Machine learning enhanced MRI assessment of clinical outcomes of stem cell therapy for cartilage repairs in osteoarthritis

Project ID: 2228cd1344 (You will need this ID for your application)

UCL Lead department: Division of Surgery and Interventional Sciences

Project Summary:

Stem cells therapy has shown promising results for repairing of cartilage defects. In this procedure, stem cells from patients’ bone marrow were harvested and transplanted back in the damaged cartilage defects in one stage procedure. The Royal National Orthopaedic Hospital (RNOH) is one of the leading centres in the world for repair of damaged cartilage in osteoarthritic joints. Currently, MRI is the only non-invasive modality for assessing the quality of repaired and regenerated cartilages. However, great divergence among MRI readings regarding the quality of regenerated cartilages sensitivity and specificity, often reported in the clinical practice. To accurately assess the quality of regenerated cartilage to predict the clinical outcome and adopt appropriate rehabilitation strategy to the patients is an unmet clinical need. This EPSRC DTP project will combine training and skill development to develop a machine learning protocol to enhance the assessment of clinical outcomes for patients who have received stem therapy for repairing and regeneration of injured cartilage. This project will lead to tangible and clinically relevant results for improving the assessment of stem cell therapy for cartilage regeneration. Subsequently, the results will be used to design personalized rehabilitation programme to improve the treatment outcome and quality life of the patients.