Unicompartmental Knee Arthroplasty: Statistical modelling for the assessment of surgical technique, implant performance and patient selection
Lead Research Organisation:
University of Southampton
Department Name: Faculty of Engineering & the Environment
Abstract
Traditional methods of treatment for conditions such as arthritis of the knee involve physiotherapy and medication. However, when the condition becomes excessively painful for the patient, surgical intervention is undertaken. Movement of the natural knee joint involves the base of the femur bone articulating against the top of the tibia bone. The surfaces of these bones are covered by articular cartilage which allows smooth, pain free movement at the joint. The base of the femur and the top of the tibia have two surfaces or 'condyles'; in severe cases, the cartilage is worn away from both condyles, and they have to be replaced by a total knee arthroplasty (TKA). In some cases only one of the condyles is affected by arthritis, and yet both condyles are replaced in a TKA procedure. Unicondylar Knee Arthroplasty (UKA), which resurfaces only the affected side, is an alternative to TKA which is becoming an increasingly popular because of its improved functional outcome, favourable long term clinical results and the benefits of minimally invasive surgical techniques. In particular, UKA offers a more effective solution than TKA for more active patients with single compartment knee disease, because the mechanics of the knee are better preserved, and more functional anatomy is maintained. UKA also has advantage of rapid rehabilitation, short hospital stay, quicker operation and quicker recovery. Evidence suggests that revision of a UKA to a TKA results in performance similar to a primary TKA and has been reported to be an easier procedure than the typical revision TKA. However, despite this, UKA is still under-exploited as an alternative to TKA. This is partly related to perception issues, and partly to historically higher failure rates due to improper technique. Therefore, it is desirable to improve the understanding of how surgical technique impacts UKA performance and failure risks, to inform clinical decision-making for UKA with best-practice surgical technique.
Most attempts to assess the performance of a joint replacement computationally have involved a 'deterministic' approach, that is, a single implant is modelled in a single bone and a single load is applied. This represents only one possible situation, when potentially many thousands could exist. Recently, there has been a move to replace deterministic approaches with statistical approaches, which attempt to take into account all sources of variability in the system. For example, the performance of an implant in a series of bones under varying loads can be analysed. In this project, statistical approaches will be applied to analyse the performance of UKA. The research will utilise a 'statistical knee joint' based on a large library of bone CT scans. This statistical knee joint represents a wide population of patients into which the unicondylar implant will be implanted. Variations in surgical technique will be accounted for by altering the nature of the surgical cuts and positions of the surrounding soft tissue structures. In this way, a knowledge of how the surgical technique can affect implant performance, in how quickly it wears and how likely it is to loosen, can be ascertained. This knowledge will be used to develop a tool that can be used to guide surgeons on what aspects of their surgical technique need careful consideration when planning their surgery in order to achieve improved patient outcomes. Industry can also benefit from the tool as part of the implant design process. The performance of new and existing implants can be robustly evaluated rapidly at the design stage, and the number of physical tests required can be reduced dramatically. In addition, designs that are predicted to perform poorly can be eliminated at an early stage, leading to substantial cost and time benefits for the design process. The commensurate benefit of this tool will be more robust implants with a longer lifespan, benefiting both the patient and the healthcare provider.
Most attempts to assess the performance of a joint replacement computationally have involved a 'deterministic' approach, that is, a single implant is modelled in a single bone and a single load is applied. This represents only one possible situation, when potentially many thousands could exist. Recently, there has been a move to replace deterministic approaches with statistical approaches, which attempt to take into account all sources of variability in the system. For example, the performance of an implant in a series of bones under varying loads can be analysed. In this project, statistical approaches will be applied to analyse the performance of UKA. The research will utilise a 'statistical knee joint' based on a large library of bone CT scans. This statistical knee joint represents a wide population of patients into which the unicondylar implant will be implanted. Variations in surgical technique will be accounted for by altering the nature of the surgical cuts and positions of the surrounding soft tissue structures. In this way, a knowledge of how the surgical technique can affect implant performance, in how quickly it wears and how likely it is to loosen, can be ascertained. This knowledge will be used to develop a tool that can be used to guide surgeons on what aspects of their surgical technique need careful consideration when planning their surgery in order to achieve improved patient outcomes. Industry can also benefit from the tool as part of the implant design process. The performance of new and existing implants can be robustly evaluated rapidly at the design stage, and the number of physical tests required can be reduced dramatically. In addition, designs that are predicted to perform poorly can be eliminated at an early stage, leading to substantial cost and time benefits for the design process. The commensurate benefit of this tool will be more robust implants with a longer lifespan, benefiting both the patient and the healthcare provider.
Planned Impact
Benefits:
Academic: The research will result in the creation of a statistical shape model (SSM) and a statistical shape and intensity model (SSIM) of the knee joint (i.e. femur and tibia), which can be used by researchers to conduct similar statistical based approaches to prospectively assess the performance of the knee implant, be it UKA or TKA. The SSIM integrates bone material properties, bone geometry, ligament position and knee joint load into a single model, which has the potential to be extended to other projects involving the knee. For example, evaluating the performance of different designs of total knee replacement (TKR), or stress/strain distributions in the intact knee joint during different sporting activities. This will be the first time that SSIM and finite element analysis (FEA) will be co-implemented in the study of UKA. The outcome of this project will answer the uncertainties inherent in the UKA operation, for example, in relation to implant positioning or surrounding soft tissues. The project will develop new robust models for performance assessment of UKA, and the underlying data will facilitate the creation of a surgical tool for guidance on pre-operative planning. The experience gained from this and other related EPSRC funded research will underpin the creation of a centre of excellence for statistical research techniques in orthopaedic biomechanics for the UK. The research provides an excellent platform for the post doctoral researchers to launch their careers in an relatively underexplored yet increasingly important field.
Economic: Successful exploitation of the project will result in a reduction in the number of revision UKA operations, lower numbers of incapacitated patients and subsequent burden on health service. Failed UKA is often converted to a TKA. Through improved UKA performance, the likelihood of arthroplasty surgery intervention outlasting the patient is increased. Similarly, a reduced number of surgical procedures will result in a reduced amount of physiotherapy /post-operative care with associated costs to healthcare provider. A further benefit of the research is the development of a tool that can be easily incorporated into the implant design process industrially. The Bioengineering Group have previous experience in this area, having developed statistically based methods that have been utilised by DePuy Orthopaedics in the design process of their most recent knee prosthesis (see letter of support). Using such an informed and directed approach to implant development reduces costs to the manufacturer and avoids the need for unnecessary trials on poor implant designs.
Societal: A major outcome of this study will be improved quality of life for patients suffering from unicondylar arthritic conditions. Note also that some patients are given a total knee replacement irrespective of whether a UKA is sufficient to treat the affected knee due to lack of confidence in the UKA procedure. One of the drivers for this research is to highlight the factors that most influence the outcome of UKA. In providing a guide for surgeons, longer lasting implants, and hence, improved confidence in the UKA procedure, will result. Thus, patients will be able to remain active for longer and remain in employment. We will also be reaching out to the public through a wide range of outreach activities. Currently, we present our research annually at 6 school visit days and several residential courses, to around 200 GCSE and A-Level students (15-18 years), and to younger students (13-14 years) in the 'Meet the Scientist' programme. We hold public lectures and open days and will use these platforms to improve public awareness of the highly interdisciplinary orthopaedic engineering research being undertaken at Southampton, as well as the issues faced by surgeons, designers and engineers when evaluating implant performance.
Academic: The research will result in the creation of a statistical shape model (SSM) and a statistical shape and intensity model (SSIM) of the knee joint (i.e. femur and tibia), which can be used by researchers to conduct similar statistical based approaches to prospectively assess the performance of the knee implant, be it UKA or TKA. The SSIM integrates bone material properties, bone geometry, ligament position and knee joint load into a single model, which has the potential to be extended to other projects involving the knee. For example, evaluating the performance of different designs of total knee replacement (TKR), or stress/strain distributions in the intact knee joint during different sporting activities. This will be the first time that SSIM and finite element analysis (FEA) will be co-implemented in the study of UKA. The outcome of this project will answer the uncertainties inherent in the UKA operation, for example, in relation to implant positioning or surrounding soft tissues. The project will develop new robust models for performance assessment of UKA, and the underlying data will facilitate the creation of a surgical tool for guidance on pre-operative planning. The experience gained from this and other related EPSRC funded research will underpin the creation of a centre of excellence for statistical research techniques in orthopaedic biomechanics for the UK. The research provides an excellent platform for the post doctoral researchers to launch their careers in an relatively underexplored yet increasingly important field.
Economic: Successful exploitation of the project will result in a reduction in the number of revision UKA operations, lower numbers of incapacitated patients and subsequent burden on health service. Failed UKA is often converted to a TKA. Through improved UKA performance, the likelihood of arthroplasty surgery intervention outlasting the patient is increased. Similarly, a reduced number of surgical procedures will result in a reduced amount of physiotherapy /post-operative care with associated costs to healthcare provider. A further benefit of the research is the development of a tool that can be easily incorporated into the implant design process industrially. The Bioengineering Group have previous experience in this area, having developed statistically based methods that have been utilised by DePuy Orthopaedics in the design process of their most recent knee prosthesis (see letter of support). Using such an informed and directed approach to implant development reduces costs to the manufacturer and avoids the need for unnecessary trials on poor implant designs.
Societal: A major outcome of this study will be improved quality of life for patients suffering from unicondylar arthritic conditions. Note also that some patients are given a total knee replacement irrespective of whether a UKA is sufficient to treat the affected knee due to lack of confidence in the UKA procedure. One of the drivers for this research is to highlight the factors that most influence the outcome of UKA. In providing a guide for surgeons, longer lasting implants, and hence, improved confidence in the UKA procedure, will result. Thus, patients will be able to remain active for longer and remain in employment. We will also be reaching out to the public through a wide range of outreach activities. Currently, we present our research annually at 6 school visit days and several residential courses, to around 200 GCSE and A-Level students (15-18 years), and to younger students (13-14 years) in the 'Meet the Scientist' programme. We hold public lectures and open days and will use these platforms to improve public awareness of the highly interdisciplinary orthopaedic engineering research being undertaken at Southampton, as well as the issues faced by surgeons, designers and engineers when evaluating implant performance.
Organisations
- University of Southampton (Lead Research Organisation)
- Aurora Medical (Collaboration)
- Biomet, Inc (Collaboration)
- Depuy International (Collaboration)
- Stryker (United Kingdom) (Project Partner)
- Zimmer Biomet (United Kingdom) (Project Partner)
- Istituto Ortopedico Rizzoli (Project Partner)
- DePuy Synthes (International) (Project Partner)
- Zimmer (Switzerland) (Project Partner)
Publications
Bah MT
(2015)
Inter-subject variability effects on the primary stability of a short cementless femoral stem.
in Journal of biomechanics
Ehrig RM
(2019)
On intrinsic equivalences of the finite helical axis, the instantaneous helical axis, and the SARA approach. A mathematical perspective.
in Journal of biomechanics
Shi J
(2017)
An articulated statistical shape model of the lower limb
in Journal of Bone and Joint Surgery
Bah MT
(2015)
Exploring inter-subject anatomic variability using a population of patient-specific femurs and a statistical shape and intensity model.
in Medical engineering & physics
Description | Critical factors in the surgeon's operative technique that are most likely to determine the success of unicompartmental knee replacement have been identified. |
Exploitation Route | Surgeons may use the developed methodologies to adapt their surgical technique to minimise the risk of failure of the implant. This should lead to improved uptake of unicompartmental surgery, and this effort is being spearheaded by a co-I who is a key opinion leader in this field. |
Sectors | Digital/Communication/Information Technologies (including Software) Healthcare |
Description | The research has led to a number of public engagement and outreach activities, in particular, the University's science roadshow, where researchers go to public events and explain their findings to the general public, and the Smallpeice Trust activity, which is a residential course (the only Biomedical themed Trust activity) held annually at the University. The research has been presented to major orthopaedic manufacturers who are keen to use the methodologies in their development programmes new implant systems. A CASE award was funded to this end. The results and methods created in this project are being used in the development of a new orthopaedic device by a major company (details confidential at this time). The methodologies developed herein have supported the development of a novel disruptive implant for small joints being developed by Aurora Medical Ltd. |
First Year Of Impact | 2021 |
Sector | Education,Healthcare,Manufacturing, including Industrial Biotechology,Culture, Heritage, Museums and Collections |
Impact Types | Cultural Societal |
Description | (APRICOT) - Anatomically Precise Revolutionary Implant for bone Conserving Osteoarthritis Treatment |
Amount | € 3,253,045 (EUR) |
Funding ID | 863183 |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 09/2019 |
End | 09/2023 |
Description | TSB Towards Zero Prototyping |
Amount | £244,000 (GBP) |
Funding ID | 101881 |
Organisation | TSB Bank plc |
Sector | Private |
Country | United Kingdom |
Start | 09/2014 |
End | 09/2016 |
Title | Statistical modelling tool |
Description | We have developed a modelling environment that enables the response of the surrounding environment (bone, tissues) to the presence of an implant. It also enables the effect of surgical technique to be considered, allowing designers to create more reliable, robust implants. |
Type Of Material | Model of mechanisms or symptoms - in vitro |
Provided To Others? | No |
Impact | Supported a successful grant application. Used in the development of a new knee implant by a major orthopaedic company. |
Title | Data analysis |
Description | Using statistical analysis techniques, we have been able to create a population of thousands of possible femur and tibia geometries that enable us to assess how implants are likely to perform in a widely varying patient population. |
Type Of Material | Data analysis technique |
Provided To Others? | No |
Impact | We have used the model to support research with orthopaedic companies interested in developing new implants |
Title | Statistical modelling |
Description | A collection of CT scans has been converted into a database of computational models that describe the variation in bone geometry and density across a population of over 100 patients |
Type Of Material | Database/Collection of data |
Provided To Others? | No |
Impact | We have extended the database to produce thousands of possible patient bone geometries and densities using statistical modelling based on the original dataset |
Title | Virtual patient software |
Description | We are developing the models we have created further to allow rapid screening of potential implant designs to be undertaken in a population of 'virtual patients'. In this way, new designs can be assessed in a rapid and efficient manner - poor designs can be immediately eliminated rather than undergo extensive animal and clinical testing. The effect of surgical technique can be assessed in a similar 'virtual' environment. |
Type Of Material | Computer model/algorithm |
Provided To Others? | No |
Impact | Research is on-going and surgeons are evaluating the potential for this software. |
Description | Aurora Medical |
Organisation | Aurora Medical |
Country | United Kingdom |
Sector | Private |
PI Contribution | Collaboration on the development of pre clinical implant assessment software |
Collaborator Contribution | Access to design files, staff time and contacts |
Impact | Successful collaborative grant application, applying for further grants together. |
Start Year | 2013 |
Description | Depuy International Ltd |
Organisation | Depuy International |
Country | United Kingdom |
Sector | Private |
PI Contribution | Knowledge transfer - pre-clinical assessment techniques for their orthopaedic implants |
Collaborator Contribution | • Involvement and expertise of company employees • Access to design and clinical data • Materials, components and software support |
Impact | Development of statistically based methodology for performance prediction of orthopaedic implants. PhD sponsorship and journal papers. |
Description | Zimmer Biomet |
Organisation | Biomet, Inc |
Department | Biomet UK |
Country | United Kingdom |
Sector | Private |
PI Contribution | We are working in partnership with the company to assess the performance of their implants using computational and experimental methods. |
Collaborator Contribution | They have provided access to databases and implants for testing. |
Impact | The research has underpinned an ongoing collaborative research strategy between our group and the company being developed across the whole of their orthopaedic product portfolio. |
Start Year | 2014 |
Title | Virtual Patient Software |
Description | The techniques investigated in the project helped support the creation of a software that assesses the performance of orthopaedic implants by automatically implanting and analysing a number of critical metrics. |
Type Of Technology | Software |
Year Produced | 2017 |
Impact | Presentation of technology to a major orthopaedic company in February 2017. Company considering adopting technology for new projects. |
Description | Museum interactions |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Public/other audiences |
Results and Impact | The techniques developed in the project have been extended to analyse historic bones and create a 'travelling' exhibit that can be taken round to museums. A 3D printed diseased bone has been created and forms the centrepiece of an exhibit entitled 'stories from bones'. The general public, schools and other students can visit the museum and handle a lifelike replica of the bone and discover its story through an interactive tablet based program. |
Year(s) Of Engagement Activity | 2015 |
URL | http://generic.wordpress.soton.ac.uk/archaeology/2015/07/24/dayofarch-5/ |
Description | Orthopaedic Companies |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | Work was presented to a series of orthopaedic companies who were introduced to the technology, the benefits, and ways in which the technology could be implemented in their research and development were discussed. Regular conference calls with the companies now take place as they continue to monitor outcomes of the project. |
Year(s) Of Engagement Activity | 2015,2016,2017 |
Description | Smallpeice |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | Yes |
Geographic Reach | National |
Primary Audience | Schools |
Results and Impact | Demonstration on how statistical analysis can be used to delineate behaviour of a population based on their walking characteristics Increased interest in biomedical engineering from A level students, much improved application numbers in mechanical engineering (not explicitly down to this activity, but students on course tended to come to Southampton) |
Year(s) Of Engagement Activity | 2011,2012,2013,2014 |