INTRODUCTION: Soft-tissue facial outline has been studied by conventional cephalometric methods, and differences between the 2 sexes have been identified, mainly related to size and timing of growth. However, shape per se was not sufficiently evaluated, especially regarding variability, age-related changes, and sexual dimorphism. The purpose of this study was to evaluate shape variability and sexual dimorphism of the soft-tissue outline by using morphometric methods. METHODS: Pretreatment lateral cephalograms from 170 consecutive patients (82 male, 88 female) aged 7 to 17 years were used. Fifteen skeletal and 22 soft-tissue landmarks were digitized and processed with Procrustes superimposition and principal component analysis. The principal components (PCs) of the soft-tissue shape were analyzed in relation to age and sex. RESULTS: The first 8 PCs explained approximately 90% of the total shape variability. The first coefficient (PC1) related to lip, nose, and chin prominence and included 36% of total shape variability. It was significantly correlated to age, but with a low coefficient of determination (r2 = 13%). The second coefficient (PC2) related to facial convexity and explained 18% of shape variability. The next 2 coefficients were mainly related to lower lip shape. Statistically significant sexual dimorphism was detected, but the overall shape differences between the average profiles of boys and girls were minor and barely detectable visually. Shape dimorphism was present both before and after the age of 12 years. CONCLUSIONS: Shape variability related mainly to relative lip protrusion, convexity of the face, and lower lip shape. Shape differences between the sexes seemed to exist even before the pubertal growth spurt, but they were small. Age changes in shape appeared more significant.

The purpose of this study was to use quantitative methods to measure the size and shape of the sella turcica and thus establish normative reference standards that could assist in a more objective evaluation and detection of pathological conditions. Standardized lateral cephalograms of 184 healthy Greeks (91 males and 93 females) were used. The age range was between 6 and 17 years. Conventional measurements included three different heights of the sella turcica (anterior, posterior, median), its length, and width, measured in relation to the Frankfort reference line. In addition, the area of sella turcica was calculated. Morphometric methods were used to assess shape. The tracings were superimposed using the Procrustes method, and the average shape was computed. Principal component analysis (PCA) was used to assess shape variability. The data were correlated with centroid size, age, and gender. Unpaired t-tests were used to determine gender differences. Sella height anteriorly was the only variable found to be significantly different between the genders, being larger in females by 0.5 mm. Linear and area measurements were found to be significantly correlated with age, but all correlations were low (r(2) below 8 per cent). Sella turcica shape, as described by PCA, was different between males and females, mainly at the posterior aspect of the sella outline. However, although there was an extensive overlap between the genders, and differences were minimal. Age was not found to be correlated with the shape coefficients, although, in the female group, the first principal component of shape was marginally not significant. Allometry was observed in both genders, the sella showing a tendency towards a flatter and wider shape with increase in size. The results of this study constitute quantitative reference data that could be used for objective evaluation of sella shape.

INTRODUCTION: Prediction of soft-tissue outline shape from skeletal remains is useful in forensics and archaeology. The inverse problem, the assessment of underlying skeletal relationships from the external appearance, is pertinent in orthodontics. The purposes of this study were to assess the correlation between craniofacial shape and shape of the soft-tissue profile outline and to determine the extent to which it might be possible to predict the latter from the former. METHODS: Lateral cephalograms from 170 consecutive orthodontic patients were used, and 17 skeletal, 2 dental, and 22 soft-tissue landmarks were digitized and processed by using Procrustes superimposition and principal component analysis. The principal components of the skeletal and soft-tissue shapes were entered into the correlation analysis. RESULTS: Significant correlations were found between the skeletal and the soft-tissue components. The use of 7 anterior skeletal landmarks (not including the nasal bone) resulted in a predictive power (coefficient of determination) of 38% of the variability of soft-tissue shape. This increased to almost 50% by adding nasal and incisor points but showed only a slight further improvement by incorporating posterior skeletal landmarks. CONCLUSIONS: Anterior skeletal and dental landmarks can be used to predict soft-tissue profile shape with a 50% power in children and adolescents.