Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8688494 | NeuroImage: Clinical | 2017 | 9 Pages |
Abstract
Global patterns of brain injury correlate with motor, cognitive, and language outcomes in survivors of neonatal encephalopathy (NE). However, it is still unclear whether local changes in brain structure predict specific deficits. We therefore examined whether differences in brain structure at 6Â months of age are associated with neurodevelopmental outcomes in this population. We enrolled 32 children with NE, performed structural brain MR imaging at 6Â months, and assessed neurodevelopmental outcomes at 30Â months. All subjects underwent T1-weighted imaging at 3Â T using a 3D IR-SPGR sequence. Images were normalized in intensity and nonlinearly registered to a template constructed specifically for this population, creating a deformation field map. We then used deformation based morphometry (DBM) to correlate variation in the local volume of gray and white matter with composite scores on the Bayley Scales of Infant and Toddler Development (Bayley-III) at 30Â months. Our general linear model included gestational age, sex, birth weight, and treatment with hypothermia as covariates. Regional brain volume was significantly associated with language scores, particularly in perisylvian cortical regions including the left supramarginal gyrus, posterior superior and middle temporal gyri, and right insula, as well as inferior frontoparietal subcortical white matter. We did not find significant correlations between regional brain volume and motor or cognitive scale scores. We conclude that, in children with a history of NE, local changes in the volume of perisylvian gray and white matter at 6Â months are correlated with language outcome at 30Â months. Quantitative measures of brain volume on early MRI may help identify infants at risk for poor language outcomes.
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Authors
Kevin A. Shapiro, Hosung Kim, Maria Luisa Mandelli, Elizabeth E. Rogers, Dawn Gano, Donna M. Ferriero, A. James Barkovich, Maria Luisa Gorno-Tempini, Hannah C. Glass, Duan Xu,