Reverse total shoulder arthroplasty (RTSA) restores elevation in rotator cuff–deficient shoulders by reconstructing the load path around the deltoid, yet baseplate fixation failure, acromial fractures, and proximal humeral stress shielding remain cl...
Reverse total shoulder arthroplasty (RTSA) restores elevation in rotator cuff–deficient shoulders by reconstructing the load path around the deltoid, yet baseplate fixation failure, acromial fractures, and proximal humeral stress shielding remain clinically relevant complications. RTSA fixation is sensitive not only to the magnitude of the joint reaction force but also to the muscle-specific redistribution that changes load composition and lines of action. However, many RTSA finite element (FE) studies still rely on a single resultant joint force and therefore cannot fully reflect cuff-dependent changes in postoperative loading.
The primary objective of this study was to develop a literature-calibrated, EMG-free model that quantitatively matches postoperative muscle-specific force redistribution after RTSA. We established a musculoskeletal static optimization (MSK–SO) pipeline using a six-muscle shoulder model (DelA, DelM, SUPSP, SUBSC, INFSP, PECM2) and calibrated it against cadaveric and in vivo references across nine rotator cuff scenarios. The optimization was designed to match joint torques, moment arms, muscle force–angle profiles, and glenohumeral joint (GHJ) force components. The calibrated outputs were standardized in a unified coordinate system and converted into two FE-ready load sets: Case 1, a single resultant GHJ load, and Case 2, a mixed load comprising muscle resultants and a residual GHJ vector that enforces overall force equilibrium.
The secondary objective was to connect the calibrated load sets to patient-specific FE models and quantify how surgically controllable positioning variables affect RTSA fixation mechanics. Patient-specific RTSA FE models were constructed for six cadaveric shoulders under shared material properties, contact and boundary conditions, and mesh-independence criteria. Across 15–120° abduction and nine cuff scenarios, we evaluated baseplate–bone micromotion (95th percentile), acromial and glenoid rim stresses, and proximal humeral stress shielding.
Case 2 tended to reduce baseplate–bone micromotion compared with Case 1 while better reproducing clinically reported loading features such as glenoid rocking and acromial stress patterns. Divergent screw angulation relative to a horizontal baseline provided the largest micromotion reduction, whereas screw length and number had smaller effects. A thin humeral stem combined with neutral or mild valgus alignment mitigated both micromotion and stress shielding, and glenosphere lateralization of approximately 5 mm minimized micromotion and rim stresses, while excessive lateralization increased glenoid and acromial stresses.
In summary, this study develops an EMG-independent, literature-calibrated muscle force redistribution matching model for RTSA and standardizes its outputs into FE inputs. By linking the calibrated load composition to patient-specific FE analysis, the framework provides quantitative guidelines for screw orientation, humeral stem alignment/diameter, and glenosphere lateralization that can be translated into preoperative RTSA planning.