Fully automated system for the analysis of the efficacy of knee replacement surgery

用于分析膝关节置换手术疗效的全自动系统

• 批准号: MR/S00405X/1
• 负责人: Claudia Lindner
• 金额: $ 30.1万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FS00405X%2F1
• 关键词: Fully; automated; system; analysis; efficacy

Musculoskeletal (MSK) diseases affect about 16% of adults and more than 30% in the age group 65+. As the incidence of most MSK diseases increases with age, the socio-economic impact of MSK diseases is increasing steadily in countries with an ageing population such as the UK. During 2014-2016, more than 260,000 primary knee replacement surgery (KRS) procedures were performed in England, Wales and Northern Ireland. KRS may, in the short or long run, lead to complications that will require a revision KRS and may result in life-threatening conditions (e.g., caused by a loose implant). Currently, the risk of KRS failure is 11% ten years post-operatively. When a KRS fails it is important to schedule a revision KRS to remove a loose or damaged implant before irreversible harm is done to the knee joint.There are an increasing number of medical images being gathered in all UK NHS hospitals, with the growing need and opportunity to utilise this information to improve the health of the nation. Currently, medical images are underutilised in clinical practise and research into MSK diseases where 2D radiographs are the imaging technique of choice due to wide availability, speed of acquisition and low cost.The aim of this project is to develop an automated software system to study the effectiveness of KRS. The system will automatically locate the knee joint in radiographs and analyse the radiographic shape and appearance of the knee bones or implant. It will then combine the obtained image-based data with clinical data aiming to predict and identify signs of early joint failure. The goal is to transform clinically collected image data into useful medical information to benefit healthcare at individual and societal levels. Various clinical placements will be undertaken to identify clinical needs and analyse the clinical workflow in KRS decision-making. This involves finding answers to questions such as how can the current workflows be revised to fit a new software system. Working closely with the Connected Health Cities project will provide details on how to technically implement such a system into the existing digital healthcare infrastructure. The collected information will be used to inform a suitable design (e.g., graphical user interface) and implementation strategy for the system to be integrated in the clinical setting. The software system will be validated at various stages of the development cycle to ensure that it fits the purpose. The usability and acceptability of the system will be evaluated during a pilot trial towards the end of the project. This research will result in a computer-aided system to inform the KRS decision-making process and the resulting medical management, improving the quality of care in clinical practice.In the long-term, this project aims to improve the health of the general population through a greater understanding of early joint failure in KRS, and by providing a computer-aided system for identifying and monitoring the latter in clinical practice. This work will have a positive impact on: (i) patients, who will benefit from better treatment choice and management, leading to improved quality of care; (ii) clinicians, who will have access to additional data to make an informed decision and who will save time by using an automated system to generate such data; (iii) the healthcare system, which will benefit from cost reductions; and (iv) the wider research community, where newly developed imaging and data modelling methods will contribute to advancements in other areas of automated image analysis as well as large scale data analysis.

肌肉骨骼（MSK）疾病影响约16%的成年人和超过30%的65岁以上的年龄组。由于大多数MSK疾病的发病率随着年龄的增长而增加，MSK疾病的社会经济影响在人口老龄化的国家（如英国）稳步增加。2014-2016年期间，在英格兰、威尔士和北方爱尔兰进行了超过26万例初次膝关节置换手术（KRS）。KRS可能在短期或长期内导致需要翻修KRS的并发症，并可能导致危及生命的疾病（例如，由松动的植入物引起）。目前，术后10年KRS失败的风险为11%。当KRS失败时，重要的是要计划翻修KRS，以在对膝关节造成不可逆转的伤害之前移除松动或损坏的植入物。在所有英国NHS医院收集的医学图像数量越来越多，利用这些信息来改善国民健康的需求和机会越来越多。目前，医学图像在临床实践和MSK疾病的研究中未得到充分利用，其中2D射线照片是首选的成像技术，由于广泛的可用性，采集速度和成本低。本项目的目的是开发一个自动化软件系统，以研究KRS的有效性。该系统将在X光片中自动定位膝关节，并分析膝骨或植入物的X光片形状和外观。然后将联合收割机将获得的基于图像的数据与临床数据相结合，旨在预测和识别早期关节衰竭的迹象。其目标是将临床收集的图像数据转换为有用的医疗信息，以使个人和社会层面的医疗保健受益。将进行各种临床实习，以确定临床需求并分析KRS决策中的临床工作流程。这涉及到寻找问题的答案，例如如何修改当前的工作流程以适应新的软件系统。与互联健康城市项目密切合作，将提供有关如何在现有数字医疗基础设施中技术上实施此类系统的详细信息。收集的信息将用于通知合适的设计（例如，图形用户界面）和系统在临床环境中集成的实施策略。软件系统将在开发周期的各个阶段进行验证，以确保其符合目的。该系统的可用性和可接受性将在项目结束时的试点试验期间进行评估。这项研究将产生一个计算机辅助系统，为KRS的决策过程和由此产生的医疗管理提供信息，提高临床实践中的护理质量。从长远来看，该项目旨在通过更好地了解KRS的早期关节衰竭，并通过提供一个计算机辅助系统来识别和监测后者在临床实践中，以改善普通人群的健康。这项工作将对以下方面产生积极影响：（一）病人，他们将受益于更好的治疗选择和管理，从而提高护理质量;（二）临床医生，他们将能够获得更多的数据以作出知情决定，并将通过使用自动化系统生成此类数据来节省时间;（三）保健系统，他们将受益于成本降低;以及（iv）更广泛的研究界，其中新开发的成像和数据建模方法将有助于自动化图像分析以及大规模数据分析的其他领域的进步。

项目成果

Medical Image Computing and Computer Assisted Intervention - MICCAI 2022 - 25th International Conference, Singapore, September 18-22, 2022, Proceedings, Part V

医学图像计算和计算机辅助干预 - MICCAI 2022 - 第 25 届国际会议，新加坡，2022 年 9 月 18-22 日，会议记录，第五部分

• DOI: 10.1007/978-3-031-16443-9_1
• 发表时间: 2022
• 作者: Ebsim R

Computational Methods and Clinical Applications in Musculoskeletal Imaging - 6th International Workshop, MSKI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers

肌肉骨骼成像中的计算方法和临床应用 - 第六届国际研讨会，MSKI 2018，与 MICCAI 2018 联合举行，西班牙格拉纳达，2018 年 9 月 16 日，修订后的精选论文

• DOI: 10.1007/978-3-030-11166-3_2
• 发表时间: 2019
• 作者: Blanco N

Osteophyte size and location on hip DXA scans are associated with hip pain: findings from a cross sectional study in UK Biobank

髋部 DXA 扫描上骨赘的大小和位置与髋部疼痛相关：英国生物银行横断面研究的结果

• DOI: 10.1101/2021.04.26.21255905
• 发表时间: 2021
• 作者: Faber B

Detecting Perthes Disease and Investigating the Effects of Aging on Hip Shape in Children

检测 Perthes 病并研究衰老对儿童髋部形状的影响

• 发表时间: 2020
• 作者: Davison AK

A GENOME WIDE ASSOCIATION STUDY OF DXA-DERIVED MINIMUM JOINT SPACE WIDTH OF THE HIP PROVIDES FURTHER INSIGHTS INTO ITS GENETIC ARCHITECTURE: FINDINGS FROM UK BIOBANK

对 DXA 得出的髋关节最小关节空间宽度进行的全基因组关联研究为其遗传结构提供了进一步的见解：英国生物银行的发现

• DOI: 10.1016/j.joca.2022.02.051
• 发表时间: 2022
• 期刊: Osteoarthritis and Cartilage
• 影响因子: 7
• 作者: Faber B