Orthopaedic Digital Twins: Linking Cartilage Pressure to Osteoarthritis Progression

Motivation: Orthopaedic Digital Twins can compute tissue mechanics, with the potential to inform diagnoses and interventions. However, orthopaedic Digital Twins are not implemented clinically because the creation process is time-consuming and prone to error. Goal(s): Develop an automated Digital Twin pipeline and quantify how individual joint geometry affects knee cartilage pressures during gait. Approach: We developed a novel Neural Shape Model-based pipeline to create personalized Digital Twins for 150 subjects from the Osteoarthritis Initiative. Results: Automated Digital Twins showed: 1) regions of high cartilage pressure undergo the greatest cartilage thinning in osteoarthritis. 2) Osteoarthritis joint shape increases cartilage contact areas, thus decreasing cartilage pressure. Impact: Our fully automated Digital Twin estimates cartilage pressures during gait that relate to future cartilage thinning, and osteoarthritis progression. These findings indicate that Digital Twins have the potential to be implemented clinically, and hold promise for understanding and treating osteoarthritis.