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: 10158441
• 负责人: Amanda E Nelson
• 金额: $ 33.18万
• 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/10158441
• 关键词: Address; African American; 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; Diagnostic radiologic examination; Discrimination; Disease; Enrollment; Ethnic Origin; Etiology; Foundations; Future; General Population; Goals; Health; Hispanics; 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; recruit; rheumatologist; sex; 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.

项目摘要 我们的长期目标是证明超声用于OA评估的实用性，标准化其采集， 和评分，并促进US在临床、研究和试验环境中使用的增加。膝 骨关节炎（KOA）是非常普遍的并且经常使人衰弱。潜在治疗方法的开发 这种常见的慢性病的异质性阻碍了，其特征是 亚组或表型的数量，具有不同的潜在病理生理机制。成像， 遗传学、生物化学生物标志物和其他特征可用于表征表型，但 数据类型可能使定义难以统一。虽然射线照相术广泛用于KOA成像，但它 评估早期疾病的能力有限（此时干预措施最有可能成功），并且对 变化超声（US）是一种广泛使用的、省时高效且具有成本效益的成像方式， 提供关于所有关节组织的详细和可靠的信息（例如，软骨、半月板、滑膜、骨），以及 因此可以告知KOA的表型（例如，存在滑膜炎、积液、软骨损伤、钙 晶体沉积和腘动脉囊肿）。目前，由于缺乏系统性的 在充分表征的非临床人群中进行的研究。为了解决这一差距，并进一步利用这一点， KOA的有利成像模式，我们将在人群中获得标准化的US和X线摄影， 基于约翰斯顿县健康研究（JoCoHS），25岁以上约翰斯顿县的新招募阶段 OA项目，包括35-70岁的白色、非洲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，我们将确定膝关节超声特征的人群患病率（n~3000），包括 软骨和关节损伤、滑膜炎/积液、钙结晶沉积、腘囊肿和骨赘 按年龄、性别、人种/种族和症状状态列出的总体和关键亚组。目标2将允许量化 这些US特征与放射学检查结果和症状评分之间的相关性， 子组（例如，按性别、种族/民族划分的有和无放射学KOA的患者）。对于目标3，我们将应用 新颖的机器学习方法（例如，方向投影置换[DiProPerm]假设检验， 联合和个体变异[JIVE]和距离加权鉴别[DWD]），以a）开发一个整体 症状性KOA的US评分和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 美国作为KOA临床使用、研究和临床试验评估工具的基础， 关于美国效用的独特的基于人群的横截面数据，并为未来的研究奠定基础。 纵向工作，评估其价值和与偶发和渐进KOA相关的性能特征。