Grant: Project Grant

The human shoulder is a joint consisting of a ball on the arm side of the joint, and a cup on the shoulder blade side. When a person seriously injures their shoulder joint, they can be left unable to lift their arm. For these patients, the only way to regain function is to undergo a shoulder replacement called Reverse Total Shoulder Arthroplasty (RTSA), whereby the above-described joint geometry is flipped; a cup-shaped implant is placed on the arm side of the joint, and a ball-shaped implant is placed on the shoulder blade side. Because of this, the anatomical landmarks that surgeons use to determine the best implant configuration during a traditional shoulder replacement are not effective. Therefore, the goal of this research is to develop the biomechanical understanding necessary to provide surgeons with an objective and quantitative surgical decision-making assistance tool to aid in the optimal planning of RTSA. This objective will be achieved in a number of phases. First, we will systematically analyze how the shapes of RTSA patients' shoulder bones differ from those of other patient groups. We will then develop computer models that can inform us of how RTSA patients' anatomy influences how different RTSA implant configurations affect how well their joint functions after surgery. Results of these computer modelling studies will then be used to develop the desired decision making assistance tool using machine learning techniques that will help surgeons customize their surgical plans to each of their patients.