title: An accurate method of predicting mandibular growth potential based on bone maturity.
abstract: Mandibular growth prediction provides important information for planning treatment and for evaluating occlusal stability after treatment. At present, several methods can predict mandibular growth, but it is not clear which method is the most accurate. This study compared the predictive error of several methods by using skeletal maturity indicators. Twenty-two longitudinal cephalograms and hand-wrist radiographs of female subjects (average initial age, 8.3 years; final age, 18.4 years) were collected to construct the prediction formula. Another 22 female subjects (initial age, 10.8 years; final age, 18.6 years) were examined to compare differences between the predicted values and the actual values. Mandibular total length (condylion-gnathion) at the final stage can be accurately predicted by (1) the ossification events of the third middle phalanx and the radius, (2) the growth potential method, (3) the growth percentage method, (4) the multiple regression method, and (5) the growth chart method. Bone age as a parameter was calculated by both the Tanner-Whitehouse 2 (TW2) method and the computer-aided skeletal maturity assessment system (CASMAS) that we developed. The average error between the predicted length of condylion to gnathion and the actual length at the final stage for each method was (1) 3.0 mm; (2) 2.1 mm (TW2), 2.4 mm (CASMAS); (3) 2.3 mm (TW2), 2.6 mm (CASMAS); (4) 4.3 mm (TW2), 4.9 mm (CASMAS); and (5) 3.6 mm (TW2), 3.7 mm (CASMAS). The growth potential method and the growth percentage method were the most accurate predictors of mandibular growth potential.
authors.affiliation: Division of Orthodontics, Department of Lifelong Oral Health Science, Graduate School of Dentistry, Tohoku University, Sendai, Japan. koshi@mail.cc.tohoku.ac.jp
authors.forename: K
authors.initials: K
authors.lastname: Sato
authors.forename: T
authors.initials: T
authors.lastname: Mito
authors.forename: H
authors.initials: H
authors.lastname: Mitani
mesh_terms: D000293:Adolescent; D000465:Algorithms; D000704:Analysis of Variance; D002508:Cephalometry; D002648:Child; D005260:Female; D005385:Fingers / Q000254:growth & development; D005544:Forecasting; D006801:Humans; D008334:Mandible / Q000254:growth & development*; D012044:Regression Analysis; D015203:Reproducibility of Results; D014953:Wrist / Q000254:growth & development