Altered small-world topology of structural brain networks in infants with intrauterine growth restriction and its association with later neurodevelopmental outcome
Altered small-world topology of structural brain networks in infants with intrauterine growth restriction and its association with later neurodevelopmental outcome
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DOI：
10.1016/j.neuroimage.2012.01.059
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发表时间：
2012-04-02
期刊：
影响因子：
5.7
通讯作者：
Gratacos, Eduard
中科院分区：
文献类型：
--
作者：
Batalle, Dafnis;Eixarch, Elisenda;Gratacos, Eduard
胎盘功能不全导致的宫内生长受限 (IUGR) 影响 5-10% 的妊娠，并且与多种短期和长期神经发育障碍相关。预测 IUGR 的神经发育结果是现代胎儿医学和儿科的临床挑战之一。近年来，一些研究使用磁共振成像 (MRI) 来证明 IUGR 受试者大脑结构的差异，但使用 MRI 对 IUGR 进行个体预测的能力有限。最近的研究表明，体内 MRI 获取大脑连接可能有可能帮助理解认知和神经发育过程。具体来说，基于 MRI 的连接组学是一种从 MRI 数据中提取信息的新兴方法，该方法详尽地映射了大脑内的区域间连接，以构建称为脑网络的神经回路的图形模型。在本研究中，我们使用基于扩散 MRI 的连接组学来获得一岁婴儿的前瞻性队列（32 名对照组和 24 IUGR）的结构脑网络，并通过脑网络的全局和区域图论特征分析 IUGR 组白质回路的可量化大脑重组的存在。基于对大脑网络拓扑的全局和区域分析，我们证明了 IUGR 婴儿在一岁时的大脑重组。具体来说，IUGR 婴儿表现出全局和局部加权效率下降，以及区域图论特征改变的模式。通过二项式逻辑回归，我们还证明连接性测量与后来的神经发育结果的异常表现相关，这是通过贝利婴幼儿发育量表第三版（BSID-III）在两岁时测量的。这些发现显示了基于连接组学和图论网络特征的扩散 MRI 的潜力，可用于估计神经回路结构的差异并开发患有产前疾病的婴儿神经发育结果不良的成像生物标志物。 (c) 2012 Elsevier Inc. 保留所有权利。
Intrauterine growth restriction (IUGR) due to placental insufficiency affects 5-10% of all pregnancies and it is associated with a wide range of short- and long-term neurodevelopmental disorders. Prediction of neurodevelopmental outcomes in IUGR is among the clinical challenges of modern fetal medicine and pediatrics. In recent years several studies have used magnetic resonance imaging (MRI) to demonstrate differences in brain structure in IUGR subjects, but the ability to use MRI for individual predictive purposes in IUGR is limited. Recent research suggests that MRI in vivo access to brain connectivity might have the potential to help understanding cognitive and neurodevelopment processes. Specifically, MRI based connectomics is an emerging approach to extract information from MRI data that exhaustively maps inter-regional connectivity within the brain to build a graph model of its neural circuitry known as brain network. In the present study we used diffusion MRI based connectomics to obtain structural brain networks of a prospective cohort of one year old infants (32 controls and 24 IUGR) and analyze the existence of quantifiable brain reorganization of white matter circuitry in IUGR group by means of global and regional graph theory features of brain networks. Based on global and regional analyses of the brain network topology we demonstrated brain reorganization in IUGR infants at one year of age. Specifically, IUGR infants presented decreased global and local weighted efficiency, and a pattern of altered regional graph theory features. By means of binomial logistic regression, we also demonstrated that connectivity measures were associated with abnormal performance in later neurodevelopmental outcome as measured by Bayley Scale for Infant and Toddler Development, Third edition (BSID-III) at two years of age. These findings show the potential of diffusion MRI based connectomics and graph theory based network characteristics for estimating differences in the architecture of neural circuitry and developing imaging biomarkers of poor neurodevelopment outcome in infants with prenatal diseases. (c) 2012 Elsevier Inc. All rights reserved.