Browsing by Author "Srinivaasappa Indira, Raj Dhanush"

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    Articular Surface Contact Parameters in High Tibial Osteotomy and Double Osteotomy: A Finite Element Approach
    (University of Waterloo, 2024-09-17) Srinivaasappa Indira, Raj Dhanush
    Osteoarthritis (OA) is a common joint disease characterized by the degeneration of articular cartilage, resulting in pain, stiffness, and reduced joint function. For knees affected with unicompartmental OA, High Tibial Osteotomy (HTO) is an effective surgical procedure to manage symptoms and slow disease progression. The surgery is performed by making an angled cut in the tibia and creating a wedge to realign the joint, shifting the load-bearing axis away from the affected compartment. For more severe deformities, a Double Osteotomy is performed, involving corrections in both the tibia and femur. These joint-preserving surgeries extend the life of the native knee and can often delay or prevent the need for partial or total knee replacement. Research indicates that the Medial Collateral Ligament (MCL) is strained during the osteotomy opening, which may lead to abnormal pressure distributions across the tibial plateau and affect the correction. However, it is unclear which osteotomy parameters influence this strain or the impact of additional or residual strain in the MCL on pressure distribution. This study aims to develop knee finite element models to simulate various osteotomy correction angles, including uncorrected, optimal correction, and over-correction, for open wedge HTO and double-level osteotomy to treat medial compartment OA. The primary goal is to investigate the contact force and pressure distribution across the tibial plateau at different simulated correction angles. Additionally, the study examines the strain in the MCL under various corrections to assess the effects of under-correction, optimal correction, and over-correction. A secondary objective is to evaluate the impact of partial and total release of the superficial MCL on force and pressure distributions across the tibial plateau. Finally, a double osteotomy procedure is simulated to determine contact parameters, with the results compared to those from HTO. The osteotomy cuts were modeled on 3D models of the tibia and femur using SolidWorks, then exported and meshed in Hypermesh. The models were subsequently transferred to Abaqus CAE, where they were assembled with the other knee components. A distributed load of 800N at the proximal surface of the femur was applied and boundary conditions were provided at the hip and ankle joints. Non-linear static simulations were performed to determine the contact forces, pressures, and stress distributions across the tibial plateau. The superficial MCL was modeled as non-linear spring elements in Abaqus, and the force in the MCL was quantified for various corrections. Additionally, a gradual release of the superficial MCL was simulated by removing the spring elements from the model, and the resulting contact parameters were determined. The results showed that the contact force on the medial compartment decreased by 3% for a 5° correction, while the contact force on the lateral compartment increased by 37%. A 20% rise in the contact force was observed on the medial tibial cartilage in the 7° correction model. Contact pressures in the medial compartment decreased with increasing correction angles and increased in the lateral compartment. A balanced distribution was noted at a 5° correction. The total MCL force increased from 187N in an uncorrected tibia to 410N in an overcorrected model, marking a 120% increase and causing a spike in the medial contact force for the overcorrected model. Reduction in medial compartment load distribution was observed after partial and total MCL release, suggesting that MCL release is a viable surgical option. For large corrections, double-level osteotomy offers a method to mitigate excessive stress on the medial compartment compared to a single osteotomy. The study demonstrated that FE models can be a useful tool for pre-planning procedures and predicting post-surgical outcomes.