Statistical Shape Models for the Planning of TKA Surgery

CT-based methods, such as robotic systems and patient-specific instrumentation (PSI), offer precise bone depiction, making them valuable for Total Knee Arthroplasty (TKA). However, they must be robust to the presence of cartilage, which is not easily visible on CT-scans. We present here a coupled bone and cartilage Statistical Shape Model (SSM) that predicts cartilage solely from bone shape. Four models were trained and tested for healthy and pathological patients, for both femur and tibia. Cartilage prediction results show good adaptability to the pathology as well as similar accuracy compared to the inter-observer MRI manual segmentation variability. This solution could be integrated in the planning of TKA surgeries to improve CT-based PSI and robotic systems.