Orthodontics & craniofacial research · 2019
Predicting adult facial type from mandibular landmark data at young ages.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Oh Heesoo, Knigge Ryan, Hardin Anna, Sherwood Richard, Duren Dana, Valiathan Manish, Leary Emily, McNulty Kieran
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.
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.