Shoulder biomechanics of RC repair and Instability: A systematic review of cadaveric methodology.
BACKGROUND
Numerous biomechanical studies have addressed normal shoulder function and the factors that affect it. While these investigations include a mix of in-vivo clinical reports, ex-vivo cadaveric studies, and computer-based simulations, each has its own strengths and limitations. A robust methodology is essential in cadaveric work but does not always come easily. Precise quantitative measurements are difficult in in-vivo studies, and simulation studies require validation steps. This review focuses on ex-vivo cadaveric studies to emphasize the best research methodologies available to simulate physiologically and clinically relevant shoulder motion.


METHODS
A PubMed and Web of Science search was conducted in March 2017 (and updated in May 2018) to identify the cadaveric studies focused on the shoulder and its function. The key words for this search included rotator cuff (RC) injuries, RC surgery, and their synonyms. The protocol of the study was registered on PROSPERO and is accessible at CRD42017068873.


RESULTS
Thirty one studies consisting of 167 specimens with various biomechanical methods met our inclusion criteria. All studies were level V cadaveric studies. Cadaveric biomechanical models are widely used to study shoulder instability and RC repair. These models are commonly limited to the glenohumeral joint by a fixed scapula, passively and discretely move the humerus, and statically load the RC without regard for the integrity of the glenohumeral capsule.


CONCLUSION
All studies captured in this review evaluated shoulder biomechanics. Recent studies in patients suggest that some assumptions made in this space may not fully characterize motion of the human shoulder. With reproducible scapular positioning, dynamic RC activation, and preservation of glenohumeral capsule integrity, cadaveric studies can facilitate proper validation for simulation models and broaden our understanding of the shoulder environment during motion in healthy and disease states.