The University of Queensland, School of Medicine, Brisbane, Australia.
PLoS One. 2013 Aug 7;8(8):e68593. doi: 10.1371/journal.pone.0068593. eCollection 2013.
Preterm birth is associated with a high prevalence of adverse neurodevelopmental outcome. Non-invasive techniques which can probe the neural correlates underpinning these deficits are required. This can be achieved by measuring the structural network of connections within the preterm infant's brain using diffusion MRI and tractography. We used diffusion MRI and T2 relaxometry to identify connections with altered white matter properties in preterm infants compared to term infants. Diffusion and T2 data were obtained from 9 term neonates and 18 preterm-born infants (born <32 weeks gestational age) at term equivalent age. Probabilistic tractography incorporating multiple fibre orientations was used in combination with the Johns Hopkins neonatal brain atlas to calculate the structural network of connections. Connections of altered diffusivity or T2, as well as their relationship with gestational age at birth and postmenstrual age at the time of MRI, were identified using the network based statistic framework. A total of 433 connections were assessed. FA was significantly reduced in 17, and T2 significantly increased in 18 connections in preterm infants, following correction for multiple comparisons. Cortical networks associated with affected connections mainly involved left frontal and temporal cortical areas: regions which are associated with working memory, verbal comprehension and higher cognitive function--deficits which are often observed later in children and adults born preterm. Gestational age at birth correlated with T2, but not diffusion in several connections. We found no association between diffusion or T2 and postmenstrual age at the time of MRI in preterm infants. This study demonstrates that alterations in the structural network of connections can be identified in preterm infants at term equivalent age, and that incorporation of non-diffusion measures such as T2 in the connectome framework provides complementary information for the assessment of brain development.
早产与不良神经发育结果的高患病率有关。需要使用可以探测这些缺陷所基于的神经相关性的非侵入性技术。这可以通过使用扩散 MRI 和轨迹追踪术来测量早产儿大脑内连接的结构网络来实现。我们使用扩散 MRI 和 T2 弛豫度测量来比较早产儿和足月产儿的脑白质性质改变的连接。扩散和 T2 数据来自 9 名足月新生儿和 18 名早产儿(胎龄<32 周)在胎龄相当的年龄。结合约翰霍普金斯新生儿脑图谱,采用多纤维取向的概率轨迹追踪来计算结构连接网络。使用基于网络的统计框架来识别扩散率或 T2 改变的连接及其与出生时的胎龄和 MRI 时的孕龄的关系。评估了总共 433 个连接。校正多重比较后,早产儿中有 17 个连接的 FA 显著降低,18 个连接的 T2 显著增加。受影响的连接相关的皮质网络主要涉及左侧额颞皮质区域:这些区域与工作记忆、言语理解和更高认知功能有关——这些缺陷在早产儿和成人中经常在后期观察到。出生时的胎龄与几个连接的 T2 相关,但与扩散无关。我们在早产儿中没有发现扩散或 T2 与 MRI 时的孕龄之间的关联。这项研究表明,在胎龄相当的早产儿中可以识别出连接的结构网络的改变,并且在连接组框架中加入非扩散测量,如 T2,可以提供用于评估大脑发育的补充信息。