Computed Tomography-based Predictive Model for Estimating the Glenoid Width from Length: A Novel Approach to Assess Glenoid Bone Loss in the Indian Population

Abstract Background: In human anatomy, certain anthropometric relationships are constant, such as height and femur length or height and arm span. This study aimed to determine the consistent relation between the length and width of the glenoid in normal shoulders and assessed its validity in shoulders with documented bone loss. Methodology: In this descriptive study, computed tomography scans of normal glenoids ( n = 46) were analyzed, and a regression analysis was performed to derive a formula correlating glenoid width with length. The derived formula demonstrated a consistent relationship between the two parameters, allowing for the estimation of glenoid width from its length. The derived formula was then applied to a pathological group with bone loss ( n = 23). The actual bone loss in this group was measured using the best-fit circle method to determine the glenoid width. This measured value was then validated with the estimated width obtained from the formula based on glenoid length. A paired t -test was conducted to compare the two sets of values to assess the accuracy of the formula. Results: The mean glenoid length was 35.82 ± 3.16 mm, and the mean width was 26.28 ± 2.91 mm. Normal Shoulder Group: Regression analysis yielded the equation: Width = (0.811 × Length) – 2.779, F = 152.681 and R 2 = 0.771 ( P < 0.005), indicating good predictive power. Pathological Shoulder Group: The paired samples t -test indicated that there was no statistically significant difference between the predicted and actual bone loss ( P = 0.074, Cohen’s d = 0.074) Conclusions: (1) The derived formula shows a constant relation between the glenoid length and width in normal shoulders. (2) It can be used as a simple, reliable, and reproducible method to assess bone loss. (3) This study improves our understanding of glenoid morphology in the Indian population and can be used in cases with instability or arthroplasty implant designing. (4) Anatomic, cadaveric, and radiological evaluation with larger samples and multicentric studies will help to strengthen the correlation.