Study of bone density changes for total shoulder arthroplasty with stemless implants

• Grant number: 24/05655-0
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• Start date: June 16, 2024
• End date: August 15, 2024
• Field of knowledge: Engineering - Mechanical Engineering - Mechanics of Solids
• Principal Investigator: Bruno Agostinho Hernandez
• Grantee: Rodolpho Gardenal Fabbre
• Supervisor: Sabina Gheduzzi
• Host Institution: Faculdade de Engenharia (FE). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil
• Institution abroad: University of Bath, England
• Associated to the scholarship: 23/14292-5 - Study of Bone Density Changes for Total Shoulder Arthroplasty with Stemless Implants, BP.IC

Abstract

Total shoulder arthroplasty (TSA) has become a common treatment for glenohumeral joint degeneration. However, the failure rate in this type of treatment is much higher compared to other joint treatments, mainly due to the high mobility and complex structural configuration of the shoulder. To reduce the number of failures, a new stemless prosthesis model has been developed. However, there are still issues with this new device, such as aseptic loosening and stress shielding. Therefore, this study aims, in collaboration with partner researcher centres, to conduct a comparative study of bone remodelling in total shoulder arthroplasty situations using Arthrex Eclipse and Mathys Affinis prostheses with finite element (FE) models. From tomographies, it will be possible to obtain CAD models of the humerus bone and prostheses. From these models, FE models will be developed to evaluate the behaviour of the implanted region, with and without both prostheses, under load forces, thus enabling a better understanding of the stress shielding phenomenon and the construction of a bone density map. We hope to understand more about bone remodelling and how implant design influences stress shielding protection and implant anchoring. Finally, we aim to create mathematical and computational models to help predict implant failures and develop better prostheses, improving the well-being and longevity of patients requiring this type of surgical intervention.