The purpose of this work is to develop and validate a process for creating patient-specific simulations of total knee arthroplasty (TKA) with measurements of component alignment and initial soft tissue balance taken at the time of surgery. TKA is a common surgical procedure used to treat degenerative joint diseases such as osteoarthritis. An estimated 500,000 TKAs were performed in the United States in 2006, and approximately 3.48 million annual procedures are expected by the year 2030. While TKA is generally successful at relieving joint pain, some TKA recipients cannot perform basic activities of daily living such as comfortably climbing the stairs in their homes, and many find themselves unable to resume activities they love such as hiking, golfing, or playing tennis. The success of TKA depends on many factors including the pre-operative condition of the knee, alignment of the prosthetic components, management (or balancing) of soft tissues around the knee, and post-operative rehabilitation. Even though many surgeons have become skilled in developing a qualitative feel for knee stability as they manually manipulate the knee during surgery, how the knee feels is never documented, and an objective definition as to what constitutes acceptable post-operative stability does not exist. Computer simulations of the knee immediately following TKA have the potential to provide valuable insight into how component alignment and knee stability could affect a patient's ability to perform important functional tasks post-operatively. However, these simulations currently rely on generic descriptions of joints based on measurements made in cadaver specimens, or the simulations are heavily influenced by the properties of the ligaments that surround the knee, which are typically are modeled using archival data from the literature. Since the ligament properties and kinematics in an osteoarthritic knee are different from those of a healthy knee and may remain different following TKA, these assumptions make it impossible to predict the post-operative function of a given patient. Computer simulations which characterize the subject-specific component alignment, kinematics, and ligamentous properties of an individual patient represent an important step toward establishing an objective definition of a balanced knee and improving post-operative functional outcomes. This project will develop new patient-specific forward dynamic simulations of TKA. Aim 1 will develop a novel approach for creating patient-specific computer simulations through a series of TKAs on cadaver specimens with the assistance of a surgical navigation system and a custom device that can measure joint stability. We will use these recorded data to develop patient-specific forward dynamic simulations that determine ligament properties through an optimization routine and will explore the effect of ligament lengths, ligament material properties, and number of modeling elements in our optimization. We will then simulate an experimental supine passive range of motion test, the experimental characterizations of knee stability in our custom device, both performed with different trial tibial inserts, and a simulated active knee extension. The success of the approach will be based on the ability of the simulations to match experimentally measured tibiofemoral contact force, knee kinematics, and ligament forces of the same motions. In Aim 2, we will compare the accuracy of the subject-specific simulations developed in Aim 1 against the results of 3 other types of established musculoskeletal modeling techniques that prescribe joint kinematics and/or ligament properties with generic parameters from the literature. The results of the simulated values of knee kinematics, and contact and ligament forces that are generated from the 4 different modeling approaches will be compared against the same values that are recorded experimentally for the tests of passive and simulated active knee extension and the motions in the stability device. This comprehensive and rigorous study creates a process for developing patient-specific simulations of TKA patients based on component alignment and soft tissue balancing. This modeling approach can then be used to objectively parameterize surgical technique, specifically component alignment and initial soft tissue balance, and can be incorporated into future generations of surgical navigation systems to predict post- operative outcome from intra-operative measurements. Data from such patient-specific simulations will provide quantifiable guidelines that will enable surgeons to make better intra-operative decisions, help physical therapists to tailor rehabilitation programs to specific patients, and give patients more realistic expectations for their own specific outcomes.