Predicting the early childhood outcomes of preterm brain shape abnormalities

项目总结/摘要 怀孕的最后几个月对孩子大脑的发育特别重要， 早产对其发育的影响可能是巨大的。早产儿在 各种认知障碍的风险更高，表现出比足月出生的孩子更多的行为障碍。 因此，必须及早发现和管理有危险的儿童。越来越多的证据表明， 早产儿皮质下结构的体积异常，这可能与阴性 长期的神经发育结果。了解这些异常有助于阐明 潜在的病理生理学，并能够早期确定处于风险中的患者，这两者都将告知 设计新的治疗策略。然而，到目前为止，仍然缺乏敏感，可靠和可访问的 能够表征早产对新生儿大脑皮层下解剖结构影响的算法 结构.此外，很少有研究直接关注 这些新生儿皮层下结构异常早期预测长期神经发育结果 最好是在新生儿年龄，这可能会对他们的结果产生变革性影响。我们 初步数据表明壳核，脑室，胼胝体， 和丘脑之间的早产儿和足月儿。我们建议通过以下方式开发早产的生物标志物： 统计学比较早产儿和新生儿皮质下结构的形态学和扩散特性， 和足月新生儿进行脑部MRI检查。这些结果将进一步用于稀疏学习框架， 预测早产儿的长期神经发育结果。假设：通过结合皮质下 形态和扩散特性，我们将能够：（1）描绘特定的相关关系 正常成熟和不同模式的白色对结构的区域性和差异性影响之间的关系 （2）提高神经影像学的特异性，早期预测神经发育结果。 目标1：为新生儿皮层下结构分析构建一个新的工具箱，该工具箱结合了联合收割机：1）基于套索的组 形状变化的显著区域的分析，2）结构相关网络分析，3）新生儿 纤维束成像; 4）基于张量的纤维束分析。目的2：确定新生儿早产的生物标志物 有不同的异常模式目的3：评估影像学和临床特征的预测潜力 对12个月和18个月以及6-8岁早产儿的神经发育结果的影响。 影响：该应用程序将提供第一个完整的足月和早产儿皮质下网络分析 新生儿在第一次对早产儿的研究中，我们将使用稀疏和多任务学习来确定 哪些出生时早产的生物标志物是长期结果的最佳预测因子。预期 这些发现可以提高我们预测这些结果的能力，并使早期治疗的设计成为可能。 多年的病理性大脑发育和症状发生。

PROJECT SUMMARY / ABSTRACT The last months of pregnancy are particularly important for the development of the child's brain, and the consequences of premature birth on its development can be substantial. Prematurely born children are at higher risk of various cognitive impairments and exhibits more behavioral disorders than full-term born children. Thus early detection and management of at risk children are essential. There is growing evidence of significant volumetric abnormalities in subcortical structures of premature neonates, which may be associated to negative long-term neurodevelopmental outcomes. Understanding these abnormalities could help elucidate the underlying pathophysiology and enable early determination of at-risk patients, both of which would inform the design of novel treatment strategies. However, to date there is still a lack of sensitive, reliable, and accessible algorithms capable of characterizing the influence of prematurity on the anatomy of neonatal brain subcortical structures. In addition, few studies have looked directly at the long-term neurodevelopmental implications of these neonatal subcortical structures abnormalities. Predicting long-term neurodevelopmental outcomes early on – and preferably at neonatal ages – is likely to have a transformative effect on their outcome. Our preliminary data indicate significant morphological differences in the putamen, ventricles, corpus callosum, and thalamus between preterm and term neonates. We propose to develop biomarkers of prematurity by statistically comparing the morphological and diffusion properties of subcortical structures between preterm and term neonates using brain MRI. These results will further be used in a sparse learning framework to predict long-term neurodevelopmental outcomes of prematurity. Hypotheses: By combining subcortical morphological and diffusion properties, we will be able to: (1) delineate specific correlative relationships between structures regionally and differentially affected by normal maturation and different patterns of white matter injury, and (2) improve the specificity of neuroimaging to predict neurodevelopmental outcomes earlier. Aim 1: Build a new toolbox for neonatal subcortical structures analyses that combine 1) a group lasso-based analysis of significant regions of shape changes, 2) a structural correlation network analysis, 3) a neonatal tractography, and 4) tensor-based analysis on tracts. Aim 2: Ascertain biomarkers of prematurity in neonates with different patterns of abnormalities. Aim 3: Assess the predictive potential of imaging and clinical features on neurodevelopmental outcomes among premature children at 12 and 18 months and 6-8 years of age. Impact: This application will provide the first complete subcortical network analysis in both term and preterm neonates. In the first study of its kind for prematurity, we will use sparse and multi-task learning to determine which of the biomarkers of prematurity at birth are the best predictors of long-term outcome. The expected findings could improve our ability to predict these outcomes and enable the design of early treatments – before years of pathological brain development and symptoms occur.