Finite Element Modeling of Patient-Specific Total Shoulder Arthroplasty

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Abstract

Total Shoulder Arthroplasty (TSA) is a surgical procedure designed to improve joint functionality by replacing the articulation between the humeral head and the glenoid fossa. Anatomic Total Shoulder Arthroplasty (aTSA) and Reverse Total Shoulder Arthroplasty (rTSA) are two types of replacement surgery to relieve pain and restore function of the shoulder. The overall goal of this study was to evaluate the effects of variation of certain patient and implant alignment parameters that may influence longterm outcomes of these surgical procedures, including kinematics, joint loads and contact mechanics. Computational models of six TSA subjects, three aTSA and three rTSA, were created using subject-specific kinematics captured through high-speed stereo radiography (HSSR) during the abduction and forward flexion activities. Results showed the crucial role of patient-specific kinematics for obtaining accurate results, as a minor change in the kinematics considerably impacted the outputs of the models. Moreover, this study provided valuable insight regarding the impact of misalignment of the humeral stem and glenoid implants, highlighting the importance of carefully considering humeral version alignment, as higher version rotations can lead to a considerable decrease in the stability of the glenoid implant. This work emphasized the importance of patient specificity in computational modeling and has the potential to inform surgical planning to improve implanted joint mechanics and potentially patient outcomes.

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