Is sequential cranial ultrasound reliable for detection of white matter injury in very preterm infants?

Cranial ultrasound (cUS) may not be reliable for detection of diffuse white matter (WM) injury. Our aim was to assess in very preterm infants the reliability of a classification system for WM injury on sequential cUS throughout the neonatal period, using magnetic resonance imaging (MRI) as reference standard. In 110 very preterm infants (gestational age < 32 weeks), serial cUS during admission (median 8, range 4-22) and again around term equivalent age (TEA) and a single MRI around TEA were performed. cUS during admission were assessed for presence of WM changes, and contemporaneous cUS and MRI around TEA additionally for abnormality of lateral ventricles. Sequential cUS (from birth up to TEA) and MRI were classified as normal/mildly abnormal, moderately abnormal, or severely abnormal, based on a combination of findings of the WM and lateral ventricles. Predictive values of the cUS classification were calculated. Sequential cUS were classified as normal/mildly abnormal, moderately abnormal, and severely abnormal in, respectively, 22%, 65%, and 13% of infants and MRI in, respectively, 30%, 52%, and 18%. The positive predictive value of the cUS classification for the MRI classification was high for severely abnormal WM (0.79) but lower for normal/mildly abnormal (0.67) and moderately abnormal (0.64) WM. Sequential cUS during the neonatal period detects severely abnormal WM in very preterm infants but is less reliable for mildly and moderately abnormal WM. MRI around TEA seems needed to reliably detect WM injury in very preterm infants.Epidemiology in Pediatrics and Child Healt

Comprehensive Brain MRI Segmentation in High Risk Preterm Newborns

Most extremely preterm newborns exhibit cerebral atrophy/growth disturbances and white matter signal abnormalities on MRI at term-equivalent age. MRI brain volumes could serve as biomarkers for evaluating the effects of neonatal intensive care and predicting neurodevelopmental outcomes. This requires detailed, accurate, and reliable brain MRI segmentation methods. We describe our efforts to develop such methods in high risk newborns using a combination of manual and automated segmentation tools. After intensive efforts to accurately define structural boundaries, two trained raters independently performed manual segmentation of nine subcortical structures using axial T2-weighted MRI scans from 20 randomly selected extremely preterm infants. All scans were re-segmented by both raters to assess reliability. High intra-rater reliability was achieved, as assessed by repeatability and intra-class correlation coefficients (ICC range: 0.97 to 0.99) for all manually segmented regions. Inter-rater reliability was slightly lower (ICC range: 0.93 to 0.99). A semi-automated segmentation approach was developed that combined the parametric strengths of the Hidden Markov Random Field Expectation Maximization algorithm with non-parametric Parzen window classifier resulting in accurate white matter, gray matter, and CSF segmentation. Final manual correction of misclassification errors improved accuracy (similarity index range: 0.87 to 0.89) and facilitated objective quantification of white matter signal abnormalities. The semi-automated and manual methods were seamlessly integrated to generate full brain segmentation within two hours. This comprehensive approach can facilitate the evaluation of large cohorts to rigorously evaluate the utility of regional brain volumes as biomarkers of neonatal care and surrogate endpoints for neurodevelopmental outcomes

White Matter and Cognition in Adults Who Were Born Preterm

BACKGROUND AND PURPOSE: Individuals born very preterm (before 33 weeks of gestation, VPT) are at risk of damage to developing white matter, which may affect later cognition and behaviour. METHODS: We used diffusion tensor MRI (DT-MRI) to assess white matter microstructure (fractional anisotropy; FA) in 80 VPT and 41 term-born individuals (mean age 19.1 years, range 17-22, and 18.5 years, range 17-22 years, respectively). VPT individuals were part of a 1982-1984 birth cohort which had been followed up since birth; term individuals were recruited by local press advertisement. General intellectual function, executive function and memory were assessed. RESULTS: The VPT group had reduced FA in four clusters, and increased FA in four clusters relative to the Term group, involving several association tracts of both hemispheres. Clusters of increased FA were associated with more severe neonatal brain injury in the VPT group. Clusters of reduced FA were associated with lower birth weight and perinatal hypoxia, and with reduced adult cognitive performance in the VPT group only. CONCLUSIONS: Alterations of white matter microstructure persist into adulthood in VPT individuals and are associated with cognitive function

Developmental malformation of the corpus callosum: a review of typical callosal development and examples of developmental disorders with callosal involvement

This review provides an overview of the involvement of the corpus callosum (CC) in a variety of developmental disorders that are currently defined exclusively by genetics, developmental insult, and/or behavior. I begin with a general review of CC development, connectivity, and function, followed by discussion of the research methods typically utilized to study the callosum. The bulk of the review concentrates on specific developmental disorders, beginning with agenesis of the corpus callosum (AgCC)—the only condition diagnosed exclusively by callosal anatomy. This is followed by a review of several genetic disorders that commonly result in social impairments and/or psychopathology similar to AgCC (neurofibromatosis-1, Turner syndrome, 22q11.2 deletion syndrome, Williams yndrome, and fragile X) and two forms of prenatal injury (premature birth, fetal alcohol syndrome) known to impact callosal development. Finally, I examine callosal involvement in several common developmental disorders defined exclusively by behavioral patterns (developmental language delay, dyslexia, attention-deficit hyperactive disorder, autism spectrum disorders, and Tourette syndrome)