Brain Development in Fetuses of Mothers with Diabetes: A Case-Control MR Imaging Study

Gestational Diabetes Mellitus and its Effects on the Developing Cerebellum: A Narrative Review on Experimental Studies

Diabetes mellitus during pregnancy is a common complication of gestation, but its effects on the offspring's development are poorly understood. Recently, some studies reported that gestational diabetes mellitus (GDM) impairs cerebellar development, and some genetic alterations have been described as consequences. Cerebellum, one of the hindbrain derived structures in the posterior cranial fossa, plays a crucial role in cognition and behavioral functions. In recent years, some surveys stated that gestational diabetes has adverse effects on the fetus's cerebellum. Disruption of cerebellar cortex morphogenesis, reduce the volume of the cerebellum, reduce the thickness of cerebellar cortex layers, and its neuronal cells and effects on the expression of synaptophysin, insulin, and insulin-like growth factor -1 receptors are some of the maternal diabetes effects on developing cerebellum. On other hand, GDM, as a neurotoxic agent, impaired cerebellar development and could be a cause for the behavioral, functional, and structural anomalies observed in pups of diabetic mothers. Based on the literature review, most studies have pointed out that administering insulin in patients with GDM decreased the cellular and molecular alterations that induced by GDM in the developing cerebellum. Undoubtedly, screening strategies for all pregnant women are necessary.

Maternal exposure to polystyrene nanoplastics alters fetal brain metabolism in mice

INTRODUCTION

Plastics used in everyday materials accumulate as waste in the environment and degrade over time. The impacts of the resulting particulate micro- and nanoplastics on human health remain largely unknown. In pregnant mice, we recently demonstrated that exposure to nanoplastics throughout gestation and during lactation resulted in changes in brain structure detected on MRI. One possible explanation for this abnormal postnatal brain development is altered fetal brain metabolism.

OBJECTIVES

To determine the effect of maternal exposure to nanoplastics on fetal brain metabolism.

METHODS

Healthy pregnant CD-1 mice were exposed to 50 nm polystyrene nanoplastics at a concentration of 106 ng/L through drinking water during gestation. Fetal brain samples were collected at embryonic day 17.5 (n = 18-21 per group per sex) and snap-frozen in liquid nitrogen. Magic angle spinning nuclear magnetic resonance was used to determine metabolite profiles and their relative concentrations in the fetal brain.

RESULTS

The relative concentrations of gamma-aminobutyric acid (GABA), creatine and glucose were found to decrease by 40%, 21% and 30% respectively following maternal nanoplastic exposure when compared to the controls (p < 0.05). The change in relative concentration of asparagine with nanoplastic exposure was dependent on fetal sex (p < 0.005).

CONCLUSION

Maternal exposure to polystyrene nanoplastics caused abnormal fetal brain metabolism in mice. The present study demonstrates the potential impacts of nanoplastic exposure during fetal development and motivates further studies to evaluate the risk to human pregnancies.

Does diabetes mellitus affect the development of fetal brain structures and spaces including corpus callosum, subarachnoid space, insula, and parieto-occipital fissure?

PURPOSE

We investigated the impact of pregestational and gestational diabetes mellitus (PGDM and GDM) on the development of fetal intracranial structures and spaces.

METHODS

This prospective cross-sectional study involved singleton pregnancies between 20 and 32 weeks of gestation. The study comprised a control group (n = 65) of healthy pregnant women without diabetes mellitus (DM); a PGDM group (n = 43) of pregnant women having type 2 DM in a controlled diabetic state; and a GDM group (n = 26) of pregnant women with GDM diagnosed with 2-h 75-g oral glucose tolerance test and received intervention to reduce the diabetic impact on fetus. During neurosonographic evaluation, the simultaneous measurements of corpus callosum (CC) width and depth in the midsagittal image; and lateral craniocortical and posterior craniocortical widths of the subarachnoid space and insular and parieto-occipital fissure depths in the axial image were performed. Before statistical analysis, these values were carefully adjusted for the occipitofrontal diameter.

RESULTS

The DM groups displayed substantially higher frequencies of family history of DM and obstetric history of GDM compared to the control group (p < 0.05). Regarding the neurosonographic parameters, the CC length and insular and parieto-occipital fissure depths were significantly increased in the GDM group but not in the PGDM group (p < 0.05). No significant difference was found among the study groups regarding other neurosonographic parameters (p > 0.05).

CONCLUSION

The results of neurosonographical evaluation of fetal brain structures and spaces reveal that diabetic impact may not be seen in the presence of PGDM, especially in pregnant women receiving prenatal interventions to reduce or avoid diabetic adverse effects on fetal brain development. The effect of GDM on neurosonographically assessed fetal brain development should be evaluated in further studies with subjects matched for gestational weeks and antenatal care conditions.

Microstructural Brain Development and Neurodevelopmental Outcome of Very Preterm Infants of Mothers with Gestational Diabetes Mellitus

INTRODUCTION

There are data linking gestational diabetes mellitus (GDM) with adverse neurodevelopmental outcome in the offspring. We investigated the effect of GDM on microstructural brain development and neurodevelopmental outcome of very preterm infants.

MATERIALS AND METHODS

Preterm infants <32 gestational weeks of mothers with GDM obtained cerebral magnetic resonance imaging (MRI) including diffusion-tensor imaging at term-equivalent age. For every infant, two gestational age-, sex-, and MRI scanner type-matched controls were included. Brain injury was assessed and fractional anisotropy (FA) and apparent diffusion coefficient (ADC) measured in 14 defined cerebral regions. Neurodevelopmental outcome was quantified at the corrected age of 24 months using the Bayley Scales of Infant Development.

RESULTS

We included 47 infants of mothers with GDM and 94 controls. There were no differences in neonatal morbidity between the groups, nor in any type of brain injury. The GDM group showed significantly higher FA values in the centrum semiovale, the posterior limb of the internal capsule and the pons bilaterally, in the corpus callosum and the right occipital white matter, as well as lower ADC values in the right centrum semiovale, the right occipital white matter and the corpus callosum. Neurodevelopmental outcome did not differ between the groups.

CONCLUSION

We found no impairment of brain development in GDM-exposed infants compared to matched controls, but differences in white matter microstructure in specific regions indicating an enhanced maturation. However, neurodevelopmental outcome was equal in both groups. Further studies are needed to better understand brain maturation in preterm infants exposed to GDM.

Development of Gestational Age-Based Fetal Brain and Intracranial Volume Reference Norms Using Deep Learning

BACKGROUND AND PURPOSE

Fetal brain MR imaging interpretations are subjective and require subspecialty expertise. We aimed to develop a deep learning algorithm for automatically measuring intracranial and brain volumes of fetal brain MRIs across gestational ages.

MATERIALS AND METHODS

This retrospective study included 246 patients with singleton pregnancies at 19-38 weeks gestation. A 3D U-Net was trained to segment the intracranial contents of 2D fetal brain MRIs in the axial, coronal, and sagittal planes. An additional 3D U-Net was trained to segment the brain from the output of the first model. Models were tested on MRIs of 10 patients (28 planes) via Dice coefficients and volume comparison with manual reference segmentations. Trained U-Nets were applied to 200 additional MRIs to develop normative reference intracranial and brain volumes across gestational ages and then to 9 pathologic fetal brains.

RESULTS

Fetal intracranial and brain compartments were automatically segmented in a mean of 6.8 (SD, 1.2) seconds with median Dices score of 0.95 and 0.90, respectively (interquartile ranges, 0.91-0.96/0.89-0.91) on the test set. Correlation with manual volume measurements was high (Pearson r = 0.996, P < .001). Normative samples of intracranial and brain volumes across gestational ages were developed. Eight of 9 pathologic fetal intracranial volumes were automatically predicted to be >2 SDs from this age-specific reference mean. There were no effects of fetal sex, maternal diabetes, or maternal age on intracranial or brain volumes across gestational ages.

CONCLUSIONS

Deep learning techniques can quickly and accurately quantify intracranial and brain volumes on clinical fetal brain MRIs and identify abnormal volumes on the basis of a normative reference standard.

Harnessing the Power of Advanced Fetal Neuroimaging to Understand In Utero Footprints for Later Neuropsychiatric Disorders

Adverse intrauterine events may profoundly impact fetal risk for future adult diseases. The mechanisms underlying this increased vulnerability are complex and remain poorly understood. Contemporary advances in fetal magnetic resonance imaging (MRI) have provided clinicians and scientists with unprecedented access to in vivo human fetal brain development to begin to identify emerging endophenotypes of neuropsychiatric disorders such as autism spectrum disorder, attention-deficit/hyperactivity disorder, and schizophrenia. In this review, we discuss salient findings of normal fetal neurodevelopment from studies using advanced, multimodal MRI that have provided unparalleled characterization of in utero prenatal brain morphology, metabolism, microstructure, and functional connectivity. We appraise the clinical utility of these normative data in identifying high-risk fetuses before birth. We highlight available studies that have investigated the predictive validity of advanced prenatal brain MRI findings and long-term neurodevelopmental outcomes. We then discuss how ex utero quantitative MRI findings can inform in utero investigations toward the pursuit of early biomarkers of risk. Lastly, we explore future opportunities to advance our understanding of the prenatal origins of neuropsychiatric disorders using precision fetal imaging.

Adverse Prenatal Exposures and Fetal Brain Development: Insights From Advanced Fetal Magnetic Resonance Imaging

Converging evidence from clinical and preclinical studies suggests that fetal vulnerability to adverse prenatal exposures increases the risk for neuropsychiatric diseases such as autism spectrum disorder, schizophrenia, and depression. Recent advances in fetal magnetic resonance imaging have allowed us to characterize typical fetal brain growth trajectories in vivo and to interrogate structural and functional alterations associated with intrauterine exposures, such as maternal stress, environmental toxins, drugs, and obesity. Here, we review proposed mechanisms for how prenatal influences disrupt neurodevelopment, including the role played by maternal and fetal inflammatory responses. We summarize insights from magnetic resonance imaging research in fetuses, highlight recent discoveries in normative fetal development using quantitative magnetic resonance imaging techniques (i.e., three-dimensional volumetry, proton magnetic resonance spectroscopy, placental diffusion imaging, and functional imaging), and discuss how baseline trajectories are shaped by prenatal exposures.

How prenatal exposures shape the infant brain: Insights from infant neuroimaging studies

Brain development during the prenatal period is rapid and unparalleled by any other time during development. Biological systems undergoing rapid development are at higher risk for disorganizing influences. Therefore, certain prenatal exposures impact brain development, increasing risk for negative neurodevelopmental outcome. While prenatal exposures have been associated with cognitive and behavioral outcomes later in life, the underlying macroscopic brain pathways remain unclear. Here, we review magnetic resonance imaging (MRI) studies investigating the association between prenatal exposures and infant brain development focusing on prenatal exposures via maternal physical health factors, maternal mental health factors, and maternal drug and medication use. Further, we discuss the need for studies to consider multiple prenatal exposures in parallel and suggest future directions for this body of research.

Brain Development in Infants of Mothers With Gestational Diabetes Mellitus: A Diffusion Tensor Imaging Study

OBJECTIVE

The objective of this study was to investigate clinical neurocognitive performance and microstructural white matter (WM) alterations in infants of mothers with gestational diabetes mellitus (GDM) using diffusion tensor imaging.

MATERIALS AND METHODS

Infants (corrected gestational age, 33.42-36.00 weeks) of mothers with GDM (n = 31) and gestational age- and sex-matched unexposed controls (n = 31) accomplished 3-T diffusion tensor imaging scans and neurocognitive tests. Diffusion tensor imaging measures, mainly referring to fractional anisotropy (FA) values, were compared between 2 groups, and within-group analysis of correlation between FA values and neurocognitive testing outcomes in GDM-exposed infants was conducted subsequently.

RESULTS

Fractional anisotropy was significantly decreased in the splenium of corpus callosum, posterior limb of internal capsule, thalamus in infants of mothers with GDM when compared with controls (P < 0.05), reflecting microstructural WM abnormalities in the GDM group. Decreased FA was associated with worse neurocognitive performance in the exposed group (P < 0.05).

CONCLUSIONS

Individuals of mothers with GDM showed microstructural WM abnormalities in different brain regions, which were significantly related to worse neurocognitive performance. This might reveal that GDM directly insults the brain development of the offspring.

Fetal and neonatal neuroimaging

Magnetic resonance imaging (MRI) can provide detail of the soft tissues of the fetal and neonatal brain that cannot be obtained by any other imaging modality. Conventional T1 and T2 weighted sequences provide anatomic detail of the normally developing brain and can demonstrate lesions, including those associated with preterm birth, hypoxic ischemic encephalopathy, perinatal arterial stroke, infections, and congenital malformations. Specialized imaging techniques can be used to assess cerebral vasculature (magnetic resonance angiography and venography), cerebral metabolism (magnetic resonance spectroscopy), cerebral perfusion (arterial spin labeling), and function (functional MRI). A wealth of quantitative tools, most of which were originally developed for the adult brain, can be applied to study the developing brain in utero and postnatally including measures of tissue microstructure obtained from diffusion MRI, morphometric studies to measure whole brain and regional tissue volumes, and automated approaches to study cortical folding. In this chapter, we aim to describe different imaging approaches for the fetal and neonatal brain, and to discuss their use in a range of clinical applications.