Date of Award
Daniel Felix Ritchie School of Engineering and Computer Science, Mechanical and Materials Engineering
Biomechanics, Patient specific, Soft tissue, Surgical planning, Total hip replacement, Total knee replacement
This dissertation focused on modeling specimen-specific soft tissue structures in the context of joint replacement surgery. The research addressed four key aspects. The first study involved developing a workflow for creating finite element models of the hip capsule to replicate its torque-rotational response. Experimental data from ten cadaveric hips were used to calibrate the models, resulting in improved accuracy and relevance for surgical planning and implant design. The second study tackled the challenge of expediting the calibration of mechanical properties of the hip capsule to match patient-specific laxities. A statistical shape function model was proposed to generate patient-specific finite element models, demonstrating potential for instant modeling and potential use in improving outcomes in hip arthroplasty. The third study involved developing a computational model of an experimental knee simulator for simultaneous evaluation of tibiofemoral and patellofemoral mechanics. The model's predictions were verified against experimental measurements, providing a reliable computational tool for further studies. The fourth study investigated the influence of soft tissue balance and implant congruency on knee stability during daily activities. Finite element models were calibrated based on experimental data, perturbed for varying soft-tissue imbalance levels, evaluated for stability during the activities of daily living, thereby highlighting the impact of implant design on stability. The dissertation's findings contribute to the knowledge of surgical planning, implant design, and potentially enhancing outcomes in joint replacement surgeries.
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Ahilan Anantha Krishnan
Received from ProQuest
Anantha Krishnan, Ahilan, "Computational Methodology for Generating Patient-Specific Soft Tissue Representations" (2023). Electronic Theses and Dissertations. 2341.