An Imaging-based Disease Model for Understanding Bone Health

骨质疏松症，定义为骨矿物质密度的损失，影响所有年龄段的男性和女性， 预测表明，鉴于艾滋病毒/艾滋病的流行， 美国人口老龄化然而，越来越多的人认识到，骨密度并不是测量骨密度的唯一指标。 骨健康：其他骨质量特征，如骨小梁微结构和形状， 在确定一个人骨折风险中的作用。了解骨骼健康-密度和质量-在 骨骼发育的高峰期可以更好地了解骨质疏松症的起点。 该项目致力于开发骨骼发育的疾病模型，以更好地理解 骨质疏松症的病因发展包括：1）使用定量磁共振（qMR）， 表征年轻成人正常人群中的骨发育; 2）进一步表征 使用qMR评估骨质量的松质骨; 3）（因果）贝叶斯信念网络的发展 (BBN)对于骨发育/健康领域，整合qMR值、成像和其他观察 数据到一个统一的模型;和4）一个可视化框架，使用BBN来指导医疗信息的显示。 数据和解释现象，除了允许用户直接查询信仰网络。集成 使用这些方法的显示器是支持的，除了调查的图形技术， 探索大型因果模型。两个患者群体为这项工作提供了测试平台：1）正常 志愿者人群，年龄20-30岁，将接受双发射X射线吸收测定法（DXA）， 外周定量计算机断层扫描（pQCT）和qMR研究，以创建性别和人种/种族 正常骨密度和质量的分层图谱;和2）在UCLA Clark Urological Center就诊的患者 患有导致肾病的慢性肾病的患者（例如，废用性肾性骨营养不良 骨质疏松症），从而提供了与本研究的正常组成部分的比较。一项子研究审查了 维生素D在异常人群中对骨骼发育的作用。评估将分为两个方面：1） 在受控环境中对研究进行技术评价; 2）进行临床评价，以检验疗效 因果疾病模型和终端用户界面的一部分。 与公共卫生的关系。这个提议的主旨是为创造骨骼奠定统一的基础 发展模式，从而更好地了解骨质疏松症。工具，以协助创建此 将开发一个模型，用于解释和探索医疗数据。

Osteoporosis, defined by a loss of bone mineral density, affects both men and women of all ages, and current projections indicate that the prevalence of this disease will grow dramatically over the next decade given the aging American population. However, it is increasingly recognized that bone density is not the only metric for bone health: other bone quality features, such as trabecular micro-architecture and shape, play a significant role in determining an individual's risk forfracture. Understanding bone health - both density and quality - at the peak of skeletal development can provide a better understanding of the starting point for osteoporosis. This project addresses the development of a disease model for bone development to better comprehend the genesis of osteoporosis. Developments include: 1) the use of quantitative magnetic resonance (qMR) to characterize bone development in a young adult normal population; 2) the further characterization of trabecular bone using qMR to assess bone quality; 3) the development of a (causal) Bayesian belief network (BBN) for the domain of bone development/health, integrating qMR values, imaging, and other observational data into a unified model; and 4) a visualization framework that uses the BBN to guide the display of medical data and explain phenomena, in addition to allowing users to directly query the belief network. Integrated displays using these methodologies are supported, in addition to investigation of graphical techniques for exploration of large causal models. Two patient populations provide the testbed for this effort: 1) a normal volunteer population, ages 20-30 years old, that will have dual-emission x-ray absorptiometry (DXA), peripheral quantitative computed tomography (pQCT), and qMR studies to create gender and race/ethnicity stratified atlases of normal bone density and quality; and 2) patients seen at UCLA Clark Urological Center who suffer from chronic renal disease resulting in osteoporotic conditions (e.g., renal osteodystrophy, disuse osteoporosis), thus providinga comparison against the normal component of this study. A sub-study examines the role of vitamin D on bone development within the abnormal population. Evaluation will be twofold: 1) technical evaluation of the research in a controlled environment; and 2) clinical evaluation to test the efficacy of the causal disease model and end user interfaces. Relation to public health. The thrust of this proposal is to lay a unified foundation for creating bone development model, leading to a better understanding of osteoporosis. Tools to assist in the creation of this model, allowing for explanation and exploration of medical data, will be developed.