Importance of a three-dimensional measure of humeral head subluxation in osteoarthritic shoulders.

HYPOTHESIS: During total shoulder arthroplasty (TSA), humeral head subluxation may be difficult to manage. Furthermore, there is a risk for postoperative recurrence of subluxation, affecting the outcome of TSA. An accurate evaluation of the subluxation is necessary to evaluate this risk. Currently, subluxation is measured in 2 dimensions (2D), usually relative to the glenoid face. The goal of this study was to extend this measure to 3 dimensions (3D) to compare glenohumeral and scapulohumeral subluxation and to evaluate the association of subluxation with the glenoid version. MATERIALS AND METHODS: The study analyzed 112 computed tomography scans of osteoarthritic shoulders. We extended the usual 2D definition of glenohumeral subluxation, scapulohumeral subluxation, and glenoid version by measuring their orientation in 3D relative to the scapular plane and the scapular axis. We evaluated statistical associations between subluxation and version in 2D and 3D. RESULTS: Orientation of subluxation and version covered all sectors of the glenoid surface. Scapulohumeral subluxation and glenoid version were highly correlated in amplitude (R(2) = 0.71; P < .01) and in orientation (R(2) = 0.86; P < .01). Approximately every degree of glenoid version induced 1% of scapulohumeral subluxation in the same orientation of the version. Conversely, glenohumeral subluxation was not correlated to glenoid version in 2D or in 3D. CONCLUSIONS: Orientation of the humeral subluxation is rarely within the arbitrary computed tomography plane and should therefore be measured in 3D to detect out-of-plane subluxation. Scapulohumeral subluxation and glenoid version measured in 3D could bring valuable information for decision making during TSA.

A musculoskeletal shoulder model based on pseudo-inverse and null-space optimization.

The goal of the present work was assess the feasibility of using a pseudo-inverse and null-space optimization approach in the modeling of the shoulder biomechanics. The method was applied to a simplified musculoskeletal shoulder model. The mechanical system consisted in the arm, and the external forces were the arm weight, 6 scapulo-humeral muscles and the reaction at the glenohumeral joint, which was considered as a spherical joint. The muscle wrapping was considered around the humeral head assumed spherical. The dynamical equations were solved in a Lagrangian approach. The mathematical redundancy of the mechanical system was solved in two steps: a pseudo-inverse optimization to minimize the square of the muscle stress and a null-space optimization to restrict the muscle force to physiological limits. Several movements were simulated. The mathematical and numerical aspects of the constrained redundancy problem were efficiently solved by the proposed method. The prediction of muscle moment arms was consistent with cadaveric measurements and the joint reaction force was consistent with in vivo measurements. This preliminary work demonstrated that the developed algorithm has a great potential for more complex musculoskeletal modeling of the shoulder joint. In particular it could be further applied to a non-spherical joint model, allowing for the natural translation of the humeral head in the glenoid fossa.