Glenosphere design affects range of movement and risk of friction-type scapular impingement in reverse shoulder arthroplasty

Aims

Scapular notching is a frequently observed radiographic phenomenon in reverse shoulder arthroplasty (RSA), signifying impingement of components. The purposes of this study were to evaluate the effect of glenoid component size and glenosphere type on impingement-free range of movement (ROM) for extension and internal and external rotation in a virtual RSA model, and to determine the optimal configuration to reduce the incidence of friction-type scapular notching.

Materials and Methods

Preoperative CT scans obtained in 21 patients (three male, 18 female) with primary osteoarthritis were analyzed using modelling software. Two concurrent factors were tested for impingement-free ROM and translation of the centre of rotation: glenosphere diameter (36 mm vs 39 mm) and type (centred, 2 mm inferior eccentric offset, 10° inferior tilt).

Results

Glenosphere size was most predictive of increased extension and external rotation, whereas lateralization of the centre of rotation was the most predictive factor for internal rotation. A larger diameter of glenosphere combined with a 10° tilted configuration demonstrated superior values for extension and external rotation, whereas the eccentric component improved internal rotation by a mean 8.9° (standard deviation 2.7°) compared with a standard concentric glenosphere.

Conclusion

Glenosphere configuration can be modified to increase range of movement in RSA. Friction-type scapular notching was most effectively reduced by use of a large-diameter glenosphere with 10° inferior tilt. Cite this article: Bone Joint J 2018;100-B:1182–6.

Characterization of the dysplastic Walch type C glenoid

Aims

The Walch Type C dysplastic glenoid is characterized by excessive retroversion. This anatomical study describes its morphology.

Patients and Methods

A total of 29 shoulders with a dysplastic glenoid were analyzed. CT was used to measure retroversion, inclination, height, width, radius-of-curvature, surface area, depth, subluxation of the humeral head and the Goutallier classification of fatty infiltration. The severity of dysplasia and deficiency of the posterior rim of the glenoid were recorded.

Results

A type C glenoid occurred in 1.8% of shoulders referred to our tertiary centres. The mean retroversion, inclination, height, width, radius-of-curvature, surface area, and depth of the glenoid were 37°, 3°, 46 mm, 30 mm, 37°, 1284 mm3, and 16 mm, respectively. The mean posterior subluxation was 90%. The Goutallier class was < 2 in 25 shoulders (86%). Glenoid dysplasia was mild in four, moderate in 14, and severe in 11 shoulders. The typical appearance of the posterior glenoid rim had a rounded or ‘lazy J’ morphology. The glenoid neck was deficient in 18 shoulders (62%).

Conclusion

A dysplastic Type C glenoid characteristically has a uniconcave retroverted morphology, a deficient posteroinferior rim and scapular neck, and a reduced depth. These findings help to define the unique anatomical variations and may aid the planning of surgery and the development of components for these patients. Cite this article: Bone Joint J 2018;100-B:1074–9.

Prediction of the pre-morbid 3D anatomy of the proximal humerus based on statistical shape modelling

Aims

Restoring the pre-morbid anatomy of the proximal humerus is a goal of anatomical shoulder arthroplasty, but reliance is placed on the surgeon’s experience and on anatomical estimations. The purpose of this study was to present a novel method, ‘Statistical Shape Modelling’, which accurately predicts the pre-morbid proximal humeral anatomy and calculates the 3D geometric parameters needed to restore normal anatomy in patients with severe degenerative osteoarthritis or a fracture of the proximal humerus.

Materials and Methods

From a database of 57 humeral CT scans 3D humeral reconstructions were manually created. The reconstructions were used to construct a statistical shape model (SSM), which was then tested on a second set of 52 scans. For each humerus in the second set, 3D reconstructions of four diaphyseal segments of varying lengths were created. These reconstructions were chosen to mimic severe osteoarthritis, a fracture of the surgical neck of the humerus and a proximal humeral fracture with diaphyseal extension. The SSM was then applied to the diaphyseal segments to see how well it predicted proximal morphology, using the actual proximal humeral morphology for comparison.

Results

With the metaphysis included, mimicking osteoarthritis, the errors of prediction for retroversion, inclination, height, radius of curvature and posterior and medial offset of the head of the humerus were 2.9° (± 2.3°), 4.0° (± 3.3°), 1.0 mm (± 0.8 mm), 0.8 mm (± 0.6 mm), 0.7 mm (± 0.5 mm) and 1.0 mm (± 0.7 mm), respectively. With the metaphysis excluded, mimicking a fracture of the surgical neck, the errors of prediction for retroversion, inclination, height, radius of curvature and posterior and medial offset of the head of the humerus were 3.8° (± 2.9°), 3.9° (± 3.4°), 2.4 mm (± 1.9 mm), 1.3 mm (± 0.9 mm), 0.8 mm (± 0.5 mm) and 0.9 mm (± 0.6 mm), respectively.

Conclusion

This study reports a novel, computerised method that accurately predicts the pre-morbid proximal humeral anatomy even in challenging situations. This information can be used in the surgical planning and operative reconstruction of patients with severe degenerative osteoarthritis or with a fracture of the proximal humerus. Cite this article: Bone Joint J 2017;99-B:927–33.

Patient-specific glenoid guides provide accuracy and reproducibility in total shoulder arthroplasty

AIMS

Patient-specific glenoid guides (PSGs) claim an improvement in accuracy and reproducibility of the positioning of components in total shoulder arthroplasty (TSA). The results have not yet been confirmed in a prospective clinical trial. Our aim was to assess whether the use of PSGs in patients with osteoarthritis of the shoulder would allow accurate and reliable implantation of the glenoid component.

PATIENTS AND METHODS

A total of 17 patients (three men and 14 women) with a mean age of 71 years (53 to 81) awaiting TSA were enrolled in the study. Pre- and post-operative version and inclination of the glenoid were measured on CT scans, using 3D planning automatic software. During surgery, a congruent 3D-printed PSG was applied onto the glenoid surface, thus determining the entry point and orientation of the central guide wire used for reaming the glenoid and the introduction of the component. Manual segmentation was performed on post-operative CT scans to compare the planned and the actual position of the entry point (mm) and orientation of the component (°).

RESULTS

The mean error in the accuracy of the entry point was -0.1 mm (standard deviation (sd) 1.4) in the horizontal plane, and 0.8 mm (sd 1.3) in the vertical plane. The mean error in the orientation of the glenoid component was 3.4° (sd 5.1°) for version and 1.8° (sd 5.3°) for inclination.

CONCLUSION

Pre-operative planning with automatic software and the use of PSGs provides accurate and reproducible positioning and orientation of the glenoid component in anatomical TSA. Cite this article: Bone Joint J 2016;98-B:1080-5.

Recognition-based segmentation and registration method for image guided shoulder surgery

For any image guided surgery, independently of the technique which is used (navigation, templates, robotics), it is necessary to get a 3D bone surface model from CT or MR images. Such model is used for planning, registration and visualization. We report that graphical representation of patient bony structure and the surgical tools, interconnectively with the tracking device and patient-to-image registration are crucial components in such a system. For Total Shoulder Arthroplasty (TSA), there are many challenges, The most of cases that we are working with are pathological cases such as rheumatoid arthritis, osteoarthritis disease. The CT images of these cases often show a fusion area between the glenoid cavity and the humeral head. They also show severe deformations of the humeral head surface that result in a loss of contours. This fusion area and image quality problems are also amplified by well-known CT-scan artifacts like beam-hardening or partial volume effects. The state of the art shows that several segmentation techniques, applied to CT-Scans of the shoulder, have already been disclosed. Unfortunately, their performances, when used on pathological data, are quite poor [1, 2]. The aim of this paper is to present a new image guided surgery system based on CT scan of the patient and using bony structure recognition, morphological analysis for the operated region and robust image-to-patient registration.