近年来早产儿的出生率正逐年增高，其中低体重（LBW）早产儿易合并脑发育不良而明显影响人口质量。与LBW早产儿相比，非低体重（non-LBW）早产儿并不在少数，而目前对non-LBW早产儿脑发育的结局尚缺乏充分的认识和应有的关注。本研究基于自主构建的五百余例新生儿MRI数据库，预通过多种MRI技术与行为学评价相对照，对non-LBW早产儿开展纵向随访研究。分别基于结构相MRI脑灰白质分割技术获取多种形态学指标，来量化评价脑结构的变化；利用扩散张量成像、扩散峰度成像来量化评价白质发育进程；并基于上述技术对其发育中脑网络连接进行时空分析比较。旨在：1）探索non-LBW早产儿脑结构和脑网络在发育过程中的时空变化规律，寻找判断脑发育进程的生物学标记；2）通过non-LBW早产儿与其它类型新生儿的对比，探索non-LBW早产儿是否存在脑发育的滞后，明确胎龄与出生体重在新生儿不同脑发育阶段的影响。

It has been reported that the birth rate of preterm is increasing in recent years. The preterm neonates with low birth weight (LBW) trend to accompany with brain dysplasia and is considered to greatly affect the quality of the population. Compared with LBW preterm neonates, non-LBW preterm neonates are not uncommon in this population. However, there is still lack of studies focusing on their brain developmental outcomes. Based on our own MRI database which includes more than 500 neonatal brains, we designed a longitudinal study to assess brain development on non-LBW preterm neonates by employing multiple MRI techniques associated with behavioral tests. In this study, the brain segmentation based on volumetric 3-dimensional MRI will be implemented to acquire multiple morphological parameters, diffusion tensor imaging and diffusion kurtosis imaging will be used to assess white matter changes during brain development, and the structural covariance brain network based on above data will be built to delineate spatial and temporal characteristics of the brain connection and network properties. The aims of this study are to: 1) explore the spatial and temporal changes of brain structures and networks in non-LBW preterm neonates and seek the image biomarkers for assessment of the brain development and predicting prognosis; 2) determine if there is developmental retardation in brain structure or/and function of non-LBW preterm neonates, and reveal the long-term independent effects of gestational age and birth weight on the development of neonatal brains.