Project: A novel tool for personalized and socio-economically optimal treatment planning for patients with osteoarthritis

Acronym	DEEPMECHANOKNEE (Reference Number: ERAPERMED2019-331)
Duration	01/04/2020 - 31/03/2023
Project Topic	The aim: Osteoarthritis (OA) is a common joint disease affecting over 40 million Europeans. The number of patients with OA will increase by over 70% in developed countries during the next 20 years, while direct and indirect costs are estimated to increase by over 300%. The most cost-effective and helpful treatment for the disease would simply be prevention. Since the progression of OA is highly subject-specific, prevention of the disease can only become possible when the progression can be predicted for an individual patient. The primary aim of the DEEPMECHANOKNEE project is to develop a tool to predict the onset and progression of osteoarthritis in the knee joint tissues due to daily loading conditions. How to achieve the aim: This consortium will combine patient-specific motion analysis and computational modelling approaches with deep learning-based methods for OA diagnostics, personalized prediction and optimal treatment. Predictions will be validated against new measurements and clinical follow-up data obtained from several European and Transatlantic registers. Subsequently, these models will be employed to indicate directly and quantitatively the effects of particular interventions (e.g. conservative, surgical) for an individual patient. Quality of life and health economic outcomes will also be assessed. Relevance to the call: In the current aging population, high quality research to improve public health should focus more on prevention. DEEPMECHANOKNEE aims at this by providing an integrative multi-scale modelling workflow coupled with deep learning algorithms, which can indicate (optimize) the best possible personalized intervention for a patient that could ultimately prevent or delay the progression of OA. The treatment could be a changed lifestyle, physical activity, or a specific surgical intervention. The socio-economic impact of this approach is expected to be significant.
Network	ERA PerMed
Call	2nd Joint Transnational Call for Proposals (2019)

Project partner

Number	Name	Role	Country
1	University of Eastern Finland	Coordinator	Finland
2	Lund University	Partner	Sweden
3	University of Oulu	Partner	Finland
4	University of Copenhagen	Partner	Denmark