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Background: Glenoid morphology plays a critical role in reverse total shoulder arthroplasty, influencing implant positioning and fixation. Although advanced Three dimensional pre-operative planning allows patient-specific optimization, a simple and reproducible framework for rapid assessment of glenoid size and bone stock remains lacking. The purpose of this study is to propose a computed tomography-based classification of glenoid size using a reproducible parameter and evaluate its potential as a complementary screening tool for pre-operative planning. Methods: A retrospective analysis of 200 non-pathological glenoids was performed. Measurements included maximum anteroposterior diameter (MAD, representing glenoid width), superoinferior diameter, surface area, and glenoid bone depth. A K-means clustering algorithm based on MAD defined 3 groups. Correlations with patient height were assessed. Baseplate compatibility and fixation potential were evaluated theoretically. Conclusion: This classification provides a simple and reproducible anatomical framework for glenoid size stratification. While not intended to replace patient-specific three dimensional planning, it may serve as a complementary screening tool to anticipate implant sizing and fixation strategies. Validation in pathologic glenoids is required.
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Quemener–Tanguy et al. (2026) studied this question.
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