RESUMO
Objective: The glenopolar angle is a helpful criterion for recommending operative treatment. This study aims to determine the morphometric features of the scapula and provide essential information that supplies scapular biomechanics to produce a formula. Methods: The study was carried out on 34 dry scapulae in the laboratory of the Anatomy Department of the Faculty of Medicine, Bursa Uludag University. We used calipers for the linear measurements and the ImageJ program for the area and angle parameters. A total of 23 parameters were evaluated in the study. Statistical analyzes were performed using SPSS 22.0 software. Results: According to the results of the correlation analysis, the highest correlation value of (R=0.957) was found to be the distance between the superior angle (angulus superior)-top of the glenoid plane and the inferior angle (angulus inferior)-the top of the glenoid plane. To estimate the glenopolar angle, we applied linear regression analysis and developed the following formula: Glenopolar angle =115.589 - (6.401 x the distance between the coracoid process and the top of the glenoid cavity) - (0.368 x angle between the glenoid plane and the lateral edge of the scapula extending towards the endpoint of the glenoid plane) (Adjusted R2=0.667). Conclusions: Glenopolar angle can provide information about the fracture risk of the glenoid cavity and allows orthopedic surgeons to make quick decisions about the risk in the region. We believe that the study will provide a different perspective on designing different products in industrial designs for shoulder joints, especially in implantations.
RESUMO
The human skull serves as an essential material for facial reconstruction. In particular, the petrous part of the temporal bone is vital due to its compact structure, which can resist mechanical forces. The study aims to give descriptive values to estimate the face shape and produce regression formulas through the external acoustic pore as a reference point. The study was carried out on 3-dimensional computed tomography images, a total of 83 adult images (45 females and 38 males) in the Department of Radiology of Bursa Uludag University Medical Faculty. The distances between the imaginary vertical line passing through the porion and the anthropometric points revealing the facial features were measured for the soft and hard tissue. The vertical distances between the soft and hard tissue landmarks were also measured for both sexes. Measurements were performed with the Image J program, and for the statistical analysis, SPSS 25.0 was used ( P < 0.005). Linear simple regression analysis was used to produce formulas to estimate the soft tissue thickness using hard tissue. Also, discriminant function analysis was performed to determine sex in the presence of an unknown skull. The descriptive values of the variables on the axial and vertical planes and the differences between sexes are given. Also, all formulas make accurate predictions of 90% or more. The authors tried to estimate the anatomical points that roughly reveal the facial features with the regression formulas developed using anthropometric measurements. The authors think that the shape of the face, which is more specific to the individual, can be reached more clearly using mathematical models, and the authors believe that this study will set an example for future studies.