Brain age predicted using graph convolutional neural network explains neurodevelopmental trajectory in preterm neonates

OBJECTIVES: Dramatic brain morphological changes occur throughout the third trimester of gestation. In this study, we investigated whether the predicted brain age (PBA) derived from graph convolutional network (GCN) that accounts for cortical morphometrics in third trimester is associated with postnatal abnormalities and neurodevelopmental outcome. METHODS: In total, 577 T1 MRI scans of preterm neonates from two different datasets were analyzed; the NEOCIVET pipeline generated cortical surfaces and morphological features, which were then fed to the GCN to predict brain age. The brain age index (BAI; PBA minus chronological age) was used to determine the relationships among preterm birth (i.e., birthweight and birth age), perinatal brain injuries, postnatal events/clinical conditions, BAI at postnatal scan, and neurodevelopmental scores at 30 months. RESULTS: Brain morphology and GCN-based age prediction of preterm neonates without brain lesions (mean absolute error [MAE]: 0.96 weeks) outperformed conventional machine learning methods using no topological information. Structural equation models (SEM) showed that BAI mediated the influence of preterm birth and postnatal clinical factors, but not perinatal brain injuries, on neurodevelopmental outcome at 30 months of age. CONCLUSIONS: Brain morphology may be clinically meaningful in measuring brain age, as it relates to postnatal factors, and predicting neurodevelopmental outcome. CLINICAL RELEVANCE STATEMENT: Understanding the neurodevelopmental trajectory of preterm neonates through the prediction of brain age using a graph convolutional neural network may allow for earlier detection of potential developmental abnormalities and improved interventions, consequently enhancing the prognosis and quality of life in this vulnerable population. KEY POINTS: •Brain age in preterm neonates predicted using a graph convolutional network with brain morphological changes mediates the pre-scan risk factors and post-scan neurodevelopmental outcomes. •Predicted brain age oriented from conventional deep learning approaches, which indicates the neurodevelopmental status in neonates, shows a lack of sensitivity to perinatal risk factors and predicting neurodevelopmental outcomes. •The new brain age index based on brain morphology and graph convolutional network enhances the accuracy and clinical interpretation of predicted brain age for neonates

CHMP1A encodes an essential regulator of BMI1-INK4A in cerebellar development

Charged multivesicular body protein 1A (CHMP1A; also known as chromatin-modifying protein 1A) is a member of the ESCRT-III (endosomal sorting complex required for transport-III) complex but is also suggested to localize to the nuclear matrix and regulate chromatin structure. Here, we show that loss-of-function mutations in human CHMP1A cause reduced cerebellar size (pontocerebellar hypoplasia) and reduced cerebral cortical size (microcephaly). CHMP1A-mutant cells show impaired proliferation, with increased expression of INK4A, a negative regulator of stem cell proliferation. Chromatin immunoprecipitation suggests loss of the normal INK4A repression by BMI in these cells. Morpholino-based knockdown of zebrafish chmp1a resulted in brain defects resembling those seen after bmi1a and bmi1b knockdown, which were partially rescued by INK4A ortholog knockdown, further supporting links between CHMP1A and BMI1-mediated regulation of INK4A. Our results suggest that CHMP1A serves as a critical link between cytoplasmic signals and BMI1-mediated chromatin modifications that regulate proliferation of central nervous system progenitor cells

Human iPSC-Derived Cerebral Organoids Model Cellular Features of Lissencephaly and Reveal Prolonged Mitosis of Outer Radial Glia

Classical lissencephaly is a genetic neurological disorder associated with mental retardation and intractable epilepsy, and Miller-Dieker syndrome (MDS) is the most severe form of the disease. In this study, to investigate the effects of MDS on human progenitor subtypes that control neuronal output and influence brain topology, we analyzed cerebral organoids derived from control and MDS-induced pluripotent stem cells (iPSCs) using time-lapse imaging, immunostaining, and single-cell RNA sequencing. We saw a cell migration defect that was rescued when we corrected the MDS causative chromosomal deletion and severe apoptosis of the founder neuroepithelial stem cells, accompanied by increased horizontal cell divisions. We also identified a mitotic defect in outer radial glia, a progenitor subtype that is largely absent from lissencephalic rodents but critical for human neocortical expansion. Our study, therefore, deepens our understanding of MDS cellular pathogenesis and highlights the broad utility of cerebral organoids for modeling human neurodevelopmental disorders

Risk of Recurrent Arterial Ischemic Stroke in Childhood: A Prospective International Study.

Background and purposePublished cohorts of children with arterial ischemic stroke (AIS) in the 1990s to early 2000s reported 5-year cumulative recurrence rates approaching 20%. Since then, utilization of antithrombotic agents for secondary stroke prevention in children has increased. We sought to determine rates and predictors of recurrent stroke in the current era.MethodsThe Vascular Effects of Infection in Pediatric Stroke (VIPS) study enrolled 355 children with AIS at 37 international centers from 2009 to 2014 and followed them prospectively for recurrent stroke. Index and recurrent strokes underwent central review and confirmation, as well as central classification of causes of stroke, including arteriopathies. Other predictors were measured via parental interview or chart review.ResultsOf the 355 children, 354 survived their acute index stroke, and 308 (87%) were treated with an antithrombotic medication. During a median follow-up of 2.0 years (interquartile range, 1.0-3.0), 40 children had a recurrent AIS, and none had a hemorrhagic stroke. The cumulative stroke recurrence rate was 6.8% (95% confidence interval, 4.6%-10%) at 1 month and 12% (8.5%-15%) at 1 year. The sole predictor of recurrence was the presence of an arteriopathy, which increased the risk of recurrence 5-fold when compared with an idiopathic AIS (hazard ratio, 5.0; 95% confidence interval, 1.8-14). The 1-year recurrence rate was 32% (95% confidence interval, 18%-51%) for moyamoya, 25% (12%-48%) for transient cerebral arteriopathy, and 19% (8.5%-40%) for arterial dissection.ConclusionsChildren with AIS, particularly those with arteriopathy, remain at high risk for recurrent AIS despite increased utilization of antithrombotic agents. Therapies directed at the arteriopathies themselves are needed

Neuropathology of brain and spinal malformations in a case of monosomy 1p36

Abstract Monosomy 1p36 is the most common subtelomeric chromosomal deletion linked to mental retardation and seizures. Neuroimaging studies suggest that monosomy 1p36 is associated with brain malformations including polymicrogyria and nodular heterotopia, but the histopathology of these lesions is unknown. Here we present postmortem neuropathological findings from a 10 year-old girl with monosomy 1p36, who died of respiratory complications. The findings included micrencephaly, periventricular nodular heterotopia in occipitotemporal lobes, cortical dysgenesis resembling polymicrogyria in dorsolateral frontal lobes, hippocampal malrotation, callosal hypoplasia, superiorly rotated cerebellum with small vermis, and lumbosacral hydromyelia. The abnormal cortex exhibited “festooned” (undulating) supragranular layers, but no significant fusion of the molecular layer. Deletion mapping demonstrated single copy loss of a contiguous 1p36 terminal region encompassing many important neurodevelopmental genes, among them four HES genes implicated in regulating neural stem cell differentiation, and TP73, a monoallelically expressed gene. Our results suggest that brain and spinal malformations in monosomy 1p36 may be more extensive than previously recognized, and may depend on the parental origin of deleted genes. More broadly, our results suggest that specific genetic disorders may cause distinct forms of cortical dysgenesis

A pictorial review of the pathophysiology and classification of the magnetic resonance imaging patterns of perinatal term hypoxic ischemic brain injury - What the radiologist needs to know….

This article provides a correlation of the pathophysiology and magnetic resonance imaging (MRI) patterns identified on imaging of children with hypoxic ischemic brain injury (HIBI). The purpose of this pictorial review is to empower the reading radiologist with a simplified classification of the patterns of cerebral injury matched to images of patients demonstrating each subtype. A background narrative literature review was undertaken of the regional, continental and international databases looking at specific patterns of cerebral injury related to perinatal HIBI. In addition, a database of MRI studies accumulated over a decade (including a total of 314 studies) was analysed and subclassified into the various patterns of cerebral injury. Selected cases were annotated to highlight the areas involved and for ease of identification of the affected substrate in daily practice.KeywordsHypoxic ischemic encephalopathy; Magnetic resonance imaging; Acute profound; Partial prolonged; Hypoxic ischemic brain injury; Ulegyria; Multicystic; Encephalopathy

Update on neuroimaging phenotypes of mid-hindbrain malformations

Purpose: Neuroimaging techniques including structural magnetic resonance imaging (MRI) and functional positron emission tomography (PET) are useful in categorizing various midbrain-hindbrain (MHB) malformations, both in allowing diagnosis and in helping to understand the developmental processes that were disturbed. Brain imaging phenotypes of numerous malformations are characteristic features that help in guiding the genetic testing in case of direct neuroimaging-genotype correlation or, at least, to differentiate among MHB malformations entities. The present review aims to provide the reader with an update of the use of neuroimaging applications in the fine analysis of MHB malformations, using a comprehensive, recently proposed developmental and genetic classification. Methods: We have performed an extensive systematic review of the literature, from the embryology main steps of MHB development through the malformations entities, with regard to their molecular and genetic basis, conventional MRI features, and other neuroimaging characteristics. Results: We discuss disorders in which imaging features are distinctive and how these features reflect the structural and functional impairment of the brain. Conclusion: Recognition of specific MRI phenotypes, including advanced imaging features, is useful to recognize the MHB malformation entities, to suggest genetic investigations, and, eventually, to monitor the disease outcome after supportive therapies.SCOPUS: ar.jinfo:eu-repo/semantics/publishe