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

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

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

Quantitative surface analysis of combined MRI and PET enhances detection of focal cortical dysplasias.

ObjectiveFocal cortical dysplasias (FCDs) often cause pharmacoresistant epilepsy, and surgical resection can lead to seizure-freedom. Magnetic resonance imaging (MRI) and positron emission tomography (PET) play complementary roles in FCD identification/localization; nevertheless, many FCDs are small or subtle, and difficult to find on routine radiological inspection. We aimed to automatically detect subtle or visually-unidentifiable FCDs by building a classifier based on an optimized cortical surface sampling of combined MRI and PET features.MethodsCortical surfaces of 28 patients with histopathologically-proven FCDs were extracted. Morphology and intensity-based features characterizing FCD lesions were calculated vertex-wise on each cortical surface, and fed to a 2-step (Support Vector Machine and patch-based) classifier. Classifier performance was assessed compared to manual lesion labels.ResultsOur classifier using combined feature selections from MRI and PET outperformed both quantitative MRI and multimodal visual analysis in FCD detection (93% vs 82% vs 68%). No false positives were identified in the controls, whereas 3.4% of the vertices outside FCD lesions were also classified to be lesional ("extralesional clusters"). Patients with type I or IIa FCDs displayed a higher prevalence of extralesional clusters at an intermediate distance to the FCD lesions compared to type IIb FCDs (p < 0.05). The former had a correspondingly lower chance of positive surgical outcome (71% vs 91%).ConclusionsMachine learning with multimodal feature sampling can improve FCD detection. The spread of extralesional clusters characterize different FCD subtypes, and may represent structurally or functionally abnormal tissue on a microscopic scale, with implications for surgical outcomes

Pontine tegmental cap dysplasia: MR imaging and diffusion tensor imaging features of impaired axonal navigation

BACKGROUND AND PURPOSE: Malformations of the brain stem are uncommon. We present MR imaging and diffusion tensor imaging (DTI) features of 6 patients with pontine tegmental cap dysplasia, characterized by ventral pontine hypoplasia and a dorsal "bump," and speculate on potential mechanisms by which it forms. MATERIALS AND METHODS: Birth and developmental records of 6 patients were reviewed. We reviewed MR imaging studies of all patients and DTIs of patient 3. Potential developmental causes were evaluated. RESULTS: All patients were born uneventfully after normal pregnancies except patient 6 (in utero growth retardation). They presented with multiple cranial neuropathies and evidence of cerebellar dysfunction. Variable hypotonia and motor dysfunction were present. Imaging revealed ventral pontine hypoplasia and mild cerebellar vermian hypoplasia, in addition to an unusual rounded to beaklike "bump" on the dorsal surface of the pons, extending into the fourth ventricle. Color fractional anisotropy maps showed the bump to consist of a bundle of axons directed horizontally (left-right). The bump appeared, on morphologic images, to be continuous with the middle cerebellar peduncles (MCPs), which were slightly diminished in size compared with those in healthy infants. Analysis of the DTI was, however, inconclusive regarding the connections of these axons. The decussation of the MCPs, transverse pontine fibers, and longitudinal brain stem axonal pathways was also abnormal. CONCLUSIONS: Our data suggest that the dorsal transverse axonal band in these disorders results from abnormal axonal pathfinding, abnormal neuronal migration, or a combination of the 2 processes.SCOPUS: re.jinfo:eu-repo/semantics/publishe

Maternal or neonatal infection: association with neonatal encephalopathy outcomes.

BackgroundPerinatal infection may potentiate brain injury among children born preterm. The objective of this study was to examine whether maternal and/or neonatal infection are associated with adverse outcomes among term neonates with encephalopathy.MethodsThis study is a cohort study of 258 term newborns with encephalopathy whose clinical records were examined for signs of maternal infection (chorioamnionitis) and infant infection (sepsis). Multivariate regression was used to assess associations between infection, pattern, and severity of injury on neonatal magnetic resonance imaging, as well as neurodevelopment at 30 mo (neuromotor examination, or Bayley Scales of Infant Development, second edition mental development index <70 or Bayley Scales of Infant Development, third edition cognitive score <85).ResultsChorioamnionitis was associated with lower risk of moderate-severe brain injury (adjusted odds ratio: 0.3; 95% confidence interval: 0.1-0.7; P = 0.004) and adverse cognitive outcome in children when compared with no chorioamnionitis. Children with signs of neonatal sepsis were more likely to exhibit watershed predominant injury than those without (P = 0.007).ConclusionAmong neonates with encephalopathy, chorioamnionitis was associated with a lower risk of brain injury and adverse outcomes, whereas signs of neonatal sepsis carried an elevated risk. The etiology of encephalopathy and timing of infection and its associated inflammatory response may influence whether infection potentiates or mitigates injury in term newborns

Maternal or neonatal infection: association with neonatal encephalopathy outcomes.

Perinatal infection may potentiate brain injury among children born preterm. The objective of this study was to examine whether maternal and/or neonatal infection are associated with adverse outcomes among term neonates with encephalopathy.This study is a cohort study of 258 term newborns with encephalopathy whose clinical records were examined for signs of maternal infection (chorioamnionitis) and infant infection (sepsis). Multivariate regression was used to assess associations between infection, pattern, and severity of injury on neonatal magnetic resonance imaging, as well as neurodevelopment at 30 mo (neuromotor examination, or Bayley Scales of Infant Development, second edition mental development index <70 or Bayley Scales of Infant Development, third edition cognitive score <85).Chorioamnionitis was associated with lower risk of moderate-severe brain injury (adjusted odds ratio: 0.3; 95% confidence interval: 0.1-0.7; P = 0.004) and adverse cognitive outcome in children when compared with no chorioamnionitis. Children with signs of neonatal sepsis were more likely to exhibit watershed predominant injury than those without (P = 0.007).Among neonates with encephalopathy, chorioamnionitis was associated with a lower risk of brain injury and adverse outcomes, whereas signs of neonatal sepsis carried an elevated risk. The etiology of encephalopathy and timing of infection and its associated inflammatory response may influence whether infection potentiates or mitigates injury in term newborns

Maternal or neonatal infection:association with neonatal encephalopathy outcomes

BACKGROUND: Perinatal infection may potentiate brain injury among children born preterm. The objective of this study was to examine whether maternal and/or neonatal infection are associated with adverse outcomes among term neonates with encephalopathy. METHODS: Cohort study of 258 term newborns with encephalopathy whose clinical records were examined for signs of maternal infection (chorioamnionitis) and infant infection (sepsis). Multivariate regression was used to assess associations between infection, pattern and severity of injury on neonatal MRI, as well as neurodevelopment at 30 months (neuromotor exam, or Bayley Scales of Infant Development II MDI <70 or Bayley III cognitive score <85). RESULTS: Chorioamnionitis was associated with lower risk of moderate-severe brain injury (adjusted OR 0.3; 95% CI 0.1–0.7, P=0.004), and adverse cognitive outcome in children when compared to no chorioamnionitis. Children with signs of neonatal sepsis were more likely to exhibit watershed predominant injury than those without (P=0.007). CONCLUSIONS: Among neonates with encephalopathy, chorioamnionitis was associated with a lower risk of brain injury and adverse outcomes, whereas signs of neonatal sepsis carried an elevated risk. The etiology of encephalopathy and timing of infection and its associated inflammatory response may influence whether infection potentiates or mitigates injury in term newborns