Main Objectives

The aim of this project is to minimize the risk of failure of joint surgery by developing an ICT-environment that will enable the safe management of joint surgery throughout all stages of joint degeneration, including joint replacement, with a focus on minimizing the key risks of failure that result from mechanical overload and instability. Although the local mechanical conditions in a joint can be determined using highly detailed, integrated finite element and musculoskeletal models, a patient specific assessment of the risks of mechanical overload and instability is currently not possible from clinically available X-rays alone. Furthermore, the individual functional competence of the dynamic musculoskeletal system has not been routinely integrated in a quantitative prediction of the outcome of joint surgery.

MXL will therefore implement an ICT framework that helps to identify a safe route to optimal functional outcome in which clinically available X-rays form the basis to derive multilevel biomechanical models, to be enhanced with musculoskeletal competency data derived from explicit clinical tests, thus providing patient-specific models for identifying a safe surgical strategy to minimize the risk of failure of joint surgery, as well as deliver optimal joint function and joint longevity.

By facilitating the collection of clinical and research data, by involving clinical, biomechanical, management and IT specialists, and by developing and providing a validated framework for allowing the accurate prediction of clinical outcome, MXL will deliver a descriptive, integrative and predictive ICT-environment that allows the inclusion of essential biomechanical information into the surgical decision making process to enable the identification of a safe route to optimal functional outcome, independent of the surgeon’s prior experience and training. This innovative ICT approach to health care guarantees wide spread access for patients undergoing joint surgery to this new dimension in the quality of personalized care and thereby addresses a key challenge of our ageing society.

Technical Objectives

  • Generation of virtual 3D anatomical models from standard 2D clinical radiographs: Develop an IT system that is able to generate virtual 3D anatomical models from patient’s 2D X ray images. This enabling technology will enhance the image data available from standard X-rays of e.g. a hip joint by generating virtual anatomical models of the complete musculoskeletal system (bones, ligaments, tendon and muscles) of the upper or lower limb, currently only possible through a combination of CT and MRI images. These virtual anatomical models of the bones and the relevant soft tissue structures will provide the necessary geometric data to generate biomechanical models for surgical planning tools.
  • Surgical planning environment: Based on reconstructed virtual anatomical models, biomechanical models, which integrate musculoskeletal (MS) models with finite element (FE) analysis, will be generated to form the basis of an ICT framework for the planning for joint surgery of the knee, hip and shoulder. The musculoskeletal models of the complete upper or lower limb will provide the forces and motions across an individual joint and these will be applied to the finite element models, in order assess the local mechanical environment in the tissues. The models will supply measures of the risk of joint overload and instability, in particular joint range of motion (MS only), kinematics (MS and FE) and bone strains and, where relevant, initial implant fixation (FE). As a result we will form a direct link between widely available patient’s X-rays and advanced computational biomechanical techniques to quantify the risk of joint failure.
  • Surgeon Training (ST) environment: A key benefit of the software system developed in Objective 1 is to form the foundations of a surgeon training module. The objective is to develop a training package that would enable a medical surgeon, trainee surgeon or consultant to work through a series of cases, of increasing complexity, to plan, execute and then assess the impact of their decisions on the outcome of surgery.
  • Targeted patient recruitment (PR) tool: Currently, cohort selection for the evaluation of drugs targeted to address joint degeneration or the assessment of new tissue engineering approaches does not have access to, and can therefore not take into account, objective and quantitative data characterising the mechanical conditions and dynamic musculoskeletal competence of the patient. Using the technology developed in Objectives 1 and 2, it will be possible to better guide recruitment of subjects to cohorts in a manner that ensures balanced distribution of musculoskeletal competence of the patients, as well as their degree of joint overload and instability in both treatment and control groups. By controlling for these key initiators of onset and modulators of progression of joint degeneration, the number of patients required to show significant group effects should be minimized, to therefore reduce the number of patients exposed to additional treatment risks.
  • Improve the quality of life for patients after joint surgery - Our objective is to reduce the risk of failure of joint surgery by improving the clinical practice and surgical decision making processes. This will consequently. improve joint performance and reduce the pain suffered by the patient. More specifically, our objectives are to:
    1. Reduce the rate of early progression to joint degeneration after joint preserving surgery of the large joints (including e.g. ligament reconstruction, osteomies) by up to 50%.
    2. Reduce the rate of early failure due to joint instability for the high volume replacement joints (hips & knees) by up to 50%.
    3. Increase the longevity of hip & knee joint replacements by an aspirational value of 5 years.
    4. Improve minority joint (shoulder, elbow, ankle) revision surgery rate (e.g. reduce the should revision rate by 50%) hence increase the clinical acceptance of these much needed minority procedures.
    5. After the end of MXL, apply the MXL ICT framework to assess mechanical overload and instability for enabling a thorough monitoring and assessment of patient safety in novel, tissue engineering approaches to joint preserving surgeries in the context of regenerative medicine.
  • Reduce the cost of joint revision to EU healthcare services by €689 million p.a. by 2020 - see section “ Reduced failure rate of joint surgery” for details on our cost analysis and the role that the MXL project will play in reducing the projected annual cost of failed joints of €6.0 Billion per year for the EU healthcare services.

State of the Art

The relevant state-of-the art for the MXL concept involves a number of disciplines and a large quantity of prior work. For the sake of brevity we will focus on the directly relevant State-of-the-Art as grouped in to the following key areas:

  • Computerised description & modelling of human anatomy – methods used to understand the complexities of individual human anatomy, the musculoskeletal system and what to do when problems occur;
  • Computational methods to determine the dynamic interaction of the structures of a joint – by complementing and taking the above anatomical modelling a stage further, this is how the biomechanical properties of human tissues interact with functional control mechanisms, to determine biomechanical conditions at the tissue, organ, and system level, also in the presence of an implant or prosthesis;
  • Biomechanical analysis in a clinical setting – the ICT methods required to obtain key patient data to better understand the patient conditions and then diagnose, predict and plan for that patient in the clinical setting;
  • Assessment of patient specific musculoskeletal competence and outcome – the practice of obtaining hard facts regarding the performance of a human subject at the system level, including data regarding specific musculoskeletal competence and functional outcome.




The MXL project has been partially funded by

European Commission Seventh Framework Programme (FP7)



Prof. Markus Heller

Bioengineering Sciences Research Group

School of Engineering Sciences

University of Southampton

Highfield, Southampton

United Kingdom

Email : M.O.Heller@soton.ac.uk