No abstract

A detailed understanding of craniofacial ontogenetic development is important in a variety of scientific disciplines dealing with facial reconstruction, forensic identification, ageing prediction, and monitoring of pathological growth, including the effect of therapy. The main goals of this study were (1) the construction of the facial aging model using local polynomial regression fitting separately for both sexes, (2) evaluation of the aging effect not only on facial form as a whole but also on dimensions important for clinical practice, and (3) monitoring of the development of shape facial sexual dimorphism. Our study was based on the form and shape analysis of three-dimensional facial surface models of 456 individuals aged 14–83 years. The facial models were obtained using a structured light-based optical scanner and divided (for some analyses) into four age categories (juveniles, young adults, middle adults, and elderly adults). The methodology was based on geometric and classic morphometrics including multivariate statistics. Aging in both sexes shared common traits such as more pronounced facial roundness reducing facial convexity, sagging soft tissue, smaller visible areas of the eyes, greater nose, and thinner lips. In contrast to female faces, male faces increase in size until almost 30 years of age. After the age of 70, male facial size not only stagnates, like in females, but actually decreases slightly. Sexual dimorphic traits tended to diminish in the frontal and orbitonasal areas and increase in the gonial area.

Factors such as growth, aging, and health have known associations with changes in facial soft tissues. A detailed understanding of facial soft tissue ontogenetic development is important in a variety of scientific disciplines dealing with facial reconstruction, forensic identification, and ageing prediction. The main goals of this study were (1) to use geometric morphometrics to model facial aging, (2) to model the development of shape facial sexual dimorphism, and (3) to use classic morphometrics to depict facial differences between individual age categories. Our study was based on the form and shape analysis of three-dimensional facial surface models of 456 individuals aged 14–83 years. The facial models were obtained using a structured light-based optical scanner and divided into four age categories (juvenile, younger adult, middle adult, and older adult). The methodology was based on geometric and classic morphometrics including multivariate statistics. Aging in both sexes shared common traits such as more pronounced facial roundness reducing facial convexity, sagging soft tissue, smaller visible areas of the eyes, greater nose, and thinner lips. Male faces exhibited more even and intense ageing changes. Sexual dimorphic traits tended to diminish in the frontal and orbitonasal area and increase in the gonial area.