The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee’s functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population. We used an active appearance model-based approach to segment the preoperative CT of 21 osteoarthritic patients, which identified the osteophyte-free surfaces and estimated cartilage from the segmented bones; these geometries were used to construct patient-specific musculoskeletal models of the pre-diseased knee. Subsequently, implantations were simulated using the MA method, and a previously developed optimization technique was employed to find the optimal implant position that minimized the root mean square deviation between pre-diseased and postoperative ligament strains and kinematics.Aims
Methods
Tibial slope was shown to majorly affect the outcomes of Total Knee Arthroplasty (TKA). More slope of the tibial component could help releasing a too tight flexion gap in cruciate-retaining (CR) TKA and is generally associated with a wider range of post-operative knee flexion. However, an excessive tibial slope could jeopardize the knee stability in flexion. The mechanism by which tibial slope affects the function of CR-TKA is not well understood. Moreover, it is not known whether the tibial bone resection should be performed by referencing the anterior cortex (AC) of the tibia or the center of the tibial plateau (CP) and whether the choice of either technique plays a role. The aim of this study was to investigate the effect of tibial slope on the position of tibiofemoral (TF) contact point, knee ligament forces, quadriceps muscle forces, and TF and patellofemoral (PF) joint contact forces during squat activity in CR-TKA. A previously validated musculoskeletal model of CR-TKA was used to simulate a squat activity performed by a 86-year-old male subject wearing an instrumented prosthesis [1,2]. Marker data over four consecutive repetitions of a squat motion were tracked using a motion optimization algorithm. Muscle and joint forces and moments were calculated from an inverse-dynamic analysis, coupled with Force-Dependent Kinematics (FDK) to solve knee kinematics, ligament and contact forces simultaneously. The tibial slope in the postoperative case was 0 degree and constituted the reference case for our simulations. In addition, eight additional cases were simulated with −3, +3, +6, +9 degrees of tibial slope, four of them simulating an AC referencing technique and four a CP technique.Introduction
Methods
The burden of Musculoskeletal (M-S) diseases and prosthetic revision operations is huge and increasing rapidly with the aging population. For patients that require a major surgical intervention, procedures are unsafe, uncertain in outcome and have a high complication rate. The goal of this project is to create an ICT-based patient-specific surgical navigation system that helps the surgeon safely reaching the optimal functional result for the patient and is a user friendly training facility for the surgeons. The purpose of this paper is to demonstrate the advancements in personalized musculoskeletal modeling for patients who require severe reconstructive surgery of the lower extremity. TLEMINTRODUCTION
METHODS
