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.

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 犹他大学埃克尔斯人类遗传学研究所的马里奥·卡佩奇博士的实验室正在研究特定的、诱导的遗传异常在小鼠中的表型表达，这个模型已经被证明可以深入了解先天性人类疾病的个体发育。传统的小鼠骨骼结构分析需要牺牲研究动物，以及在解剖显微镜下进行骨骼准备和身体检查的劳动密集型、耗时的过程。要进行有意义的统计分析，往往需要数十甚至数百个样本，这意味着巨大的时间和金钱投入。综合生物医学计算中心与Capecchi实验室合作的目标是开发一种更快的、非侵入性的骨骼分析方案，该方案使用三维微型CT的半自动图像处理，而不是对准备好的骨骼标本进行手动测量。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测量方法，如分析骨骼形状，这是准备好的骨骼标本无法实现的。此外，我们预计我们的工具将允许对长度、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(部分渗透性)或被误解为次要影响的基因变化。 在短期内，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实验室的研究人员使用准备好的标本和手动测量骨骼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；Davies和Capecchi，1994)。在这项研究中，我们将使用我们的图像处理和可视化工具获取的骨骼长度和骨骼的标量测量。正如Boulet-Capecchi的研究(Boulet和Capecchi，2002)一样，爪骨的不同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(较小的标准偏差)重现物理测量，甚至可以测量在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的计算统计形状模型的方法应用到分段的老鼠骨骼上。老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和不规则的特征组成。我们开发了一种计算形状对应点的新技术，这是形状分析管道中的关键步骤，我们认为这种方法比将曲面参数化为球体的传统方法更适合这些曲面。 参考文献 Anne Boulet和Mario Capecchi，Anne Boulet和Mario Capecchi，“Hoxd11基因的复制导致小鼠轴和附件骨骼的改变”。发育生物学，249，96-102,2002 艾伦·彼得·戴维斯和马里奥·卡佩奇：“Hoxd-11靶向中断的小鼠的轴向同源分裂和附件骨骼缺陷”。《发展》，120,2187-2198,1994。