Continuous longitudinal atlas construction for the study of brain development

摘要： 大脑皮层在围产期发育迅速。在……里面 为了描述这一复杂的过程，需要时空地图集。目前， 然而，用于婴儿大脑的皮质表面图谱的可用性是有限的。这个 与此相比，适用于这一人群的强大工具的开发明显滞后 由于难以从不合规的新生儿那里获得数据，为成年人引入的 和蹒跚学步的孩子，以及在发育过程中表现出的对比度和几何形状的快速变化 婴儿。随着大型纵向脑成像研究的出现，如UNC/UMN Baby 连接体项目(BCP)与大脑和儿童健康发展(HBCD)研究，新 需要算法解决方案来有效地处理这些数据集。在建议的 项目，我们打算开发一条与自由冲浪兼容的管道，将建立一个一致的和 围产期皮质随时间的无偏表示以及一组工具，当与 标准的临床MRI采集，将使计算准确和稳健的球面 表示发育中的大脑以及详细的宏观结构注释。是这样的 然后，表面将被用来描述在前十年中健康的大脑发育 生活。在我们的临床应用中，我们将重点研究早期生活逆境对大脑的影响 发展以及解开关于脑异常的相互矛盾的发现 早产儿，例如其前、后颞叶的脑回变复杂。这 这项工作将在麻省理工学院/哈佛大学/麻省理工学院马蒂诺斯生物医学成像中心进行 在当地合作者收集的数据集上，NIH资助了公开可用的大规模数据集 以及华盛顿大学的同事们召集的临床队列。这样的努力 将使我们能够利用尖端的新生儿成像和计算算法 开发专业知识，试图提供足够健壮和准确的计算工具 用于未来的临床研究

Abstract: There is rapid development of the cerebral cortex that takes place during the perinatal period. In order to characterize this complex process spatio-temporal atlases are needed. At present, however, there is limited availability of cortical surface atlases for the infant brain. The development of robust tools applicable to this population has been significantly lagging compared to those introduced for adults given the difficulty of obtaining data from non-compliant neonates and toddlers and the rapid change in contrast and geometry displayed during development in infants. With the advent of large longitudinal brain imaging studies, such as the UNC/UMN Baby Connectome Project (BCP) and HEALthy Brain and Child Development (HBCD) Study, novel algorithmic solutions are needed to efficiently process these data sets. During the proposed project, we intend to develop a FreeSurfer-compatible pipeline that will establish a consistent and unbiased representation of the perinatal cortex over time and a set of tools that, when used with standard clinical MRI acquisitions, will enable the computation of accurate and robust spherical representations of the developing brain along with detailed macrostructural annotations. Such surfaces then will be used to characterize healthy brain development over the first ten years of life. For our clinical application, we will focus on the effects of early life adversity on brain development as well as on disentangling contradictory findings about brain abnormalities in very preterm infants, such as gyrification complexity in their anterior and posterior temporal lobes. This work will be performed at the MGH/Harvard/MIT Martinos Center for Biomedical Imaging relying on datasets collected by local collaborators, NIH-funded publicly available large scale data sets as well as a clinical cohort assembled by colleagues at the Washington University. Such an effort will allow us to take advantage of cutting-edge neonatal imaging and computational algorithm development expertise in an attempt to deliver computational tools robust and accurate enough for future clinical studies