The absence of detailed knowledge regarding mechanical loading on knee structures inhibits our understanding of joint degeneration and injury. Information on the interrelationships between muscle activations and tissue response is crucial to the development of tissue engineered cartilage and menisci, meniscus and ligament injury and repair, and our understanding of degenerative joint disease, specifically osteoarthritis. Personalized prediction of joint and tissue level loading during ambulation has the potential to significantly enhance orthopedic medicine. In addition to providing a greater understanding of knee biomechanics and tissue function, tools with this capability would enable subject specific intervention strategies aimed at modifying gait for targeted outcomes, such as reducing articular cartilage stress. The goal of this work is to translate computational and experimental methods developed on canines and human cadavers to patient specific multiscale musculoskeletal models that concurrently simulate muscle forces and tissue level loading. To our knowledge, no simulation tool exists that incorporates body level neuromusculoskeletal function with articular cartilage tissue level parameters within a concurrent and computationally efficient framework. Innovations that will be employed for this work include: Body level muscle driven forward dynamic simulation with a natural knee, Anatomical and functional representation of the menisci within the multibody framework, Discrete body representation of articular cartilage, Surrogate models that predict tissue level stress from multibody inputs, In vivo characterization of ligament bundle zero-load lengths, and Custom localizers that register the medical imaging coordinate system to the motion capture coordinate system.
The Specific Aims of this project are: 1.) Produce subject specific multiscale musculoskeletal models of the leg with anatomical knee models that include the menisci and simultaneous prediction of cartilage level stress on three healthy female subjects, and 2.) Run dynamic multiscale simulations that combine gait measurements, forward dynamics muscle force prediction and subject specific knee models. Simulation outputs will include tibio-femoral articular cartilage contact pressures and von mises stress, meniscus contact pressures and ligament loading during a dual limb squat, walking and side- step maneuver.
The proposed work will translate previously developed computational and experimental methods to produce tools that predict patient specific loading on knee structures and tissues during ambulation. This technology would enable greater understanding of knee biomechanics and tissue function and enable personalized intervention strategies aimed at modifying gait to reduce stress on knee cartilage.
