Groundwork for a Synchrotron MicroCT Imaging Resource for Biology (SMIRB)

同步加速器 MicroCT 生物学成像资源 (SMIRB) 的基础

• 批准号: 10222804
• 负责人: Keith Chi Cheng
• 金额: $ 65.73万
• 依托单位: PENNSYLVANIA STATE UNIV HERSHEY MED CTR
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10222804
• 关键词: 3-Dimensional; Adolescent; Age; Animal Genetics; Animals; Biological; Biological Models; Biology; Biomedical Research; Body measure procedure; Caenorhabditis elegans; Cells; Cellular Structures; Cesium; Chemicals; Chemistry; Communities; Custom; Data; Development; Diagnostic; Drosophila genus; Embryo; Environment; Fishes; Foundations; Genes; Genetic; Geometry; Goals; Histologic; Histology; Histopathology; Image; Infrastructure; Institutes; Iodides; Machine Learning; Measures; Mechanics; Medicine; Metals; Microscopic; Mission; Morphology; Mus; Mutation; Nature; Nerve; Normal Range; Online Systems; Optics; Organ; Output; Pharmaceutical Preparations; Phenotype; Physics; Preparation; Reproducibility; Research; Resolution; Resources; Robotics; Roentgen Rays; Role; Sampling; Scanning; Series; Siblings; Signal Transduction; Slice; Source; Spiral Computed Tomography; Stains; Structural defect; Structure; Synchrotrons; Systems Biology; Techniques; Testing; Texture; Time; Tissue Sample; Tissue imaging; Tissues; Training; Travel; Tube; United States National Institutes of Health; Variant; Whole Organism; Work; Writing; X-Ray Computed Tomography; Zebrafish; automated segmentation; base; bone; cell type; clinical toxicology; computer science; computerized tools; crowdsourcing; data dissemination; data sharing; detector; disease phenotype; drug development; feature detection; histological studies; human disease; imaging modality; improved; instrumentation; microCT; millimeter; mutant; programs; supervised learning; tool; two-dimensional; unsupervised learning; virtual

Project Summary Each major human disease is associated with a specific range of morphological changes to cells and tissues in the micron scale. Normal and abnormal structure was discovered and is still characterized using histology - a microscopic technique that depends on physical tissue slices. Presently, histology’s use in systems biology is limited by its largely descriptive and two-dimensional nature. Making histology quantitative and three-dimensional would be potentially transformational for research and diagnostics, but has been impractical. Accordingly, we have now created a 3D form of histology by customizing X-ray microtomography (micro-CT) of fixed and stained, millimeter-scale, whole organisms and tissue samples. We used fixed and metal-stained, whole zebrafish because they contain a full range of tissues within the size range currently studied histologically. The result is the first practical way to create virtual histology-like “sections” in any plane. Three-dimensional, complete histological phenotyping has potential use in genetic and chemical screens, and in clinical and toxicological tissue diagnostics. Here, we propose the next steps needed to enable high-throughput, quantitative, 3D histological phenotyping of whole, millimeter-scale animals. The proposed work applies the principles of chemistry, physics, and computer science to improve image resolution, throughput, and analytics, organized into three specific aims. Specific Aim 1 will build on our developments in this project and further improve imaging volume and resolution by upgrading imaging array, optics, and sub-pixel shifting, and to throughput by changes in sample embedding, loading geometry and mechanics, helical CT scanning, scintillator material, and to data sharing by improvements to the ViewTool infrastructure and user interface. Specific Aim 2 will yield reference images to define the range of normal phenotypic variation and to obtain samples related to a range of potential applications. Specific Aim 3 will apply the power of machine learning to segmentation, annotation, and analytics. Together, this work will establish a practical foundation for large-scale genetic and chemical screens involving mm-scale, whole organisms based on 3-dimensional, quantitative, histological phenotyping. The instrumentation and analytics will be state-of-the-art in its combination of resolution, field-of-view, pancellularity, image quality, analytical potential, throughput, sample stability, and reproducibility and largely usable with both tube and synchrotron X-ray sources. The voxel resolution will be at least 0.5 μm across fields-of-view of up to 1 cm. Representation of every cell type make the images suitable for cross-referencing across imaging modalities. Potential applications will be explored, “wild-type” will begin to be defined, and training sets for automated segmentation generated. The potential impact will encompass the missions of most NIH Institutes and Centers. The whole-animal genetic and chemical screens enabled are expected to impact drug development, diagnostics, and our basic understanding of how genes and environment define phenotype.

项目摘要 每种主要的人类疾病都与特定范围的细胞和组织形态学变化有关， 微米尺度。发现了正常和异常结构，并且仍然使用组织学进行表征。 一种依赖于物理组织切片的显微技术。目前，组织学在系统生物学中的应用 受其主要描述性和二维性质的限制。使组织学定量化和三维化 将是研究和诊断的潜在变革，但一直不切实际。因此我们 现在已经通过定制固定和染色的X射线显微断层扫描（micro-CT）创建了3D形式的组织学， 毫米级的完整生物体和组织样本。我们用固定的金属染色的整条斑马鱼 因为它们包含目前组织学研究的大小范围内的全部组织。结果是 这是第一个在任何平面上创建虚拟组织学“切片”的实用方法。三维的，完整的 组织学表型分析在遗传和化学筛选以及临床和毒理学方面具有潜在的用途 组织诊断学在这里，我们提出了实现高通量、定量、3D所需的后续步骤 整个毫米级动物的组织学表型。拟议的工作适用以下原则： 化学，物理和计算机科学，以提高图像分辨率，吞吐量和分析，组织成 三个具体目标。具体目标1将建立在我们在这个项目的发展，并进一步改善成像 通过升级成像阵列、光学器件和子像素移位， 在样品包埋、装载几何学和力学、螺旋CT扫描、闪烁体材料和数据方面 通过对ViewTool基础设施和用户界面的改进实现共享。具体目标2将产生参考 图像，以定义正常表型变异的范围，并获得与一系列潜在变异相关的样本。 应用. Specific Aim 3将把机器学习的力量应用于分割、注释和分析。 总之，这项工作将为大规模的遗传和化学筛选奠定实践基础， mm尺度，基于三维、定量、组织学表型的整个生物体。仪表 和分析将是最先进的，在其组合的分辨率，视场，pancellularity，图像质量， 分析潜力、通量、样品稳定性和再现性， 同步加速器X射线源体素分辨率在最大1 cm的视场内至少为0.5 μm。 每种细胞类型的表示使图像适合跨成像模式的交叉参考。 潜在的应用将被探索，“野生型”将开始被定义，并训练集用于自动化 分割生成。潜在的影响将包括大多数NIH研究所和中心的使命。 整个动物的遗传和化学筛选有望影响药物开发，诊断， 以及我们对基因和环境如何定义表型的基本理解。