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Published on: February 23, 2024
Correlation between facial widths and maxillary teeth dimensions based on facial and intraoral scanning in a Chinese
Kaijin Lin1,2, Yongqing Guo1,2, Jin Yang1,2
1Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Lab of Fujian College and University, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, China.
Purpose:
This study aimed to evaluate the efficacy of facial parameters (facial widths and proportions) in predicting the maxillary anterior teeth characteristics (teeth widths and ratios) through three-dimensional (3D) analysis.
Materials And Methods:
This cross-sectional study was conducted at the Stomatology Hospital of Fujian Medical University. Facial parameters of participants were obtained using a 3D facial scanner and subsequently imported into specific software for automated measurement. Intraoral data was captured by TRIOS 3. Pearson correlation analysis was employed to identify relationships between facial and intraoral measurements. Linear regression was performed on significantly correlated variables, while t-tests evaluated the accuracy of esthetic proportions (golden proportion [GP], golden mean [GM], and recurring esthetic dental [RED]) in predicting combined central incisor width (CIW) and combined anterior teeth width (CAW) (α = 0.05).
Results:
A total of 147 volunteers participated in this study. Significant correlations for CIW and CAW were observed with facial widths (interpupillary width [IPW], intercanthal width [ICW], and intercommissural width [ICoW]) (p < 0.05). Regression equations based on these facial parameters revealed no significant differences between predicted and actual values for CIW and CAW. RED with ICW reliably predicted CIW without significant deviation from actual measurements (p > 0.05).
Conclusions:
Anterior teeth widths can be reliably predicted using regression formulas derived from facial widths. The RED proportion provides a reliable method for predicting CIW.

