Overview

Developing technologies and protocols for measuring knee osteoarthritis patients and performing in vitro and ex vivo experiments to obtain inputs for joint and tissue/cell-level models. 

We will use MRI and motion analysis to measure patient-specific geometries, muscle strength and overall movements. We will also develop two novel technologies that accurately quantify knee instability and mechanical properties. In vitro experiments will combine tissue overload with inflammatory cytokines to understand tissue degeneration. Ex vivo experiments in synchrotron facilities will calculate full-field strains within tissue and cells.

Creating a body-level model based on Newton’s laws alongside additional algorithmic approximations of how the Central Nervous System modulates movement. 

This model will be a musculoskeletal template with statistical parametric geometries designed for individual patient MRI scans. We will model the bones as rigid, the joints with elastic ligament and cartilage models, and the muscles with a Hill-type muscle model, basing the parameters on fitness tests, laxity profiles and unloaded and loaded MRI scans. Additionally, we will predict movement and forces using a novel method, considering passive and active joint stability mechanisms. We aim to include statistical movement pattern information to reduce solution space and quicken the simulations.

Predicting KOA progression by combining FEM with motion analysis and musculoskeletal and mechanobiological joint tissue modelling. The model will include subject-specific geometries of all tissues, mechanobiological degeneration mechanisms, and personalised knee joint contact. We will develop an atlas-based method to generate Finite Element meshes from MRI, subsequently creating an automatic implementation of the soft tissue material properties, enabling rapid, clinically feasible KOA progression predictions and a simulation of intervention efficacy.

Developing models that link tissue, cell action and inflammation to knee degeneration and damage. We will model load-dependent structural changes in ligaments, tendons, and the subchondral bone. Finally, we will integrate these models into a whole knee joint model.

Modelling the relationship between pain and biomechanical loading by developing a model focusing on pain as the input, modulated by the nervous system, with subjectively scored pain reports as output. 

We will merge multiscale models to estimate biomechanical loading for KOA patients, calibrating the model parameters based on the mechanistic pain profile, loading profile and subjective pain scores. We will then validate this data with experimental pain data from KOA patients, later utilising clinical evidence to predict pain after osteotomy, with preoperative mechanical pain and loading profiles as inputs.

Validating the model’s ability to predict immediate, short-term, medium-term and long-term outcomes by recruiting early-stage KOA patients eligible for conservative interventions, including knee bracing, wedged insoles and gait modifications. We will assess patient movement, cartilage loss and pain before and after the intervention(s). 

We will also use ACL patient data (those with KOA, at risk of KOA, or are eligible for  high tibial osteotomy), which we will collect at baseline and follow-up at 1, 2, and 5 years. Pre-intervention data will be fed to the model and used to predict the measured parameters at each point

Designing and optimising KOA interventions based on a mathematical model.

We will establish parametric versions of common early interventions, vary the input parameters to identify those that affect KOA progression the most and design a novel intervention to modify these parameters. 

MathKOA is a multi-national research centre led by Aalborg University in Denmark that focuses on developing the first-ever multifactorial, multiscale mathematical modelling of knee osteoarthritis. It comprises leading researchers from Aalborg University, Lund University, and the University of East Finland, along with several collaborators from Aalborg University Hospital and Massachusetts Institute of Technology. The centre has multiple research teams, each focusing on different research areas, and provides opportunities for students to collaborate and develop their skills.

MathKOA received DKK 50 million in funding from the Novo Nordisk Foundation’s Challenge Program on Mathematical Modeling of Health and Disease in 2021. The Novo Nordisk Foundation is an international enterprise foundation that supports scientific, humanitarian and social causes.

Osteoarthritis (OA) is a degenerative disease that affects human joints, most often in the hands, hips, knees and spine. It’s also a progressive disease that gradually worsens and causes chronic pain, swelling, stiffness, and a noticeably decreased range of motion, eventually leading to bone and joint deformities. These symptoms can make it difficult for OA suffers to do everyday activities such as walking, climbing, driving, or even getting out of bed in the morning. There is no known cure for osteoarthritis.

Osteoarthritis is caused by a degeneration of joint cartilage. Many factors can cause this degeneration, including ageing, injury, obesity, repetitive movement, and genetics. Manual workers and professional sportspeople who repeatedly place stress on their joints are more at risk.

Osteoarthritis can affect people of all ages, genders and races, but it is most common in people over the age of 65 and affects women more than men. However, osteoarthritis can affect teenagers and young adults, typically resulting from joint trauma or genetic factors.

Osteoarthritis is the most common form of arthritis alongside rheumatoid arthritis. Approximately 500 million people suffer from osteoarthritis worldwide, of which 50 million currently live in Europe. OA cases have risen by 113% over the past three decades.