Arab Medical University, Benghazi, Libya.
Eur J Orthod. 2013 Jun;35(3):295-304. doi: 10.1093/ejo/cjr033. Epub 2011 Apr 29.
The aim of the prospective cross-sectional morphometric study was to explore three dimensional (3D) facial shape and form (shape plus size) variation within and between 8- and 12-year-old Caucasian children; 39 males age-matched with 41 females. The 3D images were captured using a stereophotogrammeteric system, and facial form was recorded by digitizing 39 anthropometric landmarks for each scan. The x, y, z coordinates of each landmark were extracted and used to calculate linear and angular measurements. 3D landmark asymmetry was quantified using Generalized Procrustes Analysis (GPA) and an average face was constructed for each gender. The average faces were superimposed and differences were visualized and quantified. Shape variations were explored using GPA and PrincipalComponent Analysis. Analysis of covariance and Pearson correlation coefficients were used to explore gender differences and to determine any correlation between facial measurements and height or weight. Multivariate analysis was used to ascertain differences in facial measurements or 3D landmark asymmetry. There were no differences in height or weight between genders. There was a significant positive correlation between facial measurements and height and weight and statistically significant differences in linear facial width measurements between genders. These differences were related to the larger size of males rather than differences in shape. There were no age- or gender-linked significant differences in 3D landmark asymmetry. Shape analysis confirmed similarities between both males and females for facial shape and form in 8- to 12-year-old children. Any differences found were related to differences in facial size rather than shape.
本前瞻性的横断面形态计量学研究旨在探索 8-12 岁白种儿童的三维(3D)面部形状和形态(形状加大小)的内部和之间的变化;39 名男性与 41 名女性年龄匹配。使用立体摄影测量系统捕获 3D 图像,并通过为每个扫描数字化 39 个人体测量标志记录面部形态。提取每个标志的 x、y、z 坐标,并用于计算线性和角度测量。使用广义 Procrustes 分析(GPA)量化 3D 标志的不对称性,并为每个性别构建平均脸。对平均脸进行叠加,可视化和量化差异。使用 GPA 和主成分分析探索形状变化。协方差分析和 Pearson 相关系数用于探索性别差异,并确定面部测量值与身高或体重之间的任何相关性。多元分析用于确定面部测量值或 3D 标志不对称性的差异。性别之间在身高或体重上没有差异。面部测量值与身高和体重之间存在显著正相关,性别之间的线性面部宽度测量值存在统计学显著差异。这些差异与男性的更大体型有关,而与形状无关。在 3D 标志不对称性方面,没有年龄或性别相关的显著差异。形状分析证实,8-12 岁儿童的男性和女性在面部形状和形态上具有相似性。发现的任何差异都与面部大小的差异有关,而不是形状的差异。