Developing a three-dimensional statistical shape model of normal dentition using an automated algorithm and normal samples.

OBJECTIVES: The statistical shape model (SSM) is a model of geometric properties of a set of shapes based on statistical shape analysis. The SSM develops an average model of several objects using an automated algorithm that excludes the operator's subjectivity. The aim of this study was to develop a three-dimensional (3D) SSM of normal dentition to provide virtual templates for efficient treatment. MATERIALS AND METHODS: Dental casts were obtained from participants with normal dentition. After acquiring the 3D models, the SSMs of the individual teeth and whole dental arch were generated by an iterative closest point (ICP)-based rigid registration and point correspondences, respectively. Then, the individual tooth SSM was aligned to the whole dental arch SSM using ICP-based registration to generate an average model of normal dentition. RESULTS: The generated 3D SSM showed specific morphological features of normal dentition similar to those previously reported. Moreover, on measuring the arch dimensions, all values in this study were similar to those previously reported using normal dentition. CONCLUSIONS: The 3D SSM of normal dentition may increase the diagnostic efficiency of orthodontic treatments by providing a visual objective. It can be also used as a 3D template in various fields of dentistry. CLINICAL RELEVANCE: Our SSM of normal dentition provides both quantitative and qualitative information on the 3D morphology of teeth and dental arches, which may provide valuable information on 3D virtual-setup, bracket fabrication, and aligner treatment.

Three-dimensional assessment of upper lip positional changes according to simulated maxillary anterior tooth movements by white light scanning.

OBJECTIVE: Esthetic improvements during orthodontic treatment are achieved by changes in positions of the lips and surrounding soft tissues. Facial soft-tissue movement has already been two-dimensionally evaluated by cephalometry. In this study, we aimed to three-dimensionally assess positional changes of the adult upper lip according to simulated maxillary anterior tooth movements by white light scanning. METHODS: We measured changes in three-dimensional coordinates of labial landmarks in relation to maxillary incisor movements of normal adults simulated with films of varying thickness by using a white light scanner. RESULTS: With increasing protraction, the upper lip moved forward and significantly upward. Labial movement was limited by the surrounding soft tissues. The extent of movement above the vermilion border was slightly less than half that of the teeth, showing strong correlation. Most changes were concentrated in the depression above the upper vermilion border. Labial movement toward the nose was reduced significantly. CONCLUSIONS: After adequately controlling several variables and using white light scanning with high reproducibility and accuracy, the coefficient of determination showed moderate values (0.40-0.77) and significant changes could be determined. This method would be useful to predict soft-tissue positional changes according to tooth movements.