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

Lead Research Organisation: University of Manchester
Department Name: School of Health Sciences

Abstract

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.

Technical Summary

This project aims to develop a computer-aided system to analyse radiographic signs of early joint failure in knee replacement surgery (KRS).

The software system to be developed will be based on the BoneFinderTM-technology (www.bone-finder.com) which uses machine-learning methods to automatically locate skeletal structures in radiographs. Based on a set of training data consisting of radiographs and feature point annotations, BoneFinderTM uses Random Forest-based shape model matching methods to locate the corresponding feature points in unseen images. BoneFinderTM has been applied to automatically outline knee joints in radiographs but further methodological development is required to account for disease and to incorporate implant detection.

For a given image, the automatically identified feature points will be used to quantify the knee bones and implant fitting. This will include conventional geometric measurements of lengths and angles but these only give a sparse representation of the structures. Statistical Shape and Appearance Models will be used to capture and quantify their overall shape and texture. Using retrospective data, machine-learning methods will be applied to combine the derived radiographic shape and appearance information of the knee joint with collected clinical data to analyse signs of early joint failure. This will lead to a computer-aided system that will have learned to identify radiographic indications of early joint failure based on radiographs and clinical data for any new subject, informing the KRS decision-making process.

A feasibility study will be conducted to identify the clinical requirements for usability and acceptability, and for the integration of the system into the clinical workflow. This will also include the identification of a suitable implementation strategy of the system into the existing digital healthcare infrastructure. The system will be validated during a pilot trial.

Publications

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Krishnakumar Raja VB (2019) A New Innovative Software to Automatically Outline Condyles In Orthopantomography in International Journal of Medical Science and Innovative Research

 
Description iTPA Access to Expertise Award (A2E) on Establishing a data sharing platform between clinicians and researchers for studying children's hip diseases
Amount £25,000 (GBP)
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 10/2020 
End 05/2021
 
Description iTPA Projects for Translation Award (P4T) on An Automated Software System for Monitoring Developmental Dysplasia of the Hip in Children
Amount £36,000 (GBP)
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 10/2020 
End 10/2021
 
Description Substudy-collaboration with Alder Hey Children's NHS Foundation Trust (AHFT) 
Organisation Alder Hey Children's NHS Foundation Trust
Country United Kingdom 
Sector Public 
PI Contribution We are developing methods and software to automatically assess the hips of children from radiographic images and related clinical data. We are publishing results at conferences and in journals.
Collaborator Contribution AHFT provides radiographic images and related clinical data as well as clinical expertise. AHFT sets up the technical infrastructure for facilitated data sharing between the University and the Trust. AHFT contributes to all publications.
Impact This is a multi-disciplinary collaboration (computer science, radiology, pediatric orthopaedic surgery) that has so far led to three grants as well as three conference publications. Our presentation at the Bone Research Society Annual Meeting 2020 was awarded the Best Clinical Poster Prize. As part of this collaboration we are currently establishing a data sharing platform between the University and the Trust which will be of benefit to any future research studies.
Start Year 2016
 
Description Substudy-collaboration with Materialise 
Organisation Materialise
Country Belgium 
Sector Private 
PI Contribution We have provided tools and expertise in automatically analysing skeletal structures in medical images.
Collaborator Contribution Materialise provided x-ray images and ground truth measurements as well as training on estimating the femoral offset and relevant clinical/commercial expertise.
Impact This is a multi-disciplinary collaboration (computer science, radiology, orthopaedic surgery). It has led to a joint MSc Medical Imaging Science research project for two students. One of the students completed the project with distinction and is currently being interviewed for starting a self-funded PhD within our group.
Start Year 2019
 
Description Substudy-collaboration with SRM Dental College & Hospital Chennai 
Organisation SRM Dental College
Country India 
Sector Academic/University 
PI Contribution We have developed a software system to evaluate the variation in morphology of the TMJ condyles in orthopantomogram (OPG) images.
Collaborator Contribution SRM provided the OPG images and the manual annotations of the outline of the TMJ condyles. The images and annotations were used to develop the system. SRM was leading on writing the journal paper.
Impact This is a multi-disciplinary collaboration (computer science, dentistry) that has resulted in one journal paper.
Start Year 2015
 
Description Substudy-collaboration with Salford Royal NHS Foundation Trust (SRFT) 
Organisation Salford Royal NHS Foundation Trust
Country United Kingdom 
Sector Public 
PI Contribution We are developing a software system for the fully automatic assessment of radiographic changes associated with diabetic foot collapse.
Collaborator Contribution SRFT provided radiographs of the foot as well as manual measurements of Meary's angle, calcaneal tilt and cuboid height. They also provided manual annotations of the outline of the bones of the foot in each of the radiographs. We use the images and annotations to develop the system, and the measurements to evaluate the system. SRFT also contributed to writing the journal paper.
Impact This is a multi-disciplinary collaboration (computer science, radiology, podiatry). We have been awarded an MRC DTP studentship for this project to be continued, and are currently drafting a journal publication for the initial results.
Start Year 2018
 
Description Substudy-collaboration with Stockport NHS Foundation Trust (SFT) 
Organisation Stockport NHS Foundation Trust
Department Stepping Hill Hospital
Country United Kingdom 
Sector Hospitals 
PI Contribution We are developing methods and software to automatically assess pre-/post-operative knee radiographs and related clinical data (including patient reported outcomes) of patients that underwent knee replacement surgery.
Collaborator Contribution SFT is providing the data as well as clinical expertise.
Impact This is a multi-disciplinary collaboration (computer science, orthopaedic surgery). We have so far collected over 18000 radiographic images of patients that underwent knee replacement surgery.
Start Year 2018
 
Description UMCU - Bonefinder 
Organisation University Medical Center Utrecht (UMC)
Country Netherlands 
Sector Academic/University 
PI Contribution We are building models to automatically locate the outlines of the bones in the hip and the knee in radiographs, and provide the models and software tools. We contribute to all publications.
Collaborator Contribution UMCU provides radiographs of the knee and the hip as well as manual bone outlines. UMCU uses the outlines for association studies and publishes the results at conferences and in journals.
Impact Three abstracts and two journal papers have been published so far.
Start Year 2014
 
Description NIHR Musculoskeletal Research User Group 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Patients, carers and/or patient groups
Results and Impact With regards to preparing a follow-on funding application, I presented my research to the NIHR-funded Musculoskeletal Research User Group (MSK RUG) at The University of Manchester. The meeting was attended by 13 members with a range of MSK conditions, of varying ages and from both genders.

The personal perspectives gained from discussions with the group members have broadened and enhanced my thinking around how to best involve patients in future studies. The meeting also informed the design of the research to be undertaken and led to the identification of MSK RUG group members for future involvement.
Year(s) Of Engagement Activity 2020
 
Description Presentation at STEM for BRITAIN 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Policymakers/politicians
Results and Impact I gave a poster presentation on "BoneFinder: An AI software tool to analyse X-ray images" at STEM for BRITAIN, Houses of Parliament, London, UK.

STEM for Britain is a poster competition and exhibition at the Houses of Parliament that aims (i) to encourage, support and promote Britain's early-career STEM researchers, and (ii) to foster dialogue and engagement between early-stage researchers and Members both in Westminster and in their Constituencies.
Year(s) Of Engagement Activity 2020
 
Description Presentation at Springer Nature Falling Walls Lab London 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Other audiences
Results and Impact I gave an oral presentation on "Breaking the walls of radiologist shortages" at the Springer Nature Falling Walls Lab London.

The Falling Walls Lab is a platform that enables the next generation of problem solvers to showcase their ground-breaking research and initiatives on the national and global stage.
Year(s) Of Engagement Activity 2019
 
Description STEM Exhibition 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Schools
Results and Impact In my role as STEM Ambassador, I have had a BoneFinder stall at the STEM Exhibition of Levenshulme High School (Manchester) to raise awareness of STEM subjects and to promote STEM careers to the students of this all girls school.
Year(s) Of Engagement Activity 2018,2019
 
Description STEM talks 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Schools
Results and Impact I am regularly giving STEM talks at local schools to raise awareness around STEM and to generate knowledge of STEM careers.
Year(s) Of Engagement Activity 2019,2020