Development of cortical surface based tools for healthy control infants

开发用于健康控制婴儿的皮质表面工具

• 批准号: 9314698
• 负责人: Lilla Zollei
• 金额: $ 8.55万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2019-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9314698
• 关键词: Adult; Age; Age-Years; Algorithmic Software; Algorithms; Area; Atlases; Boston; Brain; Brain imaging; Childhood; Clinical; Collaborations; Consent; Data; Data Set; Development; Dimensions; Disease; Ethical Issues; Future; Geometry; Grant; Human; Image; Image Analysis; Individual; Infant; Label; Magnetic Resonance Imaging; Manuals; Maps; Medical; Methods; Neonatal; Neuroanatomy; Neurosciences Research; Outcome; Pattern; Pediatric Hospitals; Performance; Play; Population; Population Control; Premature Infant; Process; Research; Research Infrastructure; Resources; Role; Site; Source; Surface; Testing; Time; Toddler; Underserved Population; Variant; Work; age related; base; bioimaging; clinical investigation; design; image processing; interest; morphometry; myelination; neonate; neuroimaging; non-compliance; novel; premature; reconstruction; tool; translational neuroscience; white matter

Currently there are no publicly available segmentation tools and atlases that would automatically label human brain MRI images and characterize neuroanatomy in the age range of 0 to 5 years. The development of fully automated, highly accurate and robust post-processing tools applicable to this population has been significantly lagging compared to those introduced for adults given a number of factors - the difficulty of obtaining data from non-compliant neonates and toddlers, ethical issues regarding research imaging of subjects who cannot consent, and critically, the rapid change in contrast and geometry displayed during development in infants. Additionally, the majority of the existing imaging data are obtained from clinical subjects (for example, for premature borns), that cannot be used to characterize normal variation in the infant population and thus to produce a baseline for further quantitative comparison between healthy and disease. We believe that it is crucial that atlases and image processing tools are first adapted and introduced for a healthy control population. During the proposed project, we intend to develop a FreeSurfer-compatible pipeline that, when used with standard clinical MRI acquisitions, will compute cortical and subcortical segmentation maps and create topologically correct and geometrically accurate white matter and pial surfaces. Additionally, such surfaces will be used to drive novel pair- and group-wise registration methods to encode spatial correspondences and age-related information in the form of 2D and 3D atlases. This work will be performed at the MGH/Harvard/MIT Martinos Center for Biomedical Imaging in collaboration with the Boston Children's Hospital, where we will take advantage of the cutting-edge imaging facilities as well as leading imaging and clinical expertise.

目前还没有公开的分割工具和图谱可以自动标记人类 脑部 MRI 图像并表征 0 至 5 岁年龄段的神经解剖学特征。全面发展 适用于这一人群的自动化、高精度和强大的后处理工具已经 考虑到许多因素，与针对成人引入的那些相比明显滞后 - 困难 从不合规的新生儿和幼儿获取数据，有关研究成像的伦理问题 无法同意的受试者，并且批判性地，在期间显示的对比度和几何形状的快速变化 婴儿的发育。此外，现有的影像数据大部分来自临床 不能用于表征婴儿正常变异的受试者（例如，早产儿） 人口，从而为健康与疾病之间的进一步定量比较提供基线。 我们认为，首先调整和引入图集和图像处理工具对于 健康对照人群。在拟议的项目中，我们打算开发一个与 FreeSurfer 兼容的管道 当与标准临床 MRI 采集一起使用时，将计算皮质和皮质下分割 绘制并创建拓扑正确和几何精确的白质和软脑膜表面。此外， 这些表面将用于驱动新颖的成对和成组配准方法来编码空间 2D 和 3D 地图集形式的对应关系和年龄相关信息。这项工作将在 麻省总医院/哈佛大学/麻省理工学院马蒂诺斯生物医学成像中心与波士顿儿童医院合作 医院，我们将利用最先进的影像设施以及领先的影像和技术 临床专业知识。