A Three-Dimensional Computed Tomography Radiographic Study -- Can We Predict Glenoid Width Based on Glenoid Height? (216). Issue 10 (31st October 2021)

• Record Type: Journal Article
• Authors: Rayes, Johnny; Xu, Jian; Sparavalo, Sara; Ma, Jie; Wong, Ivan
• Is Part Of: Orthopaedic journal of sports medicine. Volume 9:Issue 10(2021)Supplement 5
• Publication Date: 2021-10-31
• Subjects: Sports medicine -- Periodicals; Orthopedics -- Periodicals; Arthroscopy -- Periodicals; Arthroplasty -- Periodicals; Knee -- Surgery -- Periodicals; 616.7
• DOI: 10.1177/2325967121S00324
• Languages: English
• ISSNs: 2325-9671

Abstract

Objectives: The purpose of this study was to investigate the relationship between glenoid width and other morphologic parameters using three-dimensional (3D) computed tomography (CT) images of native shoulders in hopes of generating a formula to predict glenoid width which will have utility in planning boney shoulder stabilization surgeries. Methods: 102 glenoid images were obtained for patients who underwent contralateral shoulder glenoid reconstruction for anterior shoulder instability between 2012 and 2020. Demographic data was obtained including age, gender and BMI. The subjects were excluded if they had a prior history of ipsilateral shoulder instability, shoulder fractures, or bone tumors. The following glenoid parameters were measured: width (W), height (H), ratio (W/H), anteroposterior (AP) depth, superior-inferior (SI) depth and version. The shape of the glenoid was also classified into pear, inverted comma or oval. Data was analyzed based on gender and age. Simple logistic regression, Kruskal Wallis Rank tests and Fisher Exact tests were performed. Results: There were 71 male and 25 females with a mean age of 39.74 ± 17.88 years. Pear morphotype accounted for most glenoid shapes (46%). The glenoid width was strongly correlated with the height (coefficient = 0.78) and a regression model equation was obtained: W (mm) = 3.4 + 0.68*H (mm). There was also strong correlation with gender (P<0.0001), age (P=0.0384), BMI (P<0.0001), glenoid shape (P=0.0036), height (P=0.0019), AP and SI depths (P<0.0001). Male gender was associated with higher measurement values for all parameters. Older age was significantly correlated with higher glenoid width values in both male and females group. (P=0.0015 and P=0.0104, respectively). Conclusions: The native glenoid width can be easily estimated using solely the glenoid height. This is particularly important for surgical decision making when facing anterior or posterior glenoid defects in patients with shoulder instability.