Project description
AI steps toward knee osteoarthritis treatment
Knee osteoarthritis (KOA) affects around 14 % of Europeans over 40, with no cure or reliable prevention available. Current rehabilitation methods, based on indirect knee biomechanics, often fall short. However, the EU-funded CARE-KNEEOA project aims to change that. Supported by the Marie Skłodowska-Curie Actions programme, the project is developing personalised, AI-assisted computational models that predict knee cartilage degeneration and regeneration. These models, designed for clinical use, will be fast, automated, and capable of using out-of-lab motion data. By simulating knee mechanics in real-life activities, CARE-KNEEOA hopes to revolutionise KOA treatment, improving patient outcomes and potentially reducing the need for surgery.
Objective
Knee osteoarthritis (KOA) is a leading cause of disability worldwide, with ~14% prevalence in Europeans aged over 40. KOA prevalence continues to rise, thus far, with no cure or proven prevention protocols. Nonetheless, an aberrant knee mechanobiological environment is known to accelerate KOA development. Tailored rehabilitation, aiming to favorably alter knee biomechanics and restore the joint, has shown great potential to postpone or decelerate KOA progression. But current rehabilitation protocols are based on indirect measures of knee biomechanics, often leading to suboptimal outcomes. Computational models have offered great potential for simulating knee mechanical response in functional activities, though none are developed in a holistic and individualized context. More importantly, they lack the prediction capability of tissue degeneration/regeneration to loading and the potential for clinical use, i.e. are not automated and fast and cannot use out-of-lab motion data. In this project, I will develop and validate highly personalized in silico tools to quantify knee cartilage mechanobiological degenerative/regenerative response geared towards out-of-lab and clinical use for predicting KOA progression in different functional activities, allowing personalized rehabilitation. The multiphysics computational models, assisted with artificial intelligence (AI), will be validated at different spatial scales using in vitro tissue and cell level experiments and in vivo joint loading and quantitative medical images. This multidisciplinary project bridges together complementary skill sets of Dr. Esrafilian, Profs. Korhonen’s and Delp’s teams, with their expertise in biomechanics, computational modeling, biochemistry, biology, and AI. The beyond state-of-the-art models of this research can make a profound impact on early-stage KOA prediction and treatment planning, potentially increasing the quality of life in KOA individuals and reducing the need for surgical interventions.
Fields of science (EuroSciVoc)
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences biochemistry
- medical and health sciences clinical medicine physiotherapy
- natural sciences biological sciences biophysics
- natural sciences computer and information sciences computational science multiphysics
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships
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Call for proposal
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(opens in new window) HORIZON-MSCA-2022-PF-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
70211 KUOPIO
Finland
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.