Feasibility of an alternative method to estimate glenohumeral joint center from videogrammetry measurements and CT/MRI of patients

Subject-specific model-derived kinematics of the shoulder based on skin markers during arm abduction up to 180° - assessment of 4 gleno-humeral joint models

Accuracy of shoulder kinematics predicted by multi-body kinematics optimisation depend on the joint models used. This study assesses the influence of four different subject-specific gleno-humeral joint models within multi-body kinematics optimisation: a 6-degree-of-freedom joint (i.e. single-body kinematics optimisation), a sphere-on-sphere joint (with two spheres of different radii) and a spherical joint with or without penalised translation. To drive these models, the 3D coordinates of 12 skin markers of 6 subjects performing static arm abduction poses up to 180° were used. The reference data was obtained using biplane X-rays from which 3D bone reconstructions were generated: scapula and humerus were 3D reconstructed by fitting a template model made of geometrical primitives on the two bones' X-rays. Without any motion capture system, the recording of the skin markers was performed at the very same time than the X-rays with radiopaque markers. The gleno-humeral displacements and angles, and scapula-thoracic angles were computed. The gleno-humeral sphere-on-sphere joint provided slightly better results than the spherical joint with or without penalised translation, but considerably better gleno-humeral displacements than the 6-DoF joint. Considering that it can easily be personalised from medical images, this sphere-on-sphere model seems promising for shoulder multi-body kinematics optimisation.

A Matlab toolbox for scaled-generic modeling of shoulder and elbow

There still remains a barrier ahead of widespread clinical applications of upper extremity musculoskeletal models. This study is a step toward lifting this barrier for a shoulder musculoskeletal model by enhancing its realism and facilitating its applications. To this end, two main improvements are considered. First, the elbow and the muscle groups spanning the elbow are included in the model. Second, scaling routines are developed that scale model’s bone segment inertial properties, skeletal morphologies, and muscles architectures according to a specific subject. The model is also presented as a Matlab toolbox with a graphical user interface to exempt its users from further programming. We evaluated effects of anthropometric parameters, including subject’s gender, height, weight, glenoid inclination, and degenerations of rotator cuff muscles on the glenohumeral joint reaction force (JRF) predictions. An arm abduction motion in the scapula plane is simulated while each of the parameters is independently varied. The results indeed illustrate the effect of anthropometric parameters and provide JRF predictions with less than 13% difference compared to in vivo studies. The developed Matlab toolbox could be populated with pre/post operative patients of total shoulder arthroplasty to answer clinical questions regarding treatments of glenohumeral joint osteoarthritis.