Technique and Application for Quantifying Dynamic Shoulder Joint Kinematics and Glenohumeral Joint Contact Patterns

The shoulder (glenohumeral) joint has the greatest range of motion of all human joints; as a result, it is particularly vulnerable to dislocation and injury. The ability to accurately measure dynamic in-vivo joint kinematics in 6-Degrees-of-Freedom (6-DOF) (translations and rotations) and subsequently quantify articular cartilage contact patterns of that joint has been and remains a difficult biomechanics problem. As a result, little is known about normal in-vivo glenohumeral joint contact patterns or the consequences of surgery on: shoulder joint kinematics, the soft tissue anatomy around the shoulder, and glenohumeral joint contact patterns. Additionally, the effect of quantifying glenohumeral joint contact patterns by means of proximity mapping, both with and without cartilage data is unknown. Therefore, the objectives of this thesis are to (1) describe and validate a noninvasive Dual Fluoroscopic Imaging System (DFIS) to measure dynamic shoulder joint motion; (2) describe a technique to quantify in-vivo glenohumeral joint contact patterns from the measured shoulder motion; (3) quantify normal glenohumeral joint contact patterns in the young healthy adult; (4) compare glenohumeral joint contact patterns determined both with and without articular cartilage data; and (5) demonstrate that the DFIS technique can evaluate the dynamic suprascapular nerve (a soft tissue around the shoulder) anatomy in 6-DOF in a proof of concept cadaveric model. Our results show that for the shoulder motion tested, glenohumeral joint contact was located on the anterior-inferior glenoid surface, and that the inclusion of articular cartilage data when quantifying in-vivo glenohumeral joint contact patterns has significant effects on the contact centroid location, the contact centroid range of travel, and the total contact path length. As a result, our technique offers an advantage over glenohumeral joint contact pattern measurement techniques that neglect articular cartilage data. Likewise, this technique may be more sensitive than traditional 6-DOF joint kinematics for the assessment of overall glenohumeral joint health. Lastly, in the proof of concept cadaveric model, we demonstrated that the DFIS technique can evaluate the dynamic suprascapular nerve anatomy in 6-DOF and that the anatomical course of the nerve may be altered by a rotator cuff tendon tear and subsequent to surgical intervention. Guoan Li, PhD Thesis Supervisor Professor of Orthopaedic Surgery, Harvard Medical School Peter T.C. So, PhD Committee Chair Professor of Mechanical and Biological Engineering, MIT Alan J. Grodzinsky, PhD Committee Member Professor of Electrical, Mechanical, and Biological Engineering, MIT Jon JP Warner, MD Clinical Advisor Professor of Orthopaedic Surgery, Harvard Medical School