ArticleOrthodontics & craniofacial research2019
Predicting adult facial type from mandibular landmark data at young ages.
Article in Orthodontics & craniofacial research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Comparison of individualized facial growth prediction models using artificial intelligence and partial least squares based on the Mathews growth collection.The Angle orthodontist · 2025Article
- Cross-sectional data accurately model longitudinal growth in the craniofacial skeleton.Scientific reports · 2023Article
- Classification of Maxillofacial Morphology by Artificial Intelligence Using Cephalometric Analysis Measurements.Diagnostics (Basel, Switzerland) · 2023Article
- Craniofacial growth and morphology among intersecting clinical categories.Anatomical record (Hoboken, N.J. : 2007) · 2022Article
- Geometric morphometric analysis of growth patterns among facial types.American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics · 2021Article
- Bayesian approach to longitudinal craniofacial growth: The Craniofacial Growth Consortium Study.Anatomical record (Hoboken, N.J. : 2007) · 2021Article
- Mandibular shape prediction using cephalometric analysis: applications in craniofacial analysis, forensic anthropology and archaeological reconstruction.Maxillofacial plastic and reconstructive surgery · 2020Article
- Clinical implications of age-related change of the mandibular plane angle.Orthodontics & craniofacial research · 2020Article
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Authors and funding
8 authors.
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Abstract
objectivesTo assess the potential of predicting adult facial types at different stages of mandibular development. SETTING AND SAMPLE POPULATION: 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. MATERIAL AND
methodsEach 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.
resultsAlthough 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.
conclusionsThe 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.
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