Pre-Surgical Planning of Total Shoulder Arthroplasty and Glenohumeral Instability Repair Using Patient-Specific Computer Modeling
By: Charlie Yongpravat
Publisher: [publisher not identified]
Published: 2015
Place of publication: [New York, N.Y.?]
Language: eng
Description: The glenohumeral joint has the largest range of motion in the body. This is due to its anatomy of the bony structure of the glenoid fossa providing a shallow socket with minimal constraint of the humeral head and the surrounding soft tissue structures serving as restraints to limit excessive humeral head translation. The bony and soft tissue structures function together with a delicate balance that when disrupted lead to several pathologies including degenerative osteoarthritis or glenohumeral instability, which are the focus of this research. For glenohumeral osteoarthritis, the gold standard treatment is total shoulder arthroplasty. Although the surgical success rate is reported at 95%, the long-term failure rate is as high as 30% and often caused by glenoid component failure. For glenohumeral instability, surgical capsular plication can significantly reduce recurrent dislocation rates, however, up to 70% of patients experience joint stiffness and a reduced range of motion. For these treatments, there is little consensus regarding what surgical parameters optimize functional recovery - consequently, several surgical techniques exist.

Since long-term follow-ups are lacking and difficult to perform, basic science studies are needed to identify what surgical parameters are most likely to influence patient recovery. The objective of this research was to develop patient-specific computer models to create accurate representations of these pathologies and to investigate the effects of different surgical parameters in total shoulder arthroplasty and glenohumeral instability repair. A total shoulder arthroplasty computer model was developed to investigate the effect of surgical parameters of the glenoid implant component. An initial study performed a cadaveric validation of the methodology to simulate the reaming process for resurfacing the glenoid surface. This validated computer model was then used to investigate how the degree of correction of glenoid retroversion affects cement mantle stress and potential cement failure. The use of physiologic patient-specific bone models revealed that maintaining the cortical bone layer should take precedence over version correction when a high degree of glenoid deformity is encountered.

A glenohumeral instability computer model was developed to investigate the effect of capsular repair on shoulder stability and joint range of motion. The computer model suggests that adding a plication of the posterior band of the inferior glenohumeral ligament offloads regions of high strain from the anterior region of the glenoid attachment site which may indicate a reduced risk of anterior capsular repair failure. An anisotropic hyperelastic material behavior was then incorporated to model the glenohumeral capsule by performing an inverse finite element analysis to obtain the optimized material parameters. The computer models developed in this research utilize radiographic patient images in order to replicate and investigate actual pathology. As a result, the studies performed provide a deeper understanding of the glenohumeral joint mechanics associated with the treatments of total shoulder arthroplasty and glenohumeral capsular plication. This information provides insight for the practicing shoulder surgeon in their pre-operative surgical planning to decide the optimal technique and approach for a patient with these challenging pathologies.

Moreover, the methodologies developed for simulating these surgical techniques can have a wide application to advance the foundation of pre-surgical virtual simulation and provide critical data for computer aided surgical navigation of other joints and diseases.
Notes: Department: Mechanical Engineering.

Thesis advisor: Gerard Agop Ateshian.

Thesis advisor: Christopher S. Ahmad.

Thesis (Ph.D.)--Columbia University, 2015.