Project 89: Smart Imaging-Based Functional Evaluation for Contemporary Arthroplasty
Contact Information:
Prof. Tsung Yuan Tsai
Email: tytsai@sjtu.edu.cn
Project Description and Objectives:
More than a million people in the US received primary total joint replacements in 2018. The demand for joint arthroplasty is rapidly growing each year. Although significant pain relief and improvement of the functional capacity have been observed in post-operative patients, the negative effects being a reduced range of motion, asymmetric gait pattern, and an inability to restore their normal joint kinematics are still prevalent. Advances in arthroplasty have largely focused on the development of improving implant tribology and implant fixation methods. However, the performance of contemporary arthroplasty is related to the adverse in-vivo dynamic phenomenon. This includes edge loading, wearing, impingement, and dislocation. Accurate knowledge of in-vivo joint dynamics is crucial for further improvement of arthroplasty. This project will include investigations on the bone geometry of Asian people. Statistical shape modeling will be used to extract ethnic characteristics. Non-invasive imaging tracking methods, including skin-marker-based motion analysis and dual fluoroscopic imaging tracking technique, will be employed to quantify accurate joint kinematics during daily functional activities. Subject-specific bone modeling and inverse dynamics will enable estimations of joint forces and moments. This study aims to compare the performance of contemporary total joint replacements and hopefully lead to innovations in arthroplasty.
Eligibility Requirements:
Interested students should have basic knowledge of human anatomy, computer vision, biomechanics, and MATLAB programming.
Main Tasks:
Collect a minimum of 10 subject’s CT, MRI, fluoroscopic or motion capture data.
Develop custom-made scripts and analyze the collected data.
Review relevant literature.
Finish a research report.
Website:
School: http://bme.sjtu.edu.cn/en/