Cartilage, Bone and Marrow Interactions in Knee OA

描述(申请人提供)：骨性关节炎(OA)影响着5000多万美国人，并对美国经济和医疗保健系统产生重大影响。目前，这种令人衰弱的疾病还没有治愈方法，有效的治疗充其量只能集中在缓解症状上。传统的MR技术在识别由软骨体积或表面纤颤决定的更细微的形态变化方面表现出了希望。然而，即使是这些传统技术中更具创新性的技术，在预测膝骨性关节炎进展方面也并不一致。因此，对早期识别危险人群的可靠、客观、非侵入性和定量的影像标志物的需求很高。这项赠款申请的长期目标是开发一种更有效的方法，通过对软骨、松质骨和骨髓的量化评估来识别膝骨性关节炎进展的高风险个体。高分辨率、多核[~(23)Na和~(1H)]磁共振成像方法、新的图像后处理和超高场系统(7T)可视化方法将对OA病理的客观评价产生重大影响。许多危险因素，如关节排列不齐、肥胖、创伤、半月板异常或十字韧带撕裂、生化、生物力学、遗传和环境等都可能加重骨性关节炎。具体地说，我们将使用新的钠和质子微磁共振、图像处理和可视化技术，使用模糊距离变换(FDT)、数字拓扑分析(DTA)和张量分析。我们将以纵向方式获取年龄和性别匹配的OA受试者的高分辨率钠和质子磁共振成像，以确定基线联合风险描述是否可以预测30个月期间严重膝骨性关节炎进展的危险人群。最后，我们将确定基线检查中哪些相互作用(软骨-骨、骨髓或软骨-骨髓或三者的组合等)能更好地预测30个月内严重膝骨性关节炎进展的潜在危险因素。一旦在人类膝关节中得到开发和验证，这些研究不仅将深刻地影响到对OA的早期诊断，而且可能会在早期识别危险人群。我们预计软骨、骨和骨髓之间的定量交互作用以及它们的组合交互作用可能有助于设计膝关节骨关节炎进展的风险概况，而不是个体化的方法。我们计划通过分包合同(爱荷华大学电气与计算机工程与放射学系Punam Saha博士)与外部合作解决骨关节炎患者软骨、骨骼和骨髓之间的这些密切相互作用。资助申请的重点与NIBIB/NIAMS(NIH)生物工程研究资助(BRG)计划的使命一致。

DESCRIPTION (provided by applicant): Osteoarthritis (OA) affects over 50 million Americans and has a substantial impact on the US economy and the health care system. Currently, there is no cure for this debilitating disease and the effective treatment is, at best, focused on symptomatic relief. The conventional MR techniques have shown promise for the identification of more subtle morphologic alterations as determined by cartilage volume, or surface fibrillation. However, even the more innovative of these conventional techniques have not been consistent in predicting the knee OA progression. Therefore, there is a high demand for reliable, objective, non-invasive and quantitative imaging markers that identifies the risk population at early stage. The long-term objective of this grant application is to develop a more effective means of identifying individuals at higher risk for knee OA progression via quantitative knee joint assessment of cartilage, trabecular bone and bone marrow. High- resolution, multi-nuclear [sodium (23Na) and proton (1H)] MR imaging approaches, novel image post- processing and visualization methods at ultra-high field system (7T) will significantly impact the objective assessment of OA pathology. OA may be aggravated by many risk factors such as joint malalignment, obesity, trauma, meniscal abnormalities or cruciate ligament tears, biochemical, biomechanical, genetic, and environmental. Specifically, we will use novel sodium and proton micro-MRI, image-processing and visualization technologies employing fuzzy distance transform (FDT), digital topological analysis (DTA) and tensor analysis. We will acquire high resolution sodium and proton MRI of age-and gender matched OA subjects in a longitudinal fashion to determine whether baseline combined risk profile can predict risk population for severe knee OA progression over 30 months period. Finally, we will identify which interactions (cartilage-bone, bone-marrow or cartilage-marrow or combination of all three etc) at baseline exam will better predict the potential risk factor for severe knee OA progression over 30 months period. Once developed and validated in human knee joint, these studies will profoundly affect not only to diagnose OA in its earliest stages but also possibly identifies the risk population at early stage. We anticipate that the quantitative interactions among the cartilage, bone and marrow and their combined interactions may be useful to design a risk profile for knee OA progression rather than individual approach. We plan to address these close interactions between cartilage, bone and marrow in OA patients with external collaboration through subcontract (Dr. Punam Saha, Department of Electrical & Computer Engineering and Radiology, University of Iowa). The focus of the grant application is consistent with the mission of the NIBIB/NIAMS (NIH) bioengineering research grant (BRG) program.