Unraveling the Molecular Mechanisms of the Neurodevelopmental Consequences of Fetal Protein Deficiency: Insights From Rodent Models and Public Health Implications.

Fetal brain development requires increased maternal protein intake to ensure that offspring reach their optimal cognitive potential in infancy and adulthood. While protein deficiency remains a prevalent issue in developing countries, it is also reemerging in Western societies due to the growing adoption of plant-based diets, some of which are monotonous and may fail to provide sufficient amino acids crucial for the brain's critical developmental phase. Confounding variables in human nutritional research have impeded our understanding of the precise impact of protein deficiency on fetal neurodevelopment, as well as its implications for childhood neurocognitive performance. Moreover, it remains unclear whether such deficiency could predispose to mental health problems in adulthood, mirroring observations in individuals exposed to prenatal famine. In this review, we sought to evaluate mechanistic data derived from rodent models, placing special emphasis on the involvement of neuroendocrine axes, the influence of sex and timing, epigenetic modifications, and cellular metabolism. Despite notable progress, critical knowledge gaps remain, including understanding the long-term reversibility of effects due to fetal protein restriction and the interplay between genetic predisposition and environmental factors. Enhancing our understanding of the precise mechanisms that connect prenatal nutrition to brain development in future research endeavors can be significantly advanced by integrating multiomics approaches and utilizing additional alternative models such as nonhuman primates. Furthermore, it is crucial to investigate potential interventions aimed at alleviating adverse outcomes. Ultimately, this research has profound implications for guiding public health strategies aimed at raising awareness about the crucial role of optimal maternal nutrition in supporting fetal neurodevelopment.

The Developmental Origins of Health and Disease theory posits that suboptimal conditions during early life exert a profound influence on adult health, potentially predisposing individuals to conditions such as neuropsychiatric disorders. By reviewing studies in rodents, we identified common mechanisms of how inadequate fetal protein uptake alters brain development and may contribute to anxiety, impaired memory function, and altered metabolism in adulthood. Adequate protein consumption during pregnancy is therefore critical to support healthy brain development.

Ultrasound Plane Pose Regression: Assessing Generalized Pose Coordinates in the Fetal Brain.

In obstetric ultrasound (US) scanning, the learner's ability to mentally build a three-dimensional (3D) map of the fetus from a two-dimensional (2D) US image represents a significant challenge in skill acquisition. We aim to build a US plane localization system for 3D visualization, training, and guidance without integrating additional sensors. This work builds on top of our previous work, which predicts the six-dimensional (6D) pose of arbitrarily oriented US planes slicing the fetal brain with respect to a normalized reference frame using a convolutional neural network (CNN) regression network. Here, we analyze in detail the assumptions of the normalized fetal brain reference frame and quantify its accuracy with respect to the acquisition of transventricular (TV) standard plane (SP) for fetal biometry. We investigate the impact of registration quality in the training and testing data and its subsequent effect on trained models. Finally, we introduce data augmentations and larger training sets that improve the results of our previous work, achieving median errors of 2.97 mm and 6.63° for translation and rotation, respectively.

Effects of mid­gestational sevoflurane and magnesium sulfate on maternal oxidative stress, inflammation and fetal brain histopathology.

Models of inflammation, oxidative stress, hyperoxia and hypoxia have demonstrated that magnesium sulfate (MgSO4), a commonly used drug in obstetrics, has neuroprotective potential. In the present study, the effects of MgSO4 treatment on inflammation, oxidative stress and fetal brain histopathology were evaluated in an experimental rat model following sevoflurane (Sv) exposure during the mid-gestational period. Rats were randomly divided into groups: C (control; no injections or anesthesia), Sv (exposure to 2.5% Sv for 2 h), MgSO4 (administered 270 mg/kg MgSO4 intraperitoneally) and Sv + MgSO4 (Sv administered 30 min after MgSO4 injection). Inflammatory and oxidative stress markers were measured in the serum and neurotoxicity was investigated histopathologically in fetal brain tissue. Short-term mid-gestational exposure to a 1.1 minimum alveolar concentration of Sv did not significantly increase the levels of any of the measured biochemical markers, except for TNF-α. Histopathological evaluations demonstrated no findings suggestive of pathological apoptosis, neuroinflammation or oxidative stress-induced cell damage. MgSO4 injection prior to anesthesia caused no significant differences in biochemical or histopathological marker levels compared to the C and Sv groups. The present study indicated that short-term exposure to Sv could potentially be considered a harmless external stimulus to the fetal brain.

The role of cortical structural variance in deep learning-based prediction of fetal brain age.

Background: Deep-learning-based brain age estimation using magnetic resonance imaging data has been proposed to identify abnormalities in brain development and the risk of adverse developmental outcomes in the fetal brain. Although saliency and attention activation maps have been used to understand the contribution of different brain regions in determining brain age, there has been no attempt to explain the influence of shape-related cortical structural features on the variance of predicted fetal brain age. Methods: We examined the association between the predicted brain age difference (PAD: predicted brain age-chronological age) from our convolution neural networks-based model and global and regional cortical structural measures, such as cortical volume, surface area, curvature, gyrification index, and folding depth, using regression analysis. Results: Our results showed that global brain volume and surface area were positively correlated with PAD. Additionally, higher cortical surface curvature and folding depth led to a significant increase in PAD in specific regions, including the perisylvian areas, where dramatic agerelated changes in folding structures were observed in the late second trimester. Furthermore, PAD decreased with disorganized sulcal area patterns, suggesting that the interrelated arrangement and areal patterning of the sulcal folds also significantly affected the prediction of fetal brain age. Conclusion: These results allow us to better understand the variance in deep learning-based fetal brain age and provide insight into the mechanism of the fetal brain age prediction model.

Altered thalamocortical tract trajectory growth with undisrupted thalamic parcellation pattern in human lissencephaly brain at mid-gestational stage.

Proper topographically organized neural connections between the thalamus and the cerebral cortex are mandatory for thalamus function. Thalamocortical (TC) fiber growth begins during the embryonic period and completes by the third trimester of gestation, so that human neonates at birth have a thalamus with a near-facsimile of adult functional parcellation. Whether congenital neocortical anomaly (e.g., lissencephaly) affects TC connection in humans is unknown. Here, via diffusion MRI fiber-tractography analysis of long-term formalin-fixed postmortem fetal brain diagnosed as lissencephaly in comparison with an age-matched normal one, we found similar topological patterns of thalamic subregions and of internal capsule parcellated by TC fibers. However, lissencephaly fetal brain showed white matter structural changes, including fewer/less organized TC fibers and optic radiations, and much less cortical plate invasion by TC fibers - particularly around the shallow central sulcus. Diffusion MRI fiber tractography of normal fetal brains at 15, 23, and 26 gestational weeks (GW) revealed dynamic volumetric change of each parcellated thalamic subregion, suggesting coupled developmental progress of the thalamus with the corresponding cortex. Moreover, from GW23 and GW26 normal fetal brains, TC endings in the cortical plate could be delineated to reflect cumulative progressive TC invasion of cortical plate. By contrast, lissencephaly brain showed a dramatic decrease in TC invasion of the cortical plate. Our study thus shows the feasibility of diffusion MRI fiber tractography in postmortem long-term formalin-fixed fetal brains to disclose the developmental progress of TC tracts coordinating with thalamic and neocortical growth both in normal and lissencephaly fetal brains at mid-gestational stage.

Advances in Fetal Brain Imaging.

Over the last 20 years, there have been remarkable developments in fetal brain MR imaging analysis methods. This article delves into the specifics of structural imaging, diffusion imaging, functional MR imaging, and spectroscopy, highlighting the latest advancements in motion correction, fetal brain development atlases, and the challenges and innovations. Furthermore, this article explores the clinical applications of these advanced imaging techniques in comprehending and diagnosing fetal brain development and abnormalities.

Maternal SARS-CoV-2 impacts fetal placental macrophage programs and placenta-derived microglial models of neurodevelopment.

BACKGROUND: The SARS-CoV-2 virus activates maternal and placental immune responses. Such activation in the setting of other infections during pregnancy is known to impact fetal brain development. The effects of maternal immune activation on neurodevelopment are mediated at least in part by fetal brain microglia. However, microglia are inaccessible for direct analysis, and there are no validated non-invasive surrogate models to evaluate in utero microglial priming and function. We have previously demonstrated shared transcriptional programs between microglia and Hofbauer cells (HBCs, or fetal placental macrophages) in mouse models. METHODS AND RESULTS: We assessed the impact of maternal SARS-CoV-2 on HBCs isolated from 24 term placentas (N = 10 SARS-CoV-2 positive cases, 14 negative controls). Using single-cell RNA-sequencing, we demonstrated that HBC subpopulations exhibit distinct cellular programs, with specific subpopulations differentially impacted by SARS-CoV-2. Assessment of differentially expressed genes implied impaired phagocytosis, a key function of both HBCs and microglia, in some subclusters. Leveraging previously validated models of microglial synaptic pruning, we showed that HBCs isolated from placentas of SARS-CoV-2 positive pregnancies can be transdifferentiated into microglia-like cells (HBC-iMGs), with impaired synaptic pruning behavior compared to HBC models from negative controls. CONCLUSION: These findings suggest that HBCs isolated at birth can be used to create personalized cellular models of offspring microglial programming.

Development of the Fetal Brain Corticocortical Structural Network during the Second-to-Third Trimester Based on Diffusion MRI.

During the second-to-third trimester, the neuronal pathways of the fetal brain experience rapid development, resulting in the complex architecture of the interwired network at birth. While diffusion MRI-based tractography has been employed to study the prenatal development of structural connectivity network (SCN) in preterm neonatal and postmortem fetal brains, the in utero development of SCN in the normal fetal brain remains largely unknown. In this study, we utilized in utero dMRI data from human fetuses of both sexes between 26 and 38 gestational weeks to investigate the developmental trajectories of the fetal brain SCN, focusing on intrahemispheric connections. Our analysis revealed significant increases in global efficiency, mean local efficiency, and clustering coefficient, along with significant decrease in shortest path length, while small-worldness persisted during the studied period, revealing balanced network integration and segregation. Widespread short-ranged connectivity strengthened significantly. The nodal strength developed in a posterior-to-anterior and medial-to-lateral order, reflecting a spatiotemporal gradient in cortical network connectivity development. Moreover, we observed distinct lateralization patterns in the fetal brain SCN. Globally, there was a leftward lateralization in network efficiency, clustering coefficient, and small-worldness. The regional lateralization patterns in most language, motor, and visual-related areas were consistent with prior knowledge, except for Wernicke's area, indicating lateralized brain wiring is an innate property of the human brain starting from the fetal period. Our findings provided a comprehensive view of the development of the fetal brain SCN and its lateralization, as a normative template that may be used to characterize atypical development.

Expression of Dystrophin Dp71 Splice Variants Is Temporally Regulated During Rodent Brain Development.

Dystrophin Dp71 is the major product of the Duchenne muscular dystrophy (DMD) gene in the brain, and its loss in DMD patients and mouse models leads to cognitive impairments. Dp71 is expressed as a range of proteins generated by alternative splicing of exons 71 to 74 and 78, classified in the main Dp71d and Dp71f groups that contain specific C-terminal ends. However, it is unknown whether each isoform has a specific role in distinct cell types, brain regions, and/or stages of brain development. In the present study, we characterized the expression of Dp71 isoforms during fetal (E10.5, E15.5) and postnatal (P1, P7, P14, P21 and P60) mouse and rat brain development. We finely quantified the expression of several Dp71 transcripts by RT-PCR and cloning assays in samples from whole-brain and distinct brain structures. The following Dp71 transcripts were detected: Dp71d, Dp71d∆71, Dp71d∆74, Dp71d∆71,74, Dp71d∆71-74, Dp71f, Dp71f∆71, Dp71f∆74, Dp71f∆71,74, and Dp71fΔ71-74. We found that the Dp71f isoform is the main transcript expressed at E10.5 (> 80%), while its expression is then progressively reduced and replaced by the expression of isoforms of the Dp71d group from E15.5 to postnatal and adult ages. This major finding was confirmed by third-generation nanopore sequencing. In addition, we found that the level of expression of specific Dp71 isoforms varies as a function of postnatal stages and brain structure. Our results suggest that Dp71 isoforms have different and complementary roles during embryonic and postnatal brain development, likely taking part in a variety of maturation processes in distinct cell types.

Impact of maternal immune activation and sex on placental and fetal brain cytokine and gene expression profiles in a preclinical model of neurodevelopmental disorders.

Maternal inflammation during gestation is associated with a later diagnosis of neurodevelopmental disorders including autism spectrum disorder (ASD). However, the specific impact of maternal immune activation (MIA) on placental and fetal brain development remains insufficiently understood. This study aimed to investigate the effects of MIA by analyzing placental and brain tissues obtained from the offspring of pregnant C57BL/6 dams exposed to polyinosinic: polycytidylic acid (poly I: C) on embryonic day 12.5. Cytokine and mRNA content in the placenta and brain tissues were assessed using multiplex cytokine assays and bulk-RNA sequencing on embryonic day 17.5. In the placenta, male MIA offspring exhibited higher levels of GM-CSF, IL-6, TNFα, and LT-α, but there were no differences in female MIA offspring. Furthermore, differentially expressed genes (DEG) in the placental tissues of MIA offspring were found to be enriched in processes related to synaptic vesicles and neuronal development. Placental mRNA from male and female MIA offspring were both enriched in synaptic and neuronal development terms, whereas females were also enriched for terms related to excitatory and inhibitory signaling. In the fetal brain of MIA offspring, increased levels of IL-28B and IL-25 were observed with male MIA offspring and increased levels of LT-α were observed in the female offspring. Notably, we identified few stable MIA fetal brain DEG, with no male specific difference whereas females had DEG related to immune cytokine signaling. Overall, these findings support the hypothesis that MIA contributes to the sex- specific abnormalities observed in ASD, possibly through altered neuron developed from exposure to inflammatory cytokines. Future research should aim to investigate how interactions between the placenta and fetal brain contribute to altered neuronal development in the context of MIA.

Nurturing development: how a mother's nutrition shapes offspring's brain through the gut.

Pregnancy is a transformative period marked by profound physical and emotional changes, with far-reaching consequences for both mother and child. Emerging research has illustrated the pivotal role of a mother's diet during pregnancy in influencing the prenatal gut microbiome and subsequently shaping the neurodevelopment of her offspring. The intricate interplay between maternal gut health, nutrition, and neurodevelopmental outcomes has emerged as a captivating field of investigation within developmental science. Acting as a dynamic bridge between mother and fetus, the maternal gut microbiome, directly and indirectly, impacts the offspring's neurodevelopment through diverse pathways. This comprehensive review delves into a spectrum of studies, clarifying putative mechanisms through which maternal nutrition, by modulating the gut microbiota, orchestrates the early stages of brain development. Drawing insights from animal models and human cohorts, this work underscores the profound implications of maternal gut health for neurodevelopmental trajectories and offers a glimpse into the formulation of targeted interventions able to optimize the health of both mother and offspring. The prospect of tailored dietary recommendations for expectant mothers emerges as a promising and accessible intervention to foster the growth of beneficial gut bacteria, potentially leading to enhanced cognitive outcomes and reduced risks of neurodevelopmental disorders.

Fetal Cerebral Ventriculomegaly: A Narrative Review and Practical Recommendations for Pediatric Neurologists.

Fetal cerebral ventriculomegaly is one of the most common fetal neurological disorders identified prenatally by neuroimaging. The challenges in the evolving landscape of conditions like fetal cerebral ventriculomegaly involve accurate diagnosis and how best to provide prenatal counseling regarding prognosis as well as postnatal management and care of the infant. The purpose of this narrative review is to discuss the literature on fetal ventriculomegaly, including postnatal management and neurodevelopmental outcome, and to provide practice recommendations for pediatric neurologists.

High-resolution anatomical imaging of the fetal brain with a reduced field of view using outer volume suppression.

PURPOSE: To achieve high-resolution fetal brain anatomical imaging without introducing image artifacts by reducing the FOV, and to demonstrate improved image quality compared to conventional full-FOV fetal brain imaging. METHODS: Reduced FOV was achieved by applying outer volume suppression (OVS) pulses immediately prior to standard single-shot fast spin echo (SSFSE) imaging. In the OVS preparation, a saturation RF pulse followed by a gradient spoiler was repeated three times with optimized flip-angle weightings and a variable spoiler scheme to enhance signal suppression. Simulations and phantom and in-vivo experiments were performed to evaluate OVS performance. In-vivo high-resolution SSFSE images acquired using the proposed approach were compared with conventional and high-resolution SSFSE images with a full FOV, using image quality scores assessed by neuroradiologists and calculated image metrics. RESULTS: Excellent signal suppression in the saturation bands was confirmed in phantom and in-vivo experiments. High-resolution SSFSE images with a reduced FOV acquired using OVS demonstrated the improved depiction of brain structures without significant motion and blurring artifacts. The proposed method showed the highest image quality scores in the criteria of sharpness, contrast, and artifact and was selected as the best method based on overall image quality. The calculated image sharpness and tissue contrast ratio were also the highest with the proposed method. CONCLUSION: High-resolution fetal brain anatomical images acquired using a reduced FOV with OVS demonstrated improved image quality both qualitatively and quantitatively, suggesting the potential for enhanced diagnostic accuracy in detecting fetal brain abnormalities in utero.