Craniofacial Research Instrumentation Lab, Department of Orthodontics, University of Pacific Arthur A. Dugoni School of Dentistry, San Francisco, California.
Department of Pathology and Anatomical Sciences, University of Missouri, Columbia, Missouri.
Orthod Craniofac Res. 2019 May;22 Suppl 1(Suppl 1):154-162. doi: 10.1111/ocr.12296.
To assess the potential of predicting adult facial types at different stages of mandibular development.
A total of 941 participants from the Bolton-Brush, Denver, Fels, Iowa, Michigan and Oregon growth studies with longitudinal lateral cephalograms (total of 7166) between ages 6-21 years.
Each participant was placed into one of three facial types based on mandibular plane angle (MPA) from cephalograms taken closest to 18 years of age (range of 15-21 years): hypo-divergent (MPA < 28°), normo-divergent (28°≤ MPA ≤ 39°) and hyper-divergent (MPA > 39°). Cephalograms were categorized into 13 age groups 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 and 18-21. Twenty-three two-dimensional anatomical landmarks were digitized on the mandible and superimposed using generalized Procrustes analysis, which projects landmarks into a common shape space. Data were analysed within age categories using stepwise discriminant analysis to identify landmarks that distinguish adult facial types and by jackknife cross-validation to test how well young individuals can be reclassified into their adult facial types.
Although each category has multiple best discriminating landmarks among adult types, three landmarks were common across nearly all age categories: menton, gonion and articulare. Individuals were correctly classified better than chance, even among the youngest age category. Cross-validation rates improved with age, and hyper- and hypo-divergent groups have better reclassification rates than the normo-divergent group.
The discovery of important indicators of adult facial type in the developing mandible helps improve our capacity to predict adult facial types at a younger age.
评估在下颌骨发育的不同阶段预测成人面型的潜力。
来自博尔顿-布鲁什、丹佛、费尔斯、爱荷华、密歇根和俄勒冈生长研究的共 941 名参与者，这些参与者的纵向侧位头颅侧位片（共 7166 张）拍摄于 6-21 岁之间。
根据最接近 18 岁时拍摄的头颅侧位片上的下颌平面角（MPA），将每个参与者归入三种面型之一（MPA 范围为 15-21 岁）：低角型（MPA<28°）、均角型（28°≤MPA≤39°）和高角型（MPA>39°）。头颅侧位片分为 13 个年龄组：6、7、8、9、10、11、12、13、14、15、16、17 和 18-21 岁。在下颌骨上数字化了 23 个二维解剖标志，并使用广义 Procrustes 分析进行叠加，该分析将标志投影到共同的形状空间中。在每个年龄组内使用逐步判别分析来识别区分成人面型的标志，并通过 jackknife 交叉验证来测试年轻个体被重新分类为其成人面型的准确性。
尽管每个类别在成人类型中都有多个最佳区分标志，但有三个标志几乎在所有年龄类别中都是常见的：颏下点、下颌角点和关节点。个体的分类准确率高于随机水平，即使在最年轻的年龄组也是如此。随着年龄的增长，交叉验证率提高，高角型和低角型组的重新分类率高于均角型组。
在下颌骨发育过程中发现成人面型的重要指标有助于提高我们在更年轻时预测成人面型的能力。
