41 research outputs found

    Association of prenatal diagnosis of critical congenital heart disease with postnatal brain development and the risk of brain injury

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    IMPORTANCE: The relationship of prenatal diagnosis of critical congenital heart disease (CHD) with brain injury and brain development is unknown. Given limited improvement of CHD outcomes with prenatal diagnosis, the effect of prenatal diagnosis on brain health may reveal additional benefits. OBJECTIVE: To compare the prevalence of preoperative and postoperative brain injury and the trajectory of brain development in neonates with prenatal vs postnatal diagnosis of CHD. DESIGN, SETTING, AND PARTICIPANTS: Cohort study of term newborns with critical CHD recruited consecutively from 2001 to 2013 at the University of California, San Francisco and the University of British Columbia. Term newborns with critical CHD were studied with brain magnetic resonance imaging preoperatively and postoperatively to determine brain injury severity and microstructural brain development with diffusion tensor imaging by measuring fractional anisotropy and the apparent diffusion coefficient. Comparisons of magnetic resonance imaging findings and clinical variables were made between prenatal and postnatal diagnosis of critical CHD. A total of 153 patients with transposition of the great arteries and single ventricle physiology were included in this analysis. MAIN OUTCOMES AND MEASURES: The presence of brain injury on the preoperative brain magnetic resonance imaging and the trajectory of postnatal brain microstructural development. RESULTS: Among 153 patients (67% male), 96 had transposition of the great arteries and 57 had single ventricle physiology. The presence of brain injury was significantly higher in patients with postnatal diagnosis of critical CHD (41 of 86 [48%]) than in those with prenatal diagnosis (16 of 67 [24%]) (P = .003). Patients with prenatal diagnosis demonstrated faster brain development in white matter fractional anisotropy (rate of increase, 2.2%; 95% CI, 0.1%-4.2%; P = .04) and gray matter apparent diffusion coefficient (rate of decrease, 0.6%; 95%CI, 0.1%-1.2%; P = .02). Patients with prenatal diagnosis had lower birth weight (mean, 3184.5 g; 95%CI, 3050.3–3318.6) than those with postnatal diagnosis (mean, 3397.6 g; 95%CI, 3277.6–3517.6) (P = .02). Those with prenatal diagnosis had an earlier estimated gestational age at delivery (mean, 38.6 weeks; 95%CI, 38.2–38.9) than those with postnatal diagnosis (mean, 39.1 weeks; 95%CI, 38.8–39.5) (P = .03). CONCLUSIONS AND RELEVANCE: Newborns with prenatal diagnosis of single ventricle physiology and transposition of the great arteries demonstrate less preoperative brain injury and more robust microstructural brain development than those with postnatal diagnosis. These results are likely secondary to improved cardiovascular stability. The impact of these findings on neurodevelopmental outcomes warrants further study

    Neonatal Pain-Related Stress Predicts Cortical Thickness at Age 7 Years in Children Born Very Preterm

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    Background Altered brain development is evident in children born very preterm (24–32 weeks gestational age), including reduction in gray and white matter volumes, and thinner cortex, from infancy to adolescence compared to term-born peers. However, many questions remain regarding the etiology. Infants born very preterm are exposed to repeated procedural pain-related stress during a period of very rapid brain development. In this vulnerable population, we have previously found that neonatal pain-related stress is associated with atypical brain development from birth to term-equivalent age. Our present aim was to evaluate whether neonatal pain-related stress (adjusted for clinical confounders of prematurity) is associated with altered cortical thickness in very preterm children at school age. Methods 42 right-handed children born very preterm (24–32 weeks gestational age) followed longitudinally from birth underwent 3-D T1 MRI neuroimaging at mean age 7.9 yrs. Children with severe brain injury and major motor/sensory/cognitive impairment were excluded. Regional cortical thickness was calculated using custom developed software utilizing FreeSurfer segmentation data. The association between neonatal pain-related stress (defined as the number of skin-breaking procedures) accounting for clinical confounders (gestational age, illness severity, infection, mechanical ventilation, surgeries, and morphine exposure), was examined in relation to cortical thickness using constrained principal component analysis followed by generalized linear modeling. Results After correcting for multiple comparisons and adjusting for neonatal clinical factors, greater neonatal pain-related stress was associated with significantly thinner cortex in 21/66 cerebral regions (p-values ranged from 0.00001 to 0.014), predominately in the frontal and parietal lobes. Conclusions In very preterm children without major sensory, motor or cognitive impairments, neonatal pain-related stress appears to be associated with thinner cortex in multiple regions at school age, independent of other neonatal risk factors

    Automatic segmentation of the hippocampus for preterm neonates from early-in-life to term-equivalent age.

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    INTRODUCTION: The hippocampus, a medial temporal lobe structure central to learning and memory, is particularly vulnerable in preterm-born neonates. To date, segmentation of the hippocampus for preterm-born neonates has not yet been performed early-in-life (shortly after birth when clinically stable). The present study focuses on the development and validation of an automatic segmentation protocol that is based on the MAGeT-Brain (Multiple Automatically Generated Templates) algorithm to delineate the hippocampi of preterm neonates on their brain MRIs acquired at not only term-equivalent age but also early-in-life. METHODS: First, we present a three-step manual segmentation protocol to delineate the hippocampus for preterm neonates and apply this protocol on 22 early-in-life and 22 term images. These manual segmentations are considered the gold standard in assessing the automatic segmentations. MAGeT-Brain, automatic hippocampal segmentation pipeline, requires only a small number of input atlases and reduces the registration and resampling errors by employing an intermediate template library. We assess the segmentation accuracy of MAGeT-Brain in three validation studies, evaluate the hippocampal growth from early-in-life to term-equivalent age, and study the effect of preterm birth on the hippocampal volume. The first experiment thoroughly validates MAGeT-Brain segmentation in three sets of 10-fold Monte Carlo cross-validation (MCCV) analyses with 187 different groups of input atlases and templates. The second experiment segments the neonatal hippocampi on 168 early-in-life and 154 term images and evaluates the hippocampal growth rate of 125 infants from early-in-life to term-equivalent age. The third experiment analyzes the effect of gestational age (GA) at birth on the average hippocampal volume at early-in-life and term-equivalent age using linear regression. RESULTS: The final segmentations demonstrate that MAGeT-Brain consistently provides accurate segmentations in comparison to manually derived gold standards (mean Dice\u27s Kappa \u3e 0.79 and Euclidean distance CONCLUSIONS: MAGeT-Brain is capable of segmenting hippocampi accurately in preterm neonates, even at early-in-life. Hippocampal asymmetry with a larger right side is demonstrated on early-in-life images, suggesting that this phenomenon has its onset in the 3rd trimester of gestation. Hippocampal volume assessed at the time of early-in-life and term-equivalent age is linearly associated with GA at birth, whereby smaller volumes are associated with earlier birth

    Neonatal macrocephaly: cerebral primitive neuroectodermal tumor or neuroblastoma as an infrequent cause--a case report and review of the literature

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    We report a male term newborn presenting with a congenital macrocephaly 3.5 standard deviations above the median, with a wide and tense anterior fontanel, splayed calvarial sutures, and muscular hypotonia. Antenatal head circumferences were repeatedly below the median. A postnatal head ultrasound showed a large right intracerebral mass with right lateral ventricle compression, right temporal horn dilation, and right frontal horn enlargement with lateral displacement. Additional imaging by computed tomography scan and magnetic resonance imaging was performed. A decompression was performed and histology, immunohistochemistry, and molecular biology supported the diagnosis of a primitive neuroectodermal tumor. A MYCN gene amplification assay remained negative. The incidence of neonatal brain tumors is between 1.4 and 4.1/100,000 live births. Their most common presentation is macrocephaly, hydrocephalus, stillbirth, or diagnosis by pre- or postnatal imaging. Although hydrocephaly and intra- or extracranial hemorrhage are the most frequent causes of congenital macrocephaly, this should be initially investigated by head ultrasound. A suspected malignancy will be confirmed by histopathology, immunohistochemistry, and molecular biology

    Patch-based augmentation of Expectation-Maximization for brain MRI tissue segmentation at arbitrary age after premature birth

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    International audienceAccurate automated tissue segmentation of premature neonatal magnetic resonance images is a crucial task for quantification of brain injury and its impact on early postnatal growth and later cognitive development. In such studies it is common for scans to be acquired shortly after birth or later during the hospital stay and therefore occur at arbitrary gestational ages during a period of rapid developmental change. It is important to be able to segment any of these scans with comparable accuracy. Previous work on brain tissue segmentation in premature neonates has focused on segmentation at specific ages. Here we look at solving the more general problem using adaptations of age specific atlas based methods and evaluate this using a unique manually traced database of high resolution images spanning 20 gestational weeks of development. We examine the complimentary strengths of age specific atlas-based Expectation-Maximization approaches and patch-based methods for this problem and explore the development of two new hybrid techniques, patch-based augmentation of Expectation-Maximization with weighted fusion and a spatial variability constrained patch search. The former approach seeks to combine the advantages of both atlas- and patch-based methods by learning from the performance of the two techniques across the brain anatomy at different developmental ages, while the latter technique aims to use anatomical variability maps learnt from atlas training data to locally constrain the patch-based search range. The proposed approaches were evaluated using leave-one-out cross-validation. Compared with the conventional age specific atlas-based segmentation and direct patch based segmentation, both new approaches demonstrate improved accuracy in the automated labeling of cortical gray matter, white matter, ventricles and sulcal cortical-spinal fluid regions, while maintaining comparable results in deep gray matter

    Slower postnatal growth is associated with delayed cerebral cortical maturation in preterm newborns

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    Impaired growth during neonatal intensive care is associated with delayed microstructural development of the cortical gray matter after accounting for prenatal growth, neonatal illness, and brain injury in infants born very preterm.</jats:p
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