Automatic Quantitative Analysis of MR Images of the Knee in Osteoarthritis

骨关节炎膝关节 MR 图像的自动定量分析

• 批准号: 8113619
• 负责人: Marc Niethammer
• 金额: $ 19.5万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8113619
• 关键词: Adult; Affect; Atlases; Brain; Cartilage; Cartilage injury; Clinical; Computer Analysis; Computer Assisted; Data; Data Analyses; Data Set; Databases; Degenerative polyarthritis; Development; Diagnostic radiologic examination; Diet; Disease; Early Diagnosis; Early identification; Etiology; Femur; Genetic; Hip Osteoarthritis; Human; Image; Image Analysis; Inflammation; Injury; Intervention; Joints; Knee; Label; Literature; Longitudinal Studies; Magnetic Resonance Imaging; Manuals; Measures; Methodology; Methods; Modality; Morphology; Pain; Patients; Pharmaceutical Preparations; Population; Process; Research; Software Tools; Stress; Symptoms; System; Thick; Three-Dimensional Image; Three-Dimensional Imaging; Time; United States; Width; arthropathies; base; bone; cost effective; disability; disabling disease; drug development; effective therapy; experience; imaging Segmentation; imaging modality; improved; innovation; novel; open source; population based; prevent; software development; success; tibia; tool

DESCRIPTION (provided by applicant): Osteoarthritis (OA) is the most common form of joint disease and a major cause of long-term disability in the United States (US). It is estimated that 2.5% of the adult population have symptomatic knee or hip OA. Over two-thirds of the 7.8 million OA patients in the US who seek treatment have moderate to severe joint involvement and would benefit from a therapy which arrests or delays cartilage loss. The etiology of OA is still partially unclear: While genetic factors are believed to underlie a significant proportion of OA cases, the majority of occurrences may not be genetically predetermined. OA is influenced by diet, body condition, or physical stress experienced (due to injury or overuse of a joint). Patient condition may therefore likely be improved or further progression prevented by an early identification of OA progression, combined with effective therapies. However, the current armamentarium of OA therapies merely relieves the inflammation and painful symptoms of OA but does not suppress the ongoing degenerative process. There is no known cure for osteoarthritis and further drug research is essential to help OA patients. Cartilage loss is believed to be the dominating factor in OA. While the standard radiography-based analysis method relies on joint-space width as a surrogate measure for cartilage thickness, an increasing body of literature supports the use of MRI as a primary imaging method to evaluate progression of osteoarthritis. MRI is able to directly measure cartilage volume and thickness. Being a three-dimensional imaging modality it allows, unlike x-ray projection images, for a localized analysis of imaging data in the full three-dimensional spatial context. Significant advances in MRI have resulted in the ability to quantify cartilage morphology and thereby provide a means to evaluate potential effects of pharmacologic intervention on OA progression. To aid drug development and to help subsequent regulatory approval, accurate, quantitative methods are needed to rapidly screen MR imaging data. To be time- and cost-effective, computer-assisted 3D image analysis is essential. However, most image-analysis methods for OA still require significant human intervention, precluding the comprehensive analysis of large databases as for example acquired by the Osteoarthritis Initiative. A strategy that has been beneficial in studies of the brain is the use of atlases to assist in data analysis. Following such success we propose the creation of population-based bone and cartilage atlases to facilitate bone and cartilage segmentation and to allow for localized data analysis by representing imaging data in a common anatomical coordinate system. We will use the developed methods to analyze cartilage thickness and to perform correlations with clinical variables. Developed software tools will be distributed in open-source form. PUBLIC HEALTH RELEVANCE: Osteoarthritis (OA) is a debilitating disease, with millions of people affected in the US alone. While large-scale OA studies by the Osteoarthritis Initiative and Pfizer have acquired a breathtaking wealth of data, a comprehensive analysis of the imaging data has proven difficult, due to the unavailability of robust, fully-automatic computer analysis methods. This project will develop such automatic image analysis tools to allow for the efficient extraction of quantitative measures from magnetic resonance images, to ultimately aid drug development to help patients afflicted by a disabling disease without a current cure.

描述（由申请人提供）：骨关节炎（OA）是美国联合疾病的最常见形式，也是美国长期残疾的主要原因（美国）。据估计，有2.5％的成人人群有症状的膝盖或髋关节OA。在美国寻求治疗的780万OA患者中，超过三分之二的人具有中等至重度的联合参与，并将受益于逮捕或延迟软骨损失的疗法。 OA的病因仍然部分不清楚：虽然遗传因素被认为是OA病例中很大一部分的基础，但大多数发生的情况可能不会在遗传上预先确定。 OA受饮食，身体状况或身体压力的影响（由于关节受伤或过度使用）。因此，可能会改善患者状况，或者通过早期鉴定OA进展，并结合有效疗法，从而改善或进一步进展。但是，目前的OA疗法的武器库仅减轻了OA的炎症和痛苦症状，但并不能抑制正在进行的退行过程。没有已知的骨关节炎治疗方法，进一步的药物研究对于帮助OA患者至关重要。软骨损失被认为是OA中的主要因素。基于标准的X射线照相分析方法依靠关节空间宽度作为软骨厚度的替代措施，但越来越多的文献支持将MRI用作评估骨关节炎进展的主要成像方法。 MRI能够直接测量软骨体积和厚度。作为三维成像方式，与X射线投影图像不同，它可以在整个三维空间上下文中对成像数据进行局部分析。 MRI的重大进展导致了量化软骨形态的能力，从而提供了一种评估药理干预对OA进展的潜在影响的方法。为了帮助药物开发并帮助随后的法规批准，需要准确的定量方法来快速筛选MR成像数据。时间和成本效益，计算机辅助的3D图像分析至关重要。但是，大多数OA的图像分析方法仍然需要大量的人为干预，从而排除了大型数据库的全面分析，例如骨关节炎倡议所获得的。一种对大脑研究有益的策略是使用地图集来协助数据分析。成功之后，我们提出了基于人群的骨骼和软骨图谱的创建，以促进骨骼和软骨分割，并通过在公共解剖坐标系统中表示成像数据来允许局部数据分析。我们将使用开发的方法来分析软骨厚度并与临床变量执行相关性。开发的软件工具将以开源形式分发。 公共卫生相关性：骨关节炎（OA）是一种使人衰弱的疾病，仅在美国就受到了数百万人的影响。尽管骨关节炎倡议和辉瑞的大规模OA研究获得了令人叹为观止的数据，但由于不可用，完全自动的计算机分析方法，对成像数据的全面分析被证明是困难的。该项目将开发此类自动图像分析工具，以允许从磁共振图像中有效提取定量措施，以最终帮助药物开发，以帮助因禁用疾病而无法治愈的残疾疾病患者。