Rotator cuff pathologies involving supraspinatus are a common cause of musculoskeletal morbidity and can lead to significant disability affecting the overall quality of life. Architectural parameters of the muscle directly influence its functional properties. Therefore, understanding of fiber bundle changes with surgery and different exercises can assist clinicians in planning better surgical and shoulder rehabilitative protocols. The first objective of this thesis was to systematically review human cadaveric studies of the normal supraspinatus architecture and highlight the key aspects that should be considered while performing studies of skeletal muscle architecture. The second objective was to understand the impact of surgical repair on the structural and functional recovery of the supraspinatus. The final objective was to provide a scientific rationale behind choosing an exercise to strengthen supraspinatus by investigating its muscle architecture. Study 1 systematically reviewed human cadaveric studies of the normal supraspinatus architecture. Results showed that the overall quality of majority of included is poor and there was a large range in the reported architectural values of the entire muscle. In conclusion, there were only a few studies providing the level of detail and quality suitable for advancing our understanding of shoulder biomechanics. Study 2 quantified and compared the fiber bundle architecture of the pathologic supraspinatus pre- and post-operatively at multiple time points. Results showed significant lengthening of fiber bundles after one month of surgery which then decreased significantly by 6 months of surgery. In contrast, an initial decrease followed by an increase in pennation angle overtime was found. The results suggest that the stretching applied to the tendon and muscle during repair could affect the length-tension relationship of the muscle, which in turn can compromise its function and may lead to inferior surgical outcomes. Study 3 compared the efficacy of three commonly prescribed supraspinatus strengthening exercises in the rehabilitation setting based on the architectural changes following resistance training. Results showed there was no change in FBL and increased strength after resistance training with prone horizontal abduction exercise. Findings suggest that prone horizontal abduction may be a more suitable exercise to strengthen supraspinatus.

Physiological cross sectional area (PCSA) is used to compare force-producing capabilities of skeletal muscles. PCSA has been defined as the summation of the cross sectional area of the fiber bundles composing the muscle. As PCSA cannot be measured directly from a specimen, a formula requiring averaged muscle architectural parameters has traditionally been used. The purpose of this study was to develop a finite element method (FEM) to calculate PCSA of extensor carpi radialis longus (ECRL) and brevis (ECRB) directly from digitized fiber bundle data obtained throughout the volume of the muscle and to compare the PCSAs calculated using the FEM and formula methods. Differences were found between the FEM and formula method for both muscles. The FEM provides an approach that takes into account architectural variances while minimizing the need for averaged architectural parameters.

Physiological cross sectional area (PCSA) is used to compare force-producing capabilities of skeletal muscles. PCSA has been defined as the summation of the cross sectional area of the fiber bundles composing the muscle. As PCSA cannot be measured directly from a specimen, a formula requiring averaged muscle architectural parameters has traditionally been used. The purpose of this study was to develop a finite element method (FEM) to calculate PCSA of extensor carpi radialis longus (ECRL) and brevis (ECRB) directly from digitized fiber bundle data obtained throughout the volume of the muscle and to compare the PCSAs calculated using the FEM and formula methods. Differences were found between the FEM and formula method for both muscles. The FEM provides an approach that takes into account architectural variances while minimizing the need for averaged architectural parameters.