Unicompartmental Knee Arthroplasty: Statistical modelling for the assessment of surgical technique, implant performance and patient selection

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.

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.