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The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging (fMRI) data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction, and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st to 38th gestational weeks (GWs) with a network-based statistical inference approach. The overall connectivity network, short range, and interhemispheric connections showed sigmoid expansion curve peaking at the 26-29 GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW), temporal (peak: 26 GW), frontal (peak: 26.4 GW), and parietal expansion (peak: 27.5 GW). We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macro connectivity.

Diffusion-weighted imaging (DWI) is a technique used to probe the random microscopic motion of water protons in living tissue, represented by a parameter measurement of apparent diffusion coefficient (ADC) values. This study aimed to measure the ADC values of various fetal organs and placenta using 3T at various gestational ages. This was a prospective observational study. A total of 103 singleton pregnancies from 20 to 38 weeks of gestational age were included. Diffusion-weighted imaging was performed in the axial plane from the fetal head to the trunk with the following parameters: TR: 2000–2500 ms; TE: 88 ms; FOV: 250 mm; 256 matrix; slice thickness: 4 mm with a 0 mm gap; acquisition time: 1 min, 18 s. Diffusion gradient values were b = 0 and b = 700 s/mm 2 . ADC was measured in fetal brain regions (frontal white matter, occipital white matter, centrum semiovale, pons, thalamus, cerebellum, and fetal organs (lungs, kidney, and placenta). ANOVA was used to calculate the mean ADC values. Karl Pearson’s coefficient of correlation was used to evaluate the correlation between ADC values and increasing gestational age. The mean ADC values of brain regions were: frontal white matter (1.64 ± 0.08 × 10 − 3 mm 2 /s, F-39.10,p-<0.001), occipital white matter (1.64 ± 0.06 × 10 − 3 mm 2 /s, F-26.14, p-<0.001), centrum semiovale (1.62 ± 0.03 × 10 − 3  mm 2 /s, F-49.88,p-<0.001, pons (1.23 ± 0.09 × 10 − 3 mm 2 /s F-9.14,p-<0.001) ), Thalamus (1.21 ± 0.07 × 10 − 3 mm 2 /s, F-13.54,p-<0.001) and cerebellum (1.36 ± 0.10 × 10 − 3 mm 2 /s, F-4.19,p-<0.001). The mean ADC values of fetal organs were lung (1.92 ± 0.15 × 10 − 3 mm 2 /s, F-28.24, p-<0.001), kidney (1.34 ± 0.11 × 10 − 3 mm 2 /s, F-1.05, p- 0.37) and placenta (1.94 ± 0.11 × 10 − 3 mm 2 /s, F-160.33, p-<0.001). White-matter regions showed a significant positive correlation with increasing gestational age. Statistically, a negative correlation was observed between increasing gestational age and ADC measurements obtained in the thalamus, cerebellum, pons, and kidney. This will be one of the first few studies to provide the ADC values of the fetal brain and fetal organs using 3T MRI. The current study shows that diffusion-weighted MRI can offer a promising technique to evaluate the structural development of fetal organs and can potentially lead to a biomarker for predicting the functionality of the fetal organs in abnormalities.

Fetal brain MRI has become an important tool for in utero assessment of brain development and disorders. However, quantitative analysis of fetal brain MRI remains difficult, partially due to the limited tools for automated preprocessing and the lack of normative brain templates. In this paper, we proposed an automated pipeline for fetal brain extraction, super-resolution reconstruction, and fetal brain atlasing to quantitatively map in utero fetal brain development during mid-to-late gestation in a Chinese population. First, we designed a U-net convolutional neural network for automated fetal brain extraction, which achieved an average accuracy of 97%. We then generated a developing fetal brain atlas, using an iterative linear and nonlinear registration approach. Based on the 4D spatiotemporal atlas, we quantified the morphological development of the fetal brain between 23 and 36 weeks of gestation. The proposed pipeline enabled the fully automated volumetric reconstruction for clinically available fetal brain MRI data, and the 4D fetal brain atlas provided normative templates for the quantitative characterization of fetal brain development, especially in the Chinese population.

Objective To characterize fetal brain MRI features in monochorionic twin pregnancies based on radiomics; and to investigate the correlation between these radiomic features and subsequent neurodevelopmental outcomes. Methods This retrospective cohort study analyzed 26 monochorionic twin pregnancies (36 fetus included) who underwent fetal brain MRI (Siemens Magnetom Skyra 3.0 T or Philips Ingenia 3.0 T). Neurodevelopmental assessment categorized 20 monochorionic twins into the good neurodevelopmental group and 16 into the moderate neurodevelopmental group. MRI textural features of different brain areas were quantified by composite radiomics score and individual radiomics-feature score, and the correlation between these scores and neurodevelopmental outcomes during postnatal follow-up was analyzed. Results Quantitative radiomic analysis revealed significantly higher radiomics score in the good neurodevelopmental group for the following regions: periventricular white matter (PWM), frontal, parietal and temporal lobes (all P  < 0.05). Four specific radiomics-feature score demonstrated significant group differences in these regions: Gray Level Dependence Matrix (GLDM) in PWM, first-order statistical feature in frontal lobe, Gray Level Size Zone Matrix (GLSZM) in parietal lobe, and GLSZM in temporal lobe. For predictive modeling, we identified five high-discriminatory features representing distinct feature categories: shape features (Elongation), first-order statistical features (Kurtosis), and texture features (GLCM: Cluster Shade, GLRLM: Long Run High Gray Level Emphasis, GLSZM: Size Zone Non Uniformity). The logistic regression model with nested cross-validation incorporating these features achieved excellent predictive performance for neurodevelopmental outcomes [Mean of AUC = 0.8900 (± 0.1133)]. Conclusions Radiomics scores were higher in good neurodevelopmental fetuses, and the selected radiomics features may be helpful for predicting the neurodevelopmental outcomes of monochorionic twins.

Chorioamnionitis (CAM) is an increasingly common disease affecting pregnant women which derives from bacterial vaginosis. In different clinical cases, it has been shown that CAM can cause multiple risk factors for fetal brain damage, such as infection, and intra-uterine asphyxia. However, the molecular mechanism remains unknown. In this study, we established a novel CAM mouse model by exposing pregnant mice to a combination of three risk factors: vaginal lipopolysaccharides (LPS), amniotic LPS, and ischemic reperfusion. We found amniotic LPS caused Parkinson’s disease-like fetal brain damage, in a dose and time-dependent manner. Moreover, the mechanism of this fetal brain damage is apoptosis induced by amniotic LPS but it was inhibited by being pretreated with a vaginal LPS challenge before amniotic LPS injection. In contrast, amniotic LPS with continuous ischemic reperfusion caused a higher level of apoptotic cell death than amniotic LPS alone. In particular, a potential neuroprotective biomarker phosphorylation (p)-CREB (ser133) appeared in only vaginal LPS preconditioned before amniotic LPS, whereas ischemic reperfusion triggered IKK phosphorylation after amniotic LPS. Despite the need for many future investigations, this study also discussed a developed understanding of the molecular mechanism of how these phenotypes occurred.

ABSTRACT Purpose The impact of ventriculomegaly (VM) on cortical development and brain functionality has been extensively explored in existing literature. VM has been associated with higher risks of attention‐deficit and hyperactivity disorders, as well as cognitive, language, and behavior deficits. Some studies have also shown a relationship between VM and cortical overgrowth, along with reduced cortical folding, both in fetuses and neonates. However, there is a lack of longitudinal studies that study this relationship from fetuses to neonates. Method We used a longitudinal dataset of 30 subjects (15 healthy controls and 15 subjects diagnosed with isolated non‐severe VM (INSVM)) with structural MRI acquired in and ex utero for each subject. We focused on the impact of fetal INSVM on cortical development from a longitudinal perspective, from the fetal to the neonatal stage. Particularly, we examined the relationship between ventricular enlargement and both volumetric features and a multifaceted set of cortical folding measures, including local gyrification, sulcal depth, curvature, and cortical thickness. Findings Our results show significant effects of isolated non‐severe VM (INSVM) compared to healthy controls, with reduced cortical thickness in specific brain regions such as the occipital, parietal, and frontal lobes. Conclusion These findings align with existing literature, confirming the presence of alterations in cortical growth and folding in subjects with isolated non‐severe VM (INSVM) from the fetal to neonatal stage compared to controls. This study investigates the longitudinal impact of isolated non‐severe ventriculomegaly (INSVM) on cortical development from fetal to neonatal stages using MRI data from 30 subjects (15 with VM and 15 healthy controls). The results indicate that VM subjects exhibit larger cortical volume, reduced cortical thickness and altered local gyrification over time, particularly in the occipital, parietal, and frontal lobes, confirming cortical overgrowth and delayed cortical folding observed in cross‐sectional studies.

Objectives: We used magnetic resonance spectroscopy (MRS) to evaluate brain metabolic differences in small fetuses near term as compared to appropriate for gestational age (AGA) fetuses. Study Design: 71 term small fetuses (estimated fetal weight <10th centile for gestational age with normal umbilical artery Doppler sonography) were subclassified as late intrauterine growth restriction (IUGR) (n = 50) or small for gestational age (SGA) (n = 21), and compared with 65 AGA fetuses. IUGR was defined by either abnormal middle cerebral artery, abnormal uterine artery Doppler sonography or estimated fetal weight <3rd centile. All participants underwent brain magnetic resonance imaging at 37 weeks of gestation, and single-voxel magnetic resonance spectra were obtained from the frontal lobe on a 3-tesla scanner. N-acetylaspartate (NAA)/choline (Cho), NAA/creatine (Cr) and Cho/Cr ratios were calculated and compared between cases and controls. The association of the metabolic ratios with the study groups was tested. Results: After MRS processing and applying quality control criteria, 31 spectra from late-onset IUGR, 11 from SGA and 30 from AGA fetuses were selected for further analysis. Both SGA and late-onset IUGR fetuses showed significantly reduced NAA/Cho levels when compared to AGA fetuses. This decrease followed a linear trend across the three clinical groups that were considered. Conclusions: Both SGA and late-onset IUGR fetuses showed differences in MRS brain metabolic ratios. The findings suggest that despite near-normal perinatal outcomes, SGA fetuses are not constitutionally small and may represent a form of growth disorder that needs to be clarified.

MRI-based brain age prediction has been widely used to characterize normal brain development, and deviations from the typical developmental trajectory are indications of brain abnormalities. Age prediction of the fetal brain remains unexplored, although it can be of broad interest to prenatal examination given the limited diagnostic tools available for assessment of the fetal brain. In this work, we built an attention-based deep residual network based on routine clinical T2-weighted MR images of 659 fetal brains, which achieved an overall mean absolute error of 0.767 weeks and R2 of 0.920 in fetal brain age prediction. The predictive uncertainty and estimation confidence were simultaneously quantified from the network as markers for detecting fetal brain anomalies using an ensemble method. The novel markers overcame the limitations in conventional brain age estimation and demonstrated promising diagnostic power in differentiating several types of fetal abnormalities, including small head circumference, malformations and ventriculomegaly with the area under the curve of 0.90, 0.90 and 0.67, respectively. In addition, attention maps were derived from the network, which revealed regional features that contributed to fetal age estimation at each gestational stage. The proposed attention-based deep ensembles demonstrated superior performance in fetal brain age estimation and fetal anomaly detection, which has the potential to be translated to prenatal diagnosis in clinical practice.

Given the tremendous advances in the last five years in the understanding of acquired neonatal brain injury and in the care of affected newborn infants, this book provides a timely review for the practising neurologist, neonatologist and pediatrician.The editors take a pragmatic approach, focusing on specific populations encountered regularly by the clinician.They begin by addressing aspects of fetal neurology and the interpretation of fetal imaging studies. They then follow a 'bench to bedside' approach to acquired brain injury in the preterm and term newborn infant in the next chapters. The contributors, all internationally recognized clinician scientists, provide the clinician reader with a state-of-the art review in their area of expertise. The final section of the book address special populations and concerns, areas that are largely overlooked in existing neurology textbooks. Each of these areas has seen considerable advances in the last five years and is of increasing relevance to the neurologist and neonatologist clinician.The comprehensive nature of each section (from basic science to acute clinical care to outcomes) should appeal broadly to scientists and allied health professionals working in neonatal neurology.

Maternal infection and inflammation during pregnancy are associated with neurodevelopmental disorders in offspring, but little is understood about the molecular mechanisms underlying this epidemiologic phenomenon. Here, we leveraged single-cell RNA sequencing to profile transcriptional changes in the mouse fetal brain in response to maternal immune activation (MIA) and identified perturbations in cellular pathways associated with mRNA translation, ribosome biogenesis and stress signaling. We found that MIA activates the integrated stress response (ISR) in male, but not female, MIA offspring in an interleukin-17a-dependent manner, which reduced global mRNA translation and altered nascent proteome synthesis. Moreover, blockade of ISR activation prevented the behavioral abnormalities as well as increased cortical neural activity in MIA male offspring. Our data suggest that sex-specific activation of the ISR leads to maternal inflammation-associated neurodevelopmental disorders. This paper shows that maternal immune activation in mice induces changes in the mRNA translation machinery in the fetal brain and activates the integrated stress response in male fetuses, which mediates neurobehavioral abnormalities.