IMAGE BASED PHENOTYPING

基于图像的表型分析

• 批准号: 7957219
• 负责人: ROSS T WHITAKER
• 金额: $ 9.02万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7957219
• 关键词: Animal Experimentation; Biomedical Computing; Collaborations; Complex; Computer Retrieval of Information on Scientific Projects Database; Data Set; Defect; Development; Developmental Biology; Funding; Genes; Goals; Grant; Growth; Hand; Human Genetics; Image; Imagery; Institutes; Institution; Investments; Laboratories; Length; Manuals; Measurement; Measures; Methods; Metric; Microscope; Minor; Modeling; Molecular Abnormality; Mus; Mutation; Noise; Preparation; Process; Protocols documentation; Publications; Research; Research Personnel; Research Project Grants; Resources; Shapes; Skeleton; Source; Specimen; Statistical Computing; Structure; Surface; Techniques; Time; United States National Institutes of Health; Universities; Utah; Variant; base; bone; density; human disease; humerus; image processing; imaging Segmentation; insight; morphometry; research study; shape analysis; skeletal; tool

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The laboratory of Dr. Mario Capecchi at the University of Utah's Eccles Institute of Human Genetics is investigating the phenotypic expression of specific, induced genetic abnormalities in mice, a model that has been shown to provide insight into the ontogeny of congenital human disease. Conventional analysis of mouse skeletal structure requires sacrificing the research animal and a labor-intensive, time-consuming process of skeleton preparation and physical inspection under a dissecting microscope. Many tens or even hundreds of specimens are often required for a meaningful statistical analysis, which represents an enormous investment of time and money. The goal of the Center for Integrative Biomedical Computing collaboration with the Capecchi lab is to develop a faster, non-invasive protocol for skeletal analysis that uses semi-automated image processing of three-dimensional micro-CT rather than hand measurements of prepared skeletal specimens. We are developing a set of image segmentation, measurement and visualization tools for quantitative morphometry that allow us to experiment with new metrics such as the analysis of bone shape that would not be possible with prepared skeletal specimens. Furthermore, we expect that our tools will allow for more precise and repeatable measurements for length, density and volume, and therefore give insight into genetic alterations that have previously been described as pleiotropic (partially penetrant) or that have been misinterpreted as minor effects. In the short term, the Center for Integrative Biomedical Computing is targeting two specific research projects for publication. The first project is to validate our non-invasive CT-based protocol for skeletal analysis against the results obtained using prepared specimens and manual bone measurements by researchers in the Capecchi lab (Boulet and Capecchi, 2002; Davies and Capecchi, 1994). In this study, we will use scalar measurements of bone length and bone taken with our image processing and visualization tools. As in the Boulet-Capecchi study (Boulet and Capecchi, 2002), the length of the various bones of the paw will be compared to the length of the humerus. Our hypothesis is that we can reproduce the physical measurements to a greater accuracy (smaller standard deviation) and perhaps even measure additional variation that was lost in the measurement noise inherent to the physical study. Our second research project will apply our methods for computing statistical shape models to the segmented mouse bones. The mouse bones are a very challenging data set because their surfaces are composed of many complex and irregular features. We have developed a new technique for computing shape correspondence points, an essential step in the shape analysis pipeline, that we believe are more suited for these surfaces than conventional methods which parameterize surfaces as spheres. REFERENCES "Duplication of the Hoxd11 Gene Causes Alterations in the Axial and Appendicular Skeleton of the Mouse", Anne Boulet and Mario Capecchi. Developmental Biology, 249, 96-102, 2002 "Axial homeosis and appendicular skeleton defects in mice with a targeted disruption of hoxd-11", Allan Peter Davies and Mario Capecchi. Development, 120, 2187-2198, 1994.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目和 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 犹他大学埃克尔斯人类遗传学研究所的 Mario Capecchi 博士的实验室正在研究小鼠中特定的诱导遗传异常的表型表达，该模型已被证明可以提供对先天性人类疾病的个体发育的深入了解。 小鼠骨骼结构的传统分析需要牺牲研究动物，并且在解剖显微镜下进行骨骼准备和物理检查的劳动密集型、耗时的过程。 进行有意义的统计分析通常需要数十甚至数百个样本，这需要投入大量的时间和金钱。 综合生物医学计算中心与卡佩奇实验室合作的目标是开发一种更快、非侵入性的骨骼分析方案，该方案使用三维显微 CT 的半自动图像处理，而不是对准备好的骨骼标本进行手工测量。我们正在开发一套用于定量形态测量的图像分割、测量和可视化工具，使我们能够试验新的指标，例如分析骨形状，而这对于准备好的骨骼标本来说是不可能的。 此外，我们期望我们的工具能够对长度、密度和体积进行更精确和可重复的测量，从而深入了解以前被描述为多效性（部分渗透）或被误解为次要影响的基因改变。 短期内，综合生物医学计算中心的目标是发表两个具体的研究项目。第一个项目是根据 Capecchi 实验室研究人员使用准备好的标本和手动骨测量获得的结果来验证我们基于非侵入性 CT 的骨骼分析方案（Boulet 和 Capecchi，2002 年；Davies 和 Capecchi，1994 年）。 在本研究中，我们将使用图像处理和可视化工具对骨骼长度和骨骼进行标量测量。 正如 Boulet-Capecchi 研究（Boulet 和 Capecchi，2002）一样，爪子的各种骨头的长度将与肱骨的长度进行比较。我们的假设是，我们可以以更高的精度（更小的标准偏差）重现物理测量结果，甚至可能测量物理研究固有的测量噪声中丢失的额外变化。 我们的第二个研究项目将把我们计算统计形状模型的方法应用于分段的小鼠骨骼。 小鼠骨骼是一个非常具有挑战性的数据集，因为它们的表面由许多复杂且不规则的特征组成。 我们开发了一种计算形状对应点的新技术，这是形状分析流程中的一个重要步骤，我们认为该技术比将表面参数化为球体的传统方法更适合这些表面。 参考 “Hoxd11 基因的重复导致小鼠中轴和附肢骨骼的改变”，Anne Boulet 和 Mario Capecchi。 发育生物学, 249, 96-102, 2002 “通过靶向破坏 hoxd-11 导致小鼠出现轴向同源异形和四肢骨骼缺陷”，Allan Peter Davies 和 Mario Capecchi。 发展，120，2187-2198，1994。