Age-Dependent Analysis Techniques for Pediatric Structural and Diffusion MRI Data

项目概述(由申请人提供)：该申请旨在开发一种新的表示和计算工具，使更好地了解人脑的发育。这种方法的需求量很大，因为以前介绍的成人大脑分析技术要么不完整，要么不能直接移植到婴儿身上。考虑到在生命的头两年，神经解剖学发生了戏剧性的变化，候选人建议将年龄明确地纳入她的定量图像分析工具中。她将定义并构建一个四维脑图谱，该图谱将总结正常婴儿的中枢趋势和随时间的变化。然后，这份图谱将被用来比较对照组和早产受试者的组，并描述病理发育过程。候选人还将引入计算工具，这些工具可以将来自这种地图集的信息合并到基于模板的分割和配准算法中。前者帮助在图像中分配解剖标签，而后者在新观察的数据之间建立空间对应时依赖于先前积累的图像统计。由于髓鞘形成最快的时期发生在生命的头两年，有关白质的信息对这项技术将是无价的。因此，候选者将严重依赖扩散加权MR图像来补充结构图像信息。在该奖项的指导阶段，将根据神经发育假说和从婴儿数据集获取多模式图像来构建发育中的大脑的年龄表征。在独立阶段，将引入专门为处理婴儿数据而设计的图像处理工具，新模型将用于描述和比较正常和中断的大脑发育。该项目与候选人的长期职业目标一致，即通过对多模式医学采集的分析，在定量模拟人脑发育方面建立一个具有竞争力的独立研究计划。该项目还将促进候选人的短期目标，即成为儿科神经科学和儿科磁共振成像方面的知识。这项工作的指导阶段将在麻省理工学院/哈佛/麻省理工学院马蒂诺斯生物医学成像中心进行，在那里，候选人将利用其合作机构的尖端成像设备、成像专业知识以及世界级的教育机会。她的职业发展计划包括儿科神经解剖学、MR物理学方面的培训；神经科学方面的课程工作，以及参加研讨会和科学会议。

PROJECT SUMMARY (Provided by Applicant): This application aims to develop a novel representation and computational tools that enable a better understanding of human brain development. Such methods are in high demand as previously introduced techniques for adult brain analysis are either incomplete for such purposes or are not directly transferable to infants. Given the dramatic changes in neuroanatomy during the first two years of life, the candidate proposes to explicitly incorporate age into her quantitative image analysis tools. She will define and construct a four dimensional brain atlas that will summarize central tendencies and variations over time in normal infants. This atlas will then be used to compare groups of control and prematurely born subjects and describe pathological development processes. The candidate will also introduce computational tools that may incorporate information from such an atlas into a template-based segmentation and registration algorithm. The former assists in assigning anatomical labels in the images, and the latter relies on previously accumulated image statistics when establishing spatial correspondences among newly observed data. As the most rapid period of myelination occurs in the first two years of life, information about the white matter will be invaluable for this technique. The candidate will therefore rely heavily on diffusion weighted MR images to compliment structural image information. During the Mentored Phase of the award, an age-dependent representation of the developing brain will be constructed relying on neurodevelopmental hypothesis and multi-modal image acquisitions from infant data sets. In the Independent Phase, image processing tools will be introduced that are specifically designed to work with infant data, and the new model will be used to describe and compare normal and disrupted brain development. This project is consistent with the long-term career goal of the candidate, which is to establish a competitive and independent research program in quantitatively modeling human brain development by the analysis of multi-modal medical acquisitions. The project will also facilitate the candidate's short-term goal of becoming knowledgeable in pediatric neuroscience and pediatric MR imaging. The Mentored Phase of this work is to be performed at the MGH/Harvard/MIT Martinos Center for Biomedical Imaging, where the candidate will take advantage of the cutting-edge imaging facilities, imaging expertise, as well as the world-class educational opportunities at its collaborating institutions. Her career development plan includes training in pediatric neuroanatomy, the physics of MR; coursework in neuroscience, and participation in seminars and scientific conferences.