Assessing the embryotoxicity and teratogenicity of various substances and processes is crucial due to their complexity and resource intensity. The chicken embryo (CE) serves an ideal model for simulating the first months of mammalian embryonic development. This makes the CE a reliable model for testing teratogenic effects, particularly in relation to the nervous system (NS), which experiences developmental abnormalities second in frequency only to cardiovascular teratogenic disorders. Microcomputed tomography (μCT) is a promising method for studying these processes. The advantages of μCT include relatively high research speed, diagnostic accuracy, high resolution and the ability to visualize the entire internal 3D structure of an object while preserving for other types of research. At the same time, there are practically no available databases of normative μCT data, both qualitative and quantitative, which would act as a starting point for screening detection of abnormalities in the development of the NS. In this study, we present a simple method for obtaining very detailed quantitative sets of 2D and 3D μCT data of NS structures of the CE (Gallus Gallus domesticus) at HH22-HH41 embryonic stages with contrasting by 1% phosphotungstic acid. The results of μCT demonstrate the exact boundaries, high general and differentiated contrast of the main and specific structures of the NS of CE, which are quantitatively and qualitatively similar to results of histological analysis. Calculations of the X-ray density and volume of the main structures of the NS at constant exponential growth are presented. In addition to the increase in linear dimensions, significant changes in the structures of various parts of the brain were identified and visualized during the CE development at HH22 to HH41 embryonic stages. The data presented establish the first methodology for obtaining normative data, including subtle localized differences in the NS in CE embryogenesis. The data obtained open up new opportunities for modern embryology, teratology, pharmacology and toxicology.

Pediatric cerebrovascular diseases have distinct clinical presentations, pathophysiology, and management compared to the adult counterparts. This introductory article discusses the imaging techniques and neurovascular conditions unique to each age group from the fetal stages through childhood, including vascular malformations, arteriopathy, and strokes. The article also underscores the importance of genetic factors and the need for a multidisciplinary approach in the diagnosis and treatment of pediatric neurovascular disorders.

Integrated fetal, neonatal, and pediatric training constitute an interdisciplinary fetal-neonatal neurology (FNN) program. A dynamic neural exposome concept strengthens curriculum content. Trainees participate in mentoring committee selection for guidance during a proposed two-year program. Prenatal to postnatal clinical learning re-enforces early toxic stressor interplay that influences gene-environment interactions. Maternal-placental-fetal triad, neonatal, or childhood diseases require diagnostic and therapeutic decisions during the first 1,000 days when 80 % of neural connections contribute to life-course phenotypic expression. Pediatric follow-up through 3 years adjusts to gestational ages of preterm survivors. Cumulative reproductive, pregnancy, pediatric and adult exposome effects require educational experiences that emphasize a principle-to-practice approach to a brain capital strategy across the lifespan. More rigorous training during fetal, neonatal, and pediatric rotations will be offered to full time trainees. Adult neurology residents, medical students, and trainees from diverse disciplines will learn essential topics during time-limited rotations. Curriculum content will require periodic re-assessments using educational science standards that maintain competence while promoting creative and collaborative problem-solving. Continued career-long learning by FNN graduates will strengthen shared healthcare decisions by all stakeholders. Recognition of adaptive or maladaptive neuroplasticity mechanisms requires analytic skills that identify phenotypes associated with disease pathways. Developmental origins and life-course concepts emphasize brain health across the developmental-aging continuum, applicable to interdisciplinary research collaborations. Social determinants of health recognize diversity, equity, and inclusion priorities with each neurological intervention, particularly for those challenged with disparities. Diagnostic and therapeutic strategies must address resource challenges particularly throughout the Global South to effectively lower the worldwide burden of neurologic disease. Sustainable development goals proposed by the World Health Organization offer universally applicable guidelines in response to ongoing global and regional polycrises. Gender, race, ethnicity, and socio-economic equality promote effective preventive, rescue and reparative neuroprotective interventions. Global synergistic efforts can be enhanced by establishing leadership within academic teaching hubs in FNN training to assist with structure and guidance for smaller healthcare facilities in each community that will improve practice, education and research objectives. Reduced mortality with an improved quality of life must prioritize maternal-pediatric health and well-being to sustain brain health across each lifespan with transgenerational benefits.

Determine the incremental diagnostic yield of prenatal exome sequencing (pES) over chromosome microarray (CMA) or G-banding karyotype in fetuses with central nervous system (CNS) abnormalities.

Data were collected via electronic searches from January 2010 to April 2022 in MEDLINE, Cochrane, Web of Science and EMBASE. The NHS England prenatal exome cohort was also included. Incremental yield was calculated as a pooled value using a random-effects model.

Thirty studies were included (n = 1583 cases). The incremental yield with pES for any CNS anomaly was 32% [95%CI 27%-36%; I2 = 72%]. Subgroup analysis revealed apparent incremental yields in; (a) isolated CNS anomalies; 27% [95%CI 19%-34%; I2 = 74%]; (b) single CNS anomaly; 16% [95% CI 10%-23%; I2 = 41%]; (c) more than one CNS anomaly; 31% [95% Cl 21%-40%; I2 = 56%]; and (d) the anatomical subtype with the most optimal yield was Type 1 malformation of cortical development, related to abnormal cell proliferation or apoptosis, incorporating microcephalies, megalencephalies and dysplasia; 40% (22%-57%; I2 = 68%). The commonest syndromes in isolated cases were Lissencephaly 3 and X-linked hydrocephalus.

Prenatal exome sequencing provides a high incremental diagnostic yield in fetuses with CNS abnormalities with optimal yields in cases with multiple CNS anomalies, particularly those affecting the midline, posterior fossa and cortex.

Interdisciplinary fetal-neonatal neurology (FNN) training considers a woman's reproductive and pregnancy health histories when assessing the "four great neonatal neurological syndromes". This maternal-child dyad exemplifies the symptomatic neonatal minority, compared with the silent majority of healthy children who experience preclinical diseases with variable expressions over the first 1000 days. Healthy maternal reports with reassuring fetal surveillance testing preceded signs of fetal distress during parturition. An encephalopathic neonate with seizures later exhibited childhood autistic spectrum behaviors and intractable epilepsy correlated with identified genetic biomarkers. A systems biology approach to etiopathogenesis guides the diagnostic process to interpret phenotypic form and function. Evolving gene-environment interactions expressed by changing phenotypes reflect a dynamic neural exposome influenced by reproductive and pregnancy health. This strategy considers critical/sensitive periods of neuroplasticity beyond two years of life to encompass childhood and adolescence. Career-long FNN experiences reenforce earlier training to strengthen the cognitive process and minimize cognitive biases when assessing children or adults. Prioritizing social determinants of healthcare for persons with neurologic disorders will help mitigate the global burden of brain diseases for all women and children.

Fetal-neonatal neurologists (FNNs) consider diagnostic, therapeutic, and prognostic decisions strengthened by interdisciplinary collaborations. Bio-social perspectives of the woman's health influence evaluations of maternal-placental-fetal (MPF) triad, neonate, and child. A dual cognitive process integrates "fast thinking-slow thinking" to reach shared decisions that minimize bias and maintain trust. Assessing the science of uncertainty with uncertainties in science improves diagnostic choices across the developmental-aging continuum. Three case vignettes highlight challenges that illustrate this approach. The first maternal-fetal dyad involved a woman who had been recommended to terminate her pregnancy based on an incorrect diagnosis of an encephalocele. A meningocele was subsequently identified when she sought a second opinion with normal outcome for her child. The second vignette involved two pregnancies during which fetal cardiac rhabdomyoma was identified, suggesting tuberous sclerosis complex (TSC). One woman sought an out-of-state termination without confirmation using fetal brain MRI or postmortem examination. The second woman requested pregnancy care with postnatal evaluations. Her adult child experiences challenges associated with TSC sequelae. The third vignette involved a prenatal diagnosis of an open neural tube defect with arthrogryposis multiplex congenita. The family requested prenatal surgical closure of the defect at another institution at their personal expense despite receiving a grave prognosis. The subsequent Management of Myelomeningocele Study (MOMS) would not have recommended this procedure. Their adult child requires medical care for global developmental delay, intractable epilepsy, and autism. These three evaluations involved uncertainties requiring shared clinical decisions among all stakeholders. Falsely negative or misleading positive interpretation of results reduced chances for optimal outcomes. FNN diagnostic skills require an understanding of dynamic gene-environment interactions affecting reproductive followed by pregnancy exposomes that influence the MPF triad health with fetal neuroplasticity consequences. Toxic stressor interplay can impair the neural exposome, expressed as anomalous and/or destructive fetal brain lesions. Functional improvements or permanent sequelae may be expressed across the lifespan. Equitable and compassionate healthcare for women and families require shared decisions that preserve pregnancy health, guided by person-specific racial-ethnic, religious, and bio-social perspectives. Applying developmental origins theory to neurologic principles and practice supports a brain health capital strategy for all persons across each generation.

The ultrasound scan represents the first tool that obstetricians use in fetal evaluation, but sometimes, it can be limited by mobility or fetal position, excessive thickness of the maternal abdominal wall, or the presence of post-surgical scars on the maternal abdominal wall. Artificial intelligence (AI) has already been effectively used to measure biometric parameters, automatically recognize standard planes of fetal ultrasound evaluation, and for disease diagnosis, which helps conventional imaging methods. The usage of information, ultrasound scan images, and a machine learning program create an algorithm capable of assisting healthcare providers by reducing the workload, reducing the duration of the examination, and increasing the correct diagnosis capability. The recent remarkable expansion in the use of electronic medical records and diagnostic imaging coincides with the enormous success of machine learning algorithms in image identification tasks.

We aim to review the most relevant studies based on deep learning in ultrasound anomaly scan evaluation of the most complex fetal systems (heart and brain), which enclose the most frequent anomalies.

An interdisciplinary fetal-neonatal neurology (FNN) program over the first 1,000 days teaches perspectives of the neural exposome that are applicable across the life span. This curriculum strengthens neonatal neurocritical care, pediatric, and adult neurology training objectives. Teaching at maternal-pediatric hospital centers optimally merges reproductive, pregnancy, and pediatric approaches to healthcare. Phenotype-genotype expressions of health or disease pathways represent a dynamic neural exposome over developmental time. The science of uncertainty applied to FNN training re-enforces the importance of shared clinical decisions that minimize bias and reduce cognitive errors. Trainees select mentoring committee participants that will maximize their learning experiences. Standardized questions and oral presentations monitor educational progress. Master or doctoral defense preparation and competitive research funding can be goals for specific individuals. FNN principles applied to practice offer an understanding of gene-environment interactions that recognizes the effects of reproductive health on the maternal-placental-fetal triad, neonate, child, and adult. Pre-conception and prenatal adversities potentially diminish life-course brain health. Endogenous and exogenous toxic stressor interplay (TSI) alters the neural exposome through maladaptive developmental neuroplasticity. Developmental disorders and epilepsy are primarily expressed during the first 1,000 days. Communicable and noncommunicable illnesses continue to interact with the neural exposome to express diverse neurologic disorders across the lifespan, particularly during the critical/sensitive time periods of adolescence and reproductive senescence. Anomalous or destructive fetal neuropathologic lesions change clinical expressions across this developmental-aging continuum. An integrated understanding of reproductive, pregnancy, placental, neonatal, childhood, and adult exposome effects offers a life-course perspective of the neural exposome. Exosome research promises improved disease monitoring and drug delivery starting during pregnancy. Developmental origins of health and disease principles applied to FNN practice anticipate neurologic diagnoses with interventions that can benefit successive generations. Addressing health care disparities in the Global South and high-income country medical deserts require constructive dialogue among stakeholders to achieve medical equity. Population health policies require a brain capital strategy that reduces the global burden of neurologic diseases by applying FNN principles and practice. This integrative neurologic care approach will prolong survival with an improved quality of life for persons across the lifespan confronted with neurological disorders.

Intrauterine microcephaly is a complex and lifelong condition that poses significant ethical challenges for clinicians and parents. The prognosis of microcephaly is highly variable and depends on the underlying cause and severity. In addition, microcephaly is often associated with various comorbidities, including intellectual disability, developmental delay, and epilepsy. Ultrasonography (US) is currently the most commonly used imaging modality for detecting microcephaly in the second trimester of pregnancy. However, antenatal brain magnetic resonance imaging (MRI) is increasingly being used as a more sensitive tool to identify structural abnormalities that may suggest a specific diagnosis. In this study, we report a case series of microcephaly diagnosed through the combination of MRI and US.

How to utilize a combination of MRI and US to screen for fetal microcephaly.

Based on the results of US and MRI examinations, patient 1 was found to have other craniocerebral malformations, patient 2 demonstrated macrogyria, and patient 3 exhibited skull irregularities.

The pregnancies of all 3 patients were terminated through the induction of labor by injecting Rivanol into the amniotic cavity.

The 3 patients were discharged after a period of observation.

US is an important tool for diagnosing fetal microcephaly. However, MRI can overcome the limitations of US and detect additional brain structural abnormalities, thereby providing more specific and valuable prenatal diagnostic information. Therefore, combining MRI and US has significant diagnostic value for fetal microcephaly.

Among fetal surgical procedures, neurosurgery stands out due to the number of cases and the possibility of developing new procedures that can be performed in the fetal period. To perform fetal neurosurgical procedures, there is a need for specialized centers that have experts in the diagnosis of fetal pathologies and a highly complex obstetrics service with specialized maternal-fetal teams associated with a pediatric neurosurgery center with expertise in the diverse pathologies of the fetus and the central nervous system that offers multidisciplinary follow-up during postnatal life. Services that do not have these characteristics should refer their patients to these centers to obtain better treatment results. It is essential that the fetal neurosurgical procedure be performed by a pediatric neurosurgeon with extensive experience, as he will be responsible for monitoring these patients in the postnatal period and for several years. The objective of this manuscript is to demonstrate the diagnostic and treatment possibilities, in the fetal period, of some neurosurgical diseases such as hydrocephalus, tumors, occipital encephalocele, and myelomeningocele.

An MRI of the fetus can enhance the identification of perinatal developmental disorders, which improves the accuracy of ultrasound. Manual MRI measurements require training, time, and intra-variability concerns. Pediatric neuroradiologists are also in short supply. Our purpose was developing a deep learning model and pipeline for automatically identifying anatomic landmarks on the pons and vermis in fetal brain MR imaging and suggesting suitable images for measuring the pons and vermis.

We retrospectively used 55 pregnant patients who underwent fetal brain MR imaging with a HASTE protocol. Pediatric neuroradiologists selected them for landmark annotation on sagittal single-shot T2-weighted images, and the clinically reliable method was used as the criterion standard for the measurement of the pons and vermis. A U-Net-based deep learning model was developed to automatically identify fetal brain anatomic landmarks, including the 2 anterior-posterior landmarks of the pons and 2 anterior-posterior and 2 superior-inferior landmarks of the vermis. Four-fold cross-validation was performed to test the accuracy of the model using randomly divided and sorted gestational age-divided data sets. A confidence score of model prediction was generated for each testing case.

Overall, 85% of the testing results showed a ≥90% confidence, with a mean error of <2.22 mm, providing overall better estimation results with fewer errors and higher confidence scores. The anterior and posterior pons and anterior vermis showed better estimation (which means fewer errors in landmark localization) and accuracy and a higher confidence level than other landmarks. We also developed a graphic user interface for clinical use.

This deep learning-facilitated pipeline practically shortens the time spent on selecting good-quality fetal brain images and performing anatomic measurements for radiologists.

The aim of this study was to evaluate B-mode ultrasonography and ARFI elastography of the central nervous system of canine fetuses as complementary methods to predict gestational age, monitor fetal development and establish standards. Ultrasound examinations were performed on 26 English Bulldog bitches at 34, 49 and 60 days of gestation. The circumference (C), area (A) and diameters of the short (D1) and long (D2) axis of the two cerebral hemispheres of the fetuses in cross-section were measured. Fetal cerebellum shape, echotexture, echogenicity, and transverse diameter (TCD) were evaluated in cross-section. Elastography was performed obtaining color elastograms and mean shear wave velocity (SWV m/s) of the fetal brain and cerebellar tissues. Ultrasound variables were correlated with gestational day (GD). Brain masses had a circular to oval shape, hyperechoic echogenicity, and homogeneous echotexture. C and D1 were the more accurate variables to predict gestational day, with the formulas: GD = 19.38 + 2,06∗C (R² = 81%) and GD = 18.93 + 7.45∗D1 (R² = 82%). Cerebellum had a "banana" shape, with hyperechogenic edges, hypoechoic echogenicity, and homogeneous echotexture. The TCD (P = 0.0001) and cerebellar stiffness (P = 0.0006) were greater at 60 days than at 49 days of gestation. The brain mass SWV was correlated positively with GD (P = 0.0001) and showed a gradual increase (P = 0.0001) in the three gestational timepoints evaluated. According to qualitative elastography, both brain mass and cerebellum became more rigid over the course of gestational days. It was possible to verify the development of the brain and cerebellum of canine fetuses during pregnancy by ultrasonographic characteristics and B-mode dimensions, as well as by evaluating the elasticity of these tissues through elastography. These unpublished findings allow a better follow-up of the central nervous system development in the prenatal period and may help in future studies with canine fetuses that present cerebral and cerebellar abnormalities.

One of the most common definitions of microcephaly cited is that of an occipitofrontal circumference (OFC) of the head that is less than two standard deviations below the average for age (or gestational age, if identified prenatally) and sex. Similarly, severe microcephaly is defined as an OFC that is less than three standard deviations below the average. Microcephaly is not a diagnosis, but rather, a finding that is secondary to a multitude of etiologies that can be categorized as prenatal versus postnatal, genetic versus environmental, and congenital versus acquired.

Dandy-Walker malformation (DWM) and Cerebellar vermis hypoplasia (CVH) are commonly recognized human cerebellar malformations diagnosed following ultrasound and antenatal or postnatal MRI. Specific radiological criteria are used to distinguish them, yet little is known about their differential developmental disease mechanisms. We acquired prenatal cases diagnosed as DWM and CVH and studied cerebellar morphobiometry followed by histological and immunohistochemical analyses. This was supplemented by laser capture microdissection and RNA-sequencing of the cerebellar rhombic lip, a transient progenitor zone, to assess the altered transcriptome of DWM vs control samples. Our radiological findings confirm that the cases studied fall within the accepted biometric range of DWM. Our histopathological analysis points to reduced foliation and inferior vermian hypoplasia as common features in all examined DWM cases. We also find that the rhombic lip, a dorsal stem cell zone that drives the growth and maintenance of the posterior vermis is specifically disrupted in DWM, with reduced proliferation and self-renewal of the progenitor pool, and altered vasculature, all confirmed by transcriptomics analysis. We propose a unified model for the developmental pathogenesis of DWM. We hypothesize that rhombic lip development is disrupted through either aberrant vascularization and/or direct insult which causes reduced proliferation and failed expansion of the rhombic lip progenitor pool leading to disproportionate hypoplasia and dysplasia of the inferior vermis. Timing of insult to the developing rhombic lip (before or after 14 PCW) dictates the extent of hypoplasia and distinguishes DWM from CVH.