IMAGE BASED PHENOTYPING

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。 犹他州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 小鼠特定的、诱导的遗传异常的表型表达，这是一个已被证明提供洞察力的模型 先天人类疾病的个体发育。对小鼠骨骼结构的常规分析需要牺牲 研究动物和劳动密集型、耗时的骨骼准备和体检过程 在解剖显微镜下。为了进行有意义的统计，往往需要数十甚至数百个样本 分析，这代表着巨大的时间和金钱投入。？综合管理中心的目标是 与Capecchi实验室的生物医学计算合作是为了开发一种更快的、非侵入性的骨骼协议 使用半自动图像处理的三维微型CT而不是手工测量的分析 我们正在开发一套图像分割、测量和可视化工具，用于 定量形态计量学，允许我们试验新的衡量标准，如分析骨骼形状， 用准备好的骨骼标本是不可能的。此外，我们预计我们的工具将允许更精确和 可重复测量长度、密度和体积，从而深入了解具有 以前被描述为多效性(部分渗透性)或被误解为次要影响。 在短期内，综合生物医学计算中心将针对以下两个具体的研究项目 出版。第一个项目是根据结果验证我们基于非侵入性CT的骨骼分析协议 由Capecchi实验室的研究人员使用准备好的标本和手动骨骼测量获得(Boulet和 Capecchi，2002；Davies和Capecchi，1994)。在这项研究中，我们将使用标量测量骨骼长度和骨骼 使用我们的图像处理和可视化工具拍摄。与Boulet-Capecchi研究(Boulet和Capecchi，2002)一样， 爪子不同骨骼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(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于分段鼠标 骨头。？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。？我们已经开发了一种计算形状对应点的新技术，这是 形状分析流水线，我们认为它比传统的方法更适合这些表面 将曲面参数化为球体。 参考文献 《Hoxd11基因的复制导致小鼠轴和附件骨骼的改变》，Anne Boulet 还有马里奥·卡佩奇。《发育生物学》，249，96-102,2002 《靶向干扰Hoxd-11的小鼠的轴向同源分裂和附件骨骼缺陷》，Allan Peter Davies 还有马里奥·卡佩奇。《发展》，120,2187-2198,1994。

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.