Literature DB >> 31074133

Predicting adult facial type from mandibular landmark data at young ages.

Heesoo Oh1, Ryan Knigge2,3, Anna Hardin2, Richard Sherwood2,3, Dana Duren2,3, Manish Valiathan4, Emily Leary3, Kieran McNulty5.   

Abstract

OBJECTIVES: To 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 METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  facial type; geometric morphometrics; longitudinal growth; mandibular shape

Mesh:

Year:  2019        PMID: 31074133      PMCID: PMC6512854          DOI: 10.1111/ocr.12296

Source DB:  PubMed          Journal:  Orthod Craniofac Res        ISSN: 1601-6335            Impact factor:   1.826


  17 in total

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5.  The role of mandibular plane inclination in orthodontic diagnosis.

Authors:  S E Bishara; E F Augspurger
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8.  Morphospatial analysis of soft-tissue profile in patients with Class II Division 1 malocclusion treated using twin block appliances: geometric morphometrics.

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Journal:  Orthod Craniofac Res       Date:  2002-02       Impact factor: 1.826

9.  Morphometric covariation between palatal shape and skeletal pattern in Class II growing subjects.

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  3 in total

1.  Clinical implications of age-related change of the mandibular plane angle.

Authors:  Anna M Hardin; Manish Valiathan; Heesoo Oh; Ryan P Knigge; Kieran P McNulty; Emily V Leary; Dana L Duren; Richard J Sherwood
Journal:  Orthod Craniofac Res       Date:  2019-10-01       Impact factor: 1.826

2.  Craniofacial growth and morphology among intersecting clinical categories.

Authors:  Ryan P Knigge; Anna M Hardin; Kevin M Middleton; Kieran P McNulty; Hee Soo Oh; Manish Valiathan; Dana L Duren; Richard J Sherwood
Journal:  Anat Rec (Hoboken)       Date:  2022-02-11       Impact factor: 2.227

3.  Bayesian approach to longitudinal craniofacial growth: The Craniofacial Growth Consortium Study.

Authors:  Richard J Sherwood; Hee Soo Oh; Manish Valiathan; Kieran P McNulty; Dana L Duren; Ryan P Knigge; Anna M Hardin; Christina L Holzhauser; Kevin M Middleton
Journal:  Anat Rec (Hoboken)       Date:  2020-10-12       Impact factor: 2.227

  3 in total

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