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DOI 10.1111/ocr.12296

Медицинская библиотека · Orthodontics & craniofacial research · 2019

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

Oh Heesoo, Knigge Ryan, Hardin Anna, Sherwood Richard, Duren Dana, Valiathan Manish, Leary Emily, McNulty Kieran

СтатьяПеревод пока не подготовлен

Аннотация

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.

Для цитирования: Oh Heesoo, Knigge Ryan, Hardin Anna, Sherwood Richard, Duren Dana, Valiathan Manish, Leary Emily, McNulty Kieran. Predicting adult facial type from mandibular landmark data at young ages.. Orthodontics & craniofacial research. 2019. DOI: 10.1111/ocr.12296.

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