Assessment of Total Knee Replacement Performance Using Muscle-Driven Dynamic Simulations
Open Access
- Author:
- Hast, Michael W
- Graduate Program:
- Mechanical Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- April 19, 2011
- Committee Members:
- Stephen Jacob Piazza, Dissertation Advisor/Co-Advisor
Stephen Jacob Piazza, Committee Chair/Co-Chair
Andris Freivalds, Committee Member
Matthew B Parkinson, Committee Member
Henry Joseph Sommer Iii, Committee Member - Keywords:
- computational simulation
total knee replacements - Abstract:
- The goal of a total knee replacement (TKR) procedure is to alleviate pain caused by the degradation of cartilage in the knee, and to restore normal knee function for an extended period of time. Modern TKR has proven to be a safe and e ffective means to restore the quality of life for patients, and the number of TKR procedures performed per year continues to rise. The motivation of this dissertation was the eff ective use and development of novel muscle-controlled dynamic simulations of TKR that can characterize knee joint loads. The first study involved the use of a previously developed dynamic elastic foundation model of an "Oxford Rig." The Oxford Rig is a commonly used cadaveric jig that simulates loaded knee flexion under quadriceps control. Undesirable collateral ligament laxities were introduced into the knee joint, and the model was utilized to predict the kinetic and kinematic eff ects of a surgical method, called joint line elevation, that is commonly used to address ligament laxity. The result of these simulations concurred with guidelines that have been qualitatively established through years of clinical experience. The second study used the same Oxford Rig simulation to investigate an alternative surgical method that is used to address collateral ligament laxity, called femoral upsizing. To date, the mechanical implications of mismatching femoral and tibial component sizes has received little attention. The results of this study suggested that the magnitude of collateral ligament laxity should be indicative of the method used to address collateral ligament laxity. Specifi cally, if ligament laxity is mild it is suggested that femoral upsizing should be avoided, but if more moderate or severe ligament laxity is encountered, a combination of femoral upsizing and joint line elevation should be employed. The third study augmented the Oxford Rig model to investigate the eff ects of changing the fixation point of linear displacement quadriceps actuators. A review of the literature revealed that many labs are using Oxford Rigs to investigate TKR mechanics, but the location of the quadriceps actuator has varied from lab to lab. It was found that the fi xation point of the quadriceps actuator had influence over the joint loads within the knee, but the kinematics of the knee joint were relatively unaff ected by changes in actuator position. The fi nal study developed a novel methodology to predict tibiofemoral contact forces during gait. The accurate simultaneous prediction of muscle forces and tibiofemoral contact forces continues to be a challenging task for researchers,and is the goal of the "Grand Challenge Competition to Predict In Vivo Knee Loads," hosted by the ASME Summer Bioengineering Conference. To address this challenge, we developed an dynamic elastic foundation model that employed a dual-joint paradigm to represent the knee joint, and incorporated in vivo kinematics and EMG data as inputs. The simulations provided kinematics, muscle forces, and tibiofemoral contact forces that compared well with data collected from an instrumented implant. In conclusion, this dissertation described several novel computational simulations that were used to investigate TKR kinematics and kinetics during dynamic activities. These simulations have the potential to be used by surgeons to elucidate the eff ects of choices made within the operating room, and by implant designers to evaluate implant designs before they are put into production. Although TKR is e ffectively restoring the quality of life to many patients, the post operative function of the implants can be improved with computer models by optimizing surgical techniques and by streamlining the implant design cycle.