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

儿科结构和扩散 MRI 数据的年龄相关分析技术

• 批准号: 7892749
• 负责人: Lilla Zollei
• 金额: $ 13.63万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-07 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7892749
• 关键词: Adult; Age; Algorithms; Anatomy; Atlases; Award; Brain; Brain imaging; Childhood; Collaborations; Control Groups; Data; Data Set; Development; Development Plans; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Four-dimensional; Goals; Growth; Health; Human; Human Development; Image; Image Analysis; Infant; Institution; Investigation; Label; Life; Literature; MRI Scans; Magnetic Resonance; Magnetic Resonance Imaging; Measures; Medical; Mentors; Methods; Modality; Modeling; Nature; Neuroanatomy; Neurons; Neurosciences; Outcome; Pattern; Phase; Physics; Population; Positioning Attribute; Premature Birth; Process; Property; Public Health; Publications; Research; Resources; Scheme; Structure; Techniques; Technology; Testing; Time; Tissues; Training; Underserved Population; Variant; Weight; Work; age related; base; bioimaging; brain morphology; career; career development; computerized tools; design; experience; image processing; improved; infancy; longitudinal analysis; myelination; neurodevelopment; neuroimaging; novel; programs; regional difference; statistics; symposium; tool; water diffusion; white matter; Adult; Age; Algorithms; Anatomy; Atlases; Award; Brain; Brain imaging; Childhood; Collaborations; Control Groups; Data; Data Set; Development; Development Plans; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Four-dimensional; Goals; Growth; Health; Human; Human Development; Image; Image Analysis; Infant; Institution; Investigation; Label; Life; Literature; MRI Scans; Magnetic Resonance; Magnetic Resonance Imaging; Measures; Medical; Mentors; Methods; Modality; Modeling; Nature; Neuroanatomy; Neurons; Neurosciences; Outcome; Pattern; Phase; Physics; Population; Positioning Attribute; Premature Birth; Process; Property; Public Health; Publications; Research; Resources; Scheme; Structure; Techniques; Technology; Testing; Time; Tissues; Training; Underserved Population; Variant; Weight; Work; age related; base; bioimaging; brain morphology; career; career development; computerized tools; design; experience; image processing; improved; infancy; longitudinal analysis; myelination; neurodevelopment; neuroimaging; novel; programs; regional difference; statistics; symposium; tool; water diffusion; white matter

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.

项目摘要（由申请人提供）：本申请旨在开发一种新颖的表示和计算工具，使人们能够更好地了解人脑发育。 这种方法的需求量很高，因为以前引入的成人脑分析技术要么不完整，要么是不直接转移到婴儿的。 鉴于神经解剖学在生命的头两年发生了巨大变化，候选人建议将年龄明确纳入其定量图像分析工具中。 她将定义和构建一个四维的大脑图集，该地图将总结正常婴儿随时间的中心趋势和变化。 然后，该地图集将用于比较控制和过早出生的受试者的群体并描述病理发展过程。 候选人还将引入计算工具，这些工具可能将此类地图集的信息结合到基于模板的分割和注册算法中。 前者有助于在图像中分配解剖标签，而后者则依赖于先前积累的图像统计数据，而在新观察到的数据之间建立空间对应关系时。 由于髓鞘形成最快的时期发生在生命的头两年中，有关白质的信息对于该技术将是无价的。 因此，候选人将在很大程度上依靠扩散加权的MR图像来补充结构图像信息。 在奖励的指导阶段，将依靠神经发育假设和来自婴儿数据集的多模式图像获取来构建发展大脑的年龄代表。 在独立阶段，将引入图像处理工具，专门设计用于使用婴儿数据，新模型将用于描述和比较正常和破坏的大脑发育。 该项目与候选人的长期职业目标是一致的，该项目是通过分析多模式医学收购来建立竞争性和独立的研究计划，以对人脑发育进行定量建模。 该项目还将促进候选人在小儿神经科学和小儿MR成像方面知识渊博的短期目标。 这项工作的指导阶段将在MGH/Harvard/MIT Martinos生物医学成像中心进行，候选人将利用尖端的成像设施，成像专业知识以及其合作机构的世界一流的教育机会。 她的职业发展计划包括小儿神经解剖学的培训，MR的物理学；神经科学的课程工作，并参加研讨会和科学会议。