Development and testing of patient-specific knee replacements

Abstract

This study presents a design methodology for designing and manufacturing patient-specific unicompartmental knee replacements. The design methodology uses mathematical modeling and an artificial neural network to predict the original and healthy articulating surfaces of a patient's knee. The models are combined with medical images from the patient to create a knee prosthesis that is patient-specific. These patient-specific implants are then compared to conventional implants with respect to contact stresses and kinematics. The patient-specific implant experienced lower contact stresses at the tibiofemoral joint compared to a fixed-bearing design. Both the UKRs showed similar kinematic patterns to the normal knee using two different test rigs. The patient-specific UKR showed good results and with the other benefits it shows potential to dramatically improve clinical outcomes of knee replacement surgery.