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.
|1992||Soslowsky LJ, Flatow EL, Bigliani LU, Pawluk RJ, Ateshian GA, Mow VC. Quantitation of in situ contact areas at the glenohumeral joint: a biomechanical study. J Orthop Res. July 1992;10(4):524-534.|
|1992||Bigliani LU, Pollock RG, Soslowsky LJ, Flatow EL, Pawluk RJ, Mow VC. Tensile properties of the inferior glenohumeral ligament. J Orthop Res. March 1992;10(2):187-197.|
|1967||Fung YCB. Elasticity of soft tissues in simple elongation. Am J Physiol. December 1967;213(6):1532-1544.|
|2000||Holzapfel GA, Gasser TC, Ogden RW. A new constitutive framework for arterial wall mechanics and a comparative study of material models. J Elast. 2000;61(1-3):1-48.|
|1999||Setton LA, Elliott D., Mow VC. Altered mechanics of cartilage with osteoarthritis: human osteoarthritis and an experimental model of joint degeneration. Osteoarthritis Cartilage. January 1999;7(1):2-14.|
|2002||Weiss JA, Gardiner JC, Bonifasi-Lista C. Ligament material behavior is nonlinear, viscoelastic and rate-independent under shear loading. J Biomech. July 2002;35(6):943-950.|
|1979||Fung YC, Fronek K, Patitucci P. Pseudoelasticity of arteries and of its mathematical expression. Am J Physiol. 1979;237(5):H620-H631.|
|1999||Pioletti DP, Rakotomanana LR, Leyvraz P-F. Strain rate effect on the mechanical behavior of the anterior cruciate ligament–bone complex. Med Eng Phys. March 1999;21(2):95-100.|
|2006||Teo JCM, Si-Hoe KM, Keh JEL, Teoh SH. Relationship between CT intensity, micro-architecture and mechanical properties of porcine vertebral cancellous bone. Clin Biomech (Bristol, Avon). 2006;21(3):235-244.|
|1993||Danto MI, Woo SL. The mechanical properties of skeletally mature rabbit anterior cruciate ligament and patellar tendon over a range of strain rates. J Orthop Res. January 1993;11(1):58-67.|
|2007||Schileo E, Taddei F, Malandrino A, Cristofolini L, Viceconti M. Subject-specific finite element models can accurately predict strain levels in long bones. J Biomech. 2007;40(13):2982-2989.|