Identifying Differences Between a Straight Face and a Posed Smile Using the Homologous Modeling Technique and the Principal Component Analysis.

Abstract

Recently, a homologous modeling method was developed to simulate 3D human body forms, which can visualize principal component analysis (PCA) results and facilitate its detailed comparison with results of previous method. Herein, we aimed to construct a homologous model of the face to identify differences between a straight face and a posed smile. Thirty-eight volunteers (19 males and 19 females, 38 straight faces and 38 posed smiles) with no medical history associated with a posed smile were enrolled. Three-dimensional images were constructed using the Homologous Body Modeling software and the HBM-Rugle; 9 landmarks were identified on the 3D-model surfaces. The template model automatically fitted into an individually scanned point cloud of the face by minimizing external and internal energy functions. Faces were analyzed using PCA; differences between straight faces and posed smiles were analyzed using paired t tests. Contribution of the most important principal component was 23.8%; 8 principal components explained >75% of the total variance. A significant difference between a straight face and a posed smile was observed in the second and the fourth principal components. The second principal component images revealed differences between a straight face and a posed smile and changes around the chin area with regard to length, shape, and anteroposterior position. Such changes were inclusive of individual differences. However, the fourth principal component image only revealed differences between a straight face and a posed smile; observed differences included simultaneous shortening of upper and lower eyelid length, evaluation of the nasal ala ase, swelling of the cheek area, and elevation of the mouth angle. Although these results were clinically apparent, we believe that this article is the first to statistically verify the same.Consequently, the homologous model technique and PCA are useful for evaluation of the facial soft-tissue changes.