Multi-Parametric Spatial Assessment of Bone with HR-pQCT

使用 HR-pQCT 对骨骼进行多参数空间评估

• 批准号: 9274155
• 负责人: Julio Carballido-Gamio
• 金额: $ 26.95万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2021-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9274155
• 关键词: Affect; Age; Aging; Biology; Biomechanics; Bone Density; Bone Diseases; Bone structure; Characteristics; Clinical; Clinical Sciences; Data; Development; Diagnosis; Dimensions; Discrimination; Disease; Distal; Elderly; Etiology; Exercise; Forearm Fracture; Fracture; Gender; Geometry; Goals; Hip region structure; Hormonal; Image; Imagery; Imaging Techniques; Incidence; Individual; Information Distribution; Machine Learning; Maps; Measures; Mechanics; Metabolic; Methods; Nature; Organ; Osteoporosis; Patients; Pattern; Peripheral; Persons; Pharmaceutical Preparations; Pharmacotherapy; Population; Postmenopause; Process; Property; Public Health; Radial; Resolution; Risk; Roentgen Rays; Role; Skeleton; Spatial Distribution; Stimulus; Structure; Target Populations; Techniques; Testing; Thick; Time; Tissues; Treatment Efficacy; Variant; Vertebral column; Woman; Work; X-Ray Computed Tomography; age effect; base; bone; bone quality; bone strength; cortical bone; cost; density; experience; fracture risk; improved; in vivo; in vivo imaging; innovation; insight; interest; population based; public health relevance; response; screening; skeletal; skeletal disorder; spatial relationship; substantia spongiosa; tibia; tool; treatment response

 DESCRIPTION (provided by applicant): Osteoporosis is a skeletal disorder characterized by compromised bone strength predisposing a person to an increased risk of fracture. In the U.S. today, 10 million individuals are estimated to already have the disease and almost 34 million more are estimated to have low bone density, placing them at increased risk for osteoporosis and broken bones. Currently, determination of fracture risk, aging effects, and therapeutic efficacy is primarily based on bone mineral density (BMD) measured by areal or volumetric X-ray-based imaging techniques. BMD can predict bone strength and fracture risk to some extent, however, studies have shown that BMD only explains about 70%-75% of the variance in strength, while the remaining variance has been attributed to the cumulative and synergistic effect of other factors such as bone structure, topology, geometry, tissue composition, microdamage, and biomechanical factors. High-resolution peripheral quantitative computed tomography (HR-pQCT) is a noninvasive in-vivo imaging technique which depicts many of these features, including density, geometry, structure, topology, and mechanics of cortical and trabecular bone in the distal radius and distal tibia. To date HR-pQCT imagery has been analyzed using conventional quantitative approaches that average bone features over large regions of interest. The individual quantification of average bone features (uni-parametric) or their statistical combination (multi-parametric) disregard how these three-dimensional (3D) features synergistically contribute to bone strength. As a result the traditional methods fail to capture the spatial patterning of the effect being studied, which is key to understanding the underlying biology. Bone is a 3D organ experiencing constant adaptation through remodeling, and should therefore be analyzed with 3D techniques that reflect the complementary and interdependent nature of different bone features. Statistical parametric mapping (SPM) is a technique that enables 3D spatial comparisons of multi-parametric maps between groups of subjects. Instead of measuring summary properties for arbitrary or subjective volumes of interest, this data-driven process identifies regions significantly associated with a variable of interest through valid statistical tests, thus generating 3D statistical and P-value maps that facilitate the visualization and consequently the interpretation of comparisons between target populations. The ultimate goal of this proposal is to establish a framework to automatically identify relevant bone sub-regions and features in specific populations for the targeted quantitative assessment of the spatial distribution and prediction of bone strength using HR-pQCT. For this purpose, specialized SPM techniques have been developed for HR-pQCT. To evaluate the potential of SPM in clinical science, we propose to apply SPM to image data from three existing in-vivo HR-pQCT studies investigating: a) regional variations in bone structure related to gender and age; b) differences due to fracture of the forearm; and c) longitudinal effects of two osteoporosis treatments.

 描述（由适用提供）：骨质疏松症是一种骨骼疾病，其特征是骨骼强度受损使人遭受骨折的风险增加。在当今的美国，据估计，1000万个人已经患有这种疾病，估计有近3400万人的骨密度低，使他们患骨质疏松症和骨骼骨折的风险增加。当前，确定骨折风险，衰老作用和治疗效果主要基于面积或大量X射线成像技术测量的骨矿物质密度（BMD）。但是，BMD可以在一定程度上预测骨骼强度和断裂风险，研究表明，BMD仅解释了强度差异的70％-75％，而其余方差则归因于其他因素的累积和共同作用，例如骨骼结构，拓扑结构，拓扑，组织组合，微氨基酰胺和生物力学因素和生物力学因素。高分辨率外围定量计算机断层扫描（HR-PQCT）是一种无创的体内成像技术，在不同的半径和独特的胫骨中深处，包括密度，几何，几何，几何形状，结构，拓扑，结构，结构，拓扑和机械骨。迄今为止，已经使用常规定量方法对HR-PQCT图像进行了分析，这些定量方法的平均骨骼特征在大型感兴趣的区域上。平均骨特征（单参数）或其统计组合（多参数）的个人定量无视这些三维（3D）特征如何协同促进骨骼强度。结果，传统方法无法捕获研究效果的空间图案，这是理解潜在生物学的关键。骨骼是一种3D器官，通过重塑经历了恒定的适应性，因此应使用3D技术分析，以反映不同骨骼特征的完整性和相互依存的性质。统计参数映射（SPM）是一种技术，可以实现受试者组之间多参数图的3D空间比较。该数据驱动的过程没有测量关注的任意或主观量的摘要属性，而是通过有效的统计检验确定了与关注变量显着相关的区域，从而产生了3D统计和p值图，从而促进了可视化，从而促进了目标种群之间比较的解释。该提案的最终目标是建立一个框架，以自动确定特定人群中相关的骨区和特征，以使用HR-PQCT对空间分布和骨强度预测的靶向定量评估。为此，为HR-PQCT开发了专门的SPM技术。为了评估SPM在临床科学中的潜力，我们建议将SPM应用于研究研究的三个现有体内HR-PQCT研究研究：a）与性别和年龄有关的骨骼结构的区域变化； b）由于森林破裂而造成的差异； c）两种骨质疏松症治疗的纵向作用。