Structural, Biochemical and Functional Connectivity in Osteoarthritis using Quantitative Magnetic Resonance Imaging and Skeletal Biomechanics

骨关节炎(OA)是一种导致关节退行性变的多因素疾病，影响着2700万美国人。 成人，往往会导致严重残疾。在65岁以上的成年人中，OA的患病率为33.6%。 尽管骨性关节炎是一种广泛传播并使人衰弱的疾病，但目前的治疗选择非常有限。 有限的、成熟的疾病修正疗法并不存在。该解决方案通常提供治疗晚期 阶段，有症状的膝骨性关节炎是关节置换(全膝关节/髋关节置换术，TKA/THA)，而这 手术侵入性和昂贵的治疗方法提供了暂时的缓解，替换通常在10-15年后失败， 肥胖者的寿命较短。为了减少TKA/THA手术的数量，预防性的 针对早期OA的努力和干预是必不可少的-第一步将是在 疾病发展的高风险，在组织尚未丢失和软骨基质异常的阶段 可能是可逆的。了解关节退行性变、膝关节和髋关节的复杂病理生理学 相互作用，步态生物力学的影响，都是决定髋关节骨性关节炎的力学基础的关键。 以软骨生化变化为标志的髋关节骨性关节炎进展具有复杂的多关节相互作用 有几个机制因素，包括形态特征，步态生物力学和人口统计学。 然而，到目前为止的研究大多集中在单一的机械因素和 半定量/定量成像测量、步态生物力学或非客观症状证据 时髦的办公自动化。这次竞争性更新的总体目标是扩展我们的纵向工作，以确定 髋关节软骨生化退变的结构-功能-连通性及其机制因素 与中期(6-8年)的骨质疏松症进展有关。 在这项建议中，受试者将被招募进行纵向研究(覆盖5-8年的随访)从我们的 现有队列(n=184髋关节，92名受试者)，可获得现有的3年随访数据，包括双侧髋关节 髋关节侧位X光片和核磁共振图像，步态生物力学和患者报告的结果。我们将使用小说， 以体素为基础测量基于磁共振的T1ρ和T2弛豫时间的全自动和平移方法， 这将提供有关软骨蛋白多糖、胶原完整性和水分的精确和定位信息 内容。自动分割技术与机器学习算法相结合将用于 在具有体素水平上可量化的T1ρ/T2值的特征良好的数据集中分析软骨T1ρ/T2，并 自动检测导致晚期骨性关节炎的焦点T1ρ/T2抬高模式，并推动 退行性疾病(8岁以上)。基于泛函原理的步态生物力学详细分析 成分分析将利用丰富的骨骼生物力学数据和成像(超过8年)。想象一下 膝关节和髋关节纵向将提供未完成的OA进展的多关节分析(超过4年) 以前并将提供独特的见解，在髋关节骨关节炎的机制，与膝盖的变化。

Osteoarthritis (OA), a multifactorial disease that causes joint degeneration, affects 27 million U.S. adults, and often leads to severe disability. The prevalence of OA is 33.6% in adults older than 65 years. Despite the fact that OA is a widespread and debilitating disease, treatment options are currently extremely limited, and established disease-modifying therapies do not exist. The solution generally offered to treat late stage, symptomatic knee OA is joint replacement (total knee/hip arthroplasty, TKA/THA), and while this surgically invasive and expensive remedy offers temporary relief, replacements often fail after 10-15 years, with shorter life spans in obese individuals. In order to reduce the number of TKA/THA procedures, preventive efforts and interventions targeting early stage OA are essential – the first step would be identifying subjects at high risk for disease development, at a stage when tissue is not yet lost, and cartilage matrix abnormalities are potentially reversible. Understanding the complex pathophysiology of joint degeneration, knee and hip joint interactions, impact of gait biomechanics, are all critical to determine the mechanistic basis of hip OA. Hip OA progression marked by changes in cartilage biochemistry has complex multi-joint interactions with several mechanistic factors, including morphological features, gait biomechanics and demographics. However, studies to date have mostly focused on the relationship between single mechanistic factors and semi-quantitative/ quantitative imaging measures, gait biomechanics, or non-objective symptomatic evidence of hip OA. The overall goal of this competitive renewal is to extend our longitudinal work to determine the structure-function-connectivity and mechanistic factors that mediate biochemical degeneration of hip cartilage associated with OA progression over the mid-term (6-8-year) period. In this proposal, subjects will be recruited for a longitudinal study (covering 5-8 year follow up) from our existing cohort (n=184 hips, 92 subjects), with the availability of existing 3-year follow-up data including bi- lateral hip radiographs and MR images, gait biomechanics and patient reported outcomes. We will use novel, fully automated and translational methods to measure MRI-based T1ρ and T2 relaxation time on a voxel basis, which will provide precise and localized information on cartilage proteoglycan and collagen integrity and water content. Automatic segmentation techniques combined with machine learning algorithms will be used to analyze cartilage T1ρ/T2 in a well-characterized dataset with quantifiable T1ρ/T2 values on a voxel-level, and to automatically detect the patterns of focal T1ρ/T2 elevations that lead to later stage OA and drive progression of degenerative disease (over 8 years). Detailed analysis of gait biomechanics using functional principal component analysis will utilize the rich skeletal biomechanics data and imaging (over 8 years). Imaging the knee and hip longitudinally will provide a multi-joint analysis of OA progression (over 4 years) not done previously and will provide unique insights in the mechanisms in hip OA, connections with knee changes.