Versus Arthritis Centre for Sport, Exercise and Osteoarthritis
University of Nottingham
  

Computational Modelling of the Morphological and Dynamic Changes Associated with Knee Osteoarthritis (OA) to Stratify Patients and Better Target Treatments 

Overview:

Recent developments in modern multibody modelling have demonstrated the ability to predict realistic joint contact forces, and to model adaptations to physiological changes such as weakening of muscles and morphological variation. Multibody modelling offers the potential to refine computational models to include muscle inputs and to explore computationally the effects on knee joint function and subsequently, knee replacement implant performance. Outputs from such modelling adaptations may help understand how abnormal loading at the knee joint could contribute to osteoarthritic changes.   

Traditional analysis of walking is often used to measure functional changes in patients. Recent research has shown the importance of increasing the demand on the patient beyond simple walking gait. The research will focus on analysing activities of daily living (e.g. stair ascent/descent) undertaken by people with knee OA to help understand the broader functional impact of OA and weaknesses associated with OA.  

Further to the advancement in modelling techniques, stratification of patient characteristics (e.g. age, BMI, morphology, movement strategies) can identify more specific groups with differing outcome trajectories. Through these stratification techniques targeted treatments can also be developed. 

Aims and Objectives:

  • The overall aim of this project is to produce a multibody computational model of the knee including real-world pathological inputs and to explore the effects of altered muscle function on knee mechanics.  

  • To explore the muscle weakness related to developing OA and muscles weaknesses association with knee function pre and post arthroplasty.  

  • To identify metabolic output changes in patients with OA and joint replacements. 

 
Work Package Early Disease and Risk Prediction: Prevent
Objective   1.3
Investigators Anthony Redmond, David Lunn 
Institution  University of Leeds

 

red shoes walking up stairs - D Lunn 240x150