Assessment of ultrasound features of knee osteoarthritis in a population-based community cohort

基于人群的社区队列中膝骨关节炎超声特征的评估

• 批准号: 10395598
• 负责人: Amanda E Nelson
• 金额: $ 33.87万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-05 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10395598
• 关键词: Address; African American; African American population; Age; Area; Assessment tool; Bilateral; Biochemical; Biological Markers; Bone Spur; Calcium; Cartilage; Categories; Characteristics; Chronic; Claustrophobias; Clinic; Clinical; Clinical Assessment Tool; Clinical Data; Clinical Research; Clinical Trials; Cohort Studies; Communities; County; Crystal Formation; Crystallization; Data; Data Set; Degenerative polyarthritis; Development; Discrimination; Disease; Enrollment; Ethnic Origin; Etiology; Foundations; Future; General Population; Goals; Health; Hispanic; Image; Implant; Individual; Infrastructure; Intervention; Joints; Knee; Knee Osteoarthritis; Machine Learning; Magnetic Resonance Imaging; Measures; Meniscus structure of joint; Mission; Modality; Musculoskeletal; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Nature; Outcome; Pain; Participant; Pathology; Performance; Phase; Phenotype; Physical activity; Popliteal Cyst; Population; Population Study; Prevalence; Public Health; Race; Receiver Operating Characteristics; Research; Risk Factors; Sex Differences; Specialist; Standardization; Subgroup; Symptoms; Syndrome; Synovial Membrane; Synovitis; Testing; Time; Tissues; Ultrasonography; Variant; Woman; Work; aged; base; bone; cohort; cost; cost effective; effusion; follow-up; imaging genetics; imaging modality; individual variation; interest; machine learning method; men; novel; point of care; population based; radiological imaging; recruit; rheumatologist; sex; ultrasound; uptake

Project summary Our long-term goal is to demonstrate the utility of ultrasound for OA assessment, standardize its acquisition and scoring, and promote increased uptake of US for use in clinical, research, and trial settings. Knee osteoarthritis (KOA) is highly prevalent and frequently debilitating. Development of potential treatments has been hampered by the heterogenous nature of this common chronic condition, which is characterized by a number of subgroups, or phenotypes, with different underlying pathophysiological mechanisms. Imaging, genetics, biochemical biomarkers, and other features can be used to characterize phenotypes, but variations in data types can make it difficult to harmonize definitions. While radiography is widely used in KOA imaging, it is limited in its ability to assess early disease (when interventions are most likely to succeed) and is insensitive to change. Ultrasound (US) is a widely accessible, time-efficient and cost-effective imaging modality that can provide detailed and reliable information about all joint tissues (e.g., cartilage, meniscus, synovium, bone), and could therefore inform phenotypes in KOA (e.g., by presence of synovitis, effusion, cartilage damage, calcium crystal deposition, and popliteal cysts). Use of US is currently limited by the lack of systematically performed studies in well-characterized non-clinical populations. To address this gap and further the use of this advantageous imaging modality for KOA, we will obtain standardized US and radiography in the population- based Johnston County Health Study (JoCoHS), the new enrollment phase of the 25+ year Johnston County OA Project which includes white, African American, and Hispanic men and women aged 35-70, to achieve three aims. In Aim 1, we will determine the population prevalence (n~3000) of knee US features including cartilage and meniscal damage, synovitis/effusion, calcium crystal deposition, popliteal cysts and osteophytes overall and in key subgroups by age, sex, race/ethnicity, and symptom status. Aim 2 will allow quantification of the associations between these US features and radiographic findings and symptom scores overall and in key subgroups (e.g., those with and without radiographic KOA, by sex, by race/ethnicity). For Aim 3, we will apply novel machine learning methodologies (e.g., Direction-projection-permutation [DiProPerm] hypothesis testing, Joint and Individual Variation [JIVE], and Distance-Weighted Discrimination [DWD]) to a) develop an overall US score for symptomatic KOA and b) identify the contribution of US variables to phenotypes relevant to KOA based on general health, physical activity, and functional assessments. This study is a crucial step to establish the foundation for US as an assessment tool for clinical use, research, and clinical trials in KOA, providing unique population-based cross-sectional data regarding the utility of US and forming the basis for future longitudinal work evaluating its value and performance characteristics related to incident and progressive KOA.

项目概要 我们的长期目标是展示超声在 OA 评估中的实用性，标准化其采集 和评分，并促进美国在临床、研究和试验环境中的使用。膝盖 骨关节炎（KOA）非常普遍，并且经常使人衰弱。潜在治疗方法的开发已 这种常见慢性病的异质性阻碍了这种疾病的发展，其特点是 具有不同潜在病理生理机制的亚组或表型的数量。成像， 遗传学、生化生物标志物和其他特征可用于表征表型，但差异 数据类型可能会导致难以协调定义。虽然射线照相术广泛应用于 KOA 成像，但 其评估早期疾病的能力有限（当干预措施最有可能成功时），并且对 改变。超声（美国）是一种广泛使用、省时且经济高效的成像方式，可以 提供有关所有关节组织（例如软骨、半月板、滑膜、骨）的详细且可靠的信息，以及 因此可以了解 KOA 的表型（例如滑膜炎、积液、软骨损伤、钙 晶体沉积和腘窝囊肿）。由于缺乏系统化的执行，目前 US 的使用受到限制 在特征明确的非临床人群中进行的研究。为了解决这一差距并进一步利用这一 对于 KOA 有利的成像方式，我们将在人群中获得标准化的超声和放射线照相 - 基于约翰斯顿县健康研究 (JoCoHS)，约翰斯顿县 25 年以上的新注册阶段 OA 项目包括 35-70 岁的白人、非裔美国人和西班牙裔男性和女性，以实现 三个目标。在目标 1 中，我们将确定膝关节 US 特征的人群患病率 (n~3000)，包括 软骨和半月板损伤、滑膜炎/积液、钙晶体沉积、腘窝囊肿和骨赘 总体情况以及按年龄、性别、种族/民族和症状状态划分的关键亚组。目标 2 将允许量化 这些美国特征与放射学检查结果以及总体和关键症状评分之间的关​​联 亚组（例如，有或没有放射学 KOA 的患者，按性别、种族/民族）。对于目标 3，我们将申请 新颖的机器学习方法（例如，方向投影排列 [DiProPerm] 假设检验， 联合和个体变异 [JIVE] 和距离加权歧视 [DWD]） a) 开发整体 有症状 KOA 的 US 评分，b) 确定 US 变量对 KOA 相关表型的贡献 基于一般健康状况、身体活动和功能评估。这项研究是建立 US 作为 KOA 临床使用、研究和临床试验的评估工具的基础，提供 关于美国效用的独特的基于人口的横截面数据，并为未来奠定基础 纵向工作评估其与事件和进行性 KOA 相关的价值和性能特征。