Ren Hongyu, Chen Xin, Zhang Yongqing
Department of Orthodontics, Xiangyang Stomatological Hospital, Affiliated Stomatological Hospital of Hubei University of Arts and Science Xiangyang, Hubei, China.
Am J Transl Res. 2025 Aug 15;17(8):6236-6249. doi: 10.62347/JSWV8973. eCollection 2025.
To investigate the correlation between nine commonly used cephalometric analyses and facial profile attractiveness and to explore an optimized combination of cephalometric measures.
Sixteen nonprofessional evaluators assessed the profile attractiveness of 210 untreated Chinese adults using a visual analog scale. Eighty-seven cephalometric measures were obtained from nine analyses (Burstone, Downs, Holdaway, Jarabak, McNamara, Ricketts, Steiner, Tweed, and Wylie). Quadratic regression analysis was employed to identify measures significantly correlated with facial profile attractiveness and to calculate their maximum attractiveness values (MAVs). Stepwise regression was applied to assess the explanatory power of each analysis for profile attractiveness and to construct optimized predictive models.
The explanatory power of the nine analyses for attractiveness variation was ranked as follows: Holdaway (41.5%) > Ricketts (37.6%) > Steiner (36.8%) > Burstone (35.7%) > Tweed (35.6%) > Downs (33.9%) > McNamara (24.3%) > Wylie (13.2%) > Jarabak (6.1%). Among individual measures, the H-angle, ANB (°), A-Npog (mm), and NA-APo (°) accounted for more than 26% of attractiveness variation. A five-indicator model comprising H-angle (28.8%; MAV = 17.2°), L1-APog (14.6%; MAV = 0.5 mm), Wits appraisal (4.5%; MAV = 0.1 mm), ANS-Me/N-Me (4.2%; MAV = 54%), and ANS-Ptm (3.3%; MAV = 46.7 mm) explained 55.4% of the variation.
Among the nine cephalometric analyses, the Holdaway method exhibited the strongest explanatory power for variation in profile attractiveness. The newly constructed five-indicator model may provide more precise aesthetic references for orthodontic and orthognathic treatments.
探讨九种常用头影测量分析方法与面部侧貌吸引力之间的相关性，并探索头影测量指标的优化组合。
16名非专业评估者使用视觉模拟量表对210名未经治疗的中国成年人的侧貌吸引力进行评估。从九种分析方法（Burstone、Downs、Holdaway、Jarabak、McNamara、Ricketts、Steiner、Tweed和Wylie）中获取87项头影测量指标。采用二次回归分析确定与面部侧貌吸引力显著相关的指标，并计算其最大吸引力值（MAV）。应用逐步回归评估每种分析方法对侧貌吸引力的解释力，并构建优化预测模型。
九种分析方法对吸引力变化的解释力排序如下：Holdaway（41.5%）＞Ricketts（37.6%）＞Steiner（36.8%）＞Burstone（35.7%）＞Tweed（35.6%）＞Downs（33.9%）＞McNamara（24.3%）＞Wylie（13.2%）＞Jarabak（6.1%）。在个体指标中，H角、ANB（°）、A-Npog（mm）和NA-APo（°）占吸引力变化的比例超过26%。由H角（28.8%；MAV = 17.2°）、L1-APog（14.6%；MAV = 0.5 mm）、Wits值（4.5%；MAV = 0.1 mm）、ANS-Me/N-Me（4.2%；MAV = 54%）和ANS-Ptm（3.3%；MAV = 46.7 mm）组成的五指标模型解释了55.4%的变化。
在九种头影测量分析方法中，Holdaway方法对侧貌吸引力变化的解释力最强。新构建的五指标模型可为正畸和正颌治疗提供更精确的美学参考。
