title: Predicting mandibular growth increment on the basis of cervical vertebral dimensions in Iranian girls.
abstract: BACKGROUND
  The purpose of this longitudinal study was to establish an equation to predict incremental mandibular length on the basis of the analysis of the cervical vertebrae on a single cephalometric radiograph and to compare the predictive accuracy with the method by Mito et al.
  
  
  METHODS
  Data consist of a group of 33 Iranian girls, 9 to 11 years old with two lateral cephalometric radiographs taken at a 24-month interval. For each individual, on the lateral cephalometric radiographs, points and lines for the description of the morphologic characteristics of the third and fourth cervical vertebral bodies were traced and measured. The real mandibular length increment (MLI) in this period was determined by the difference between the second (24 months) and first (baseline) radiographs: MLI=Ar-Pog (second)-Ar-Pog (first). An equation was determined to calculate mandibular length increments on the basis of the measurements in the third and fourth cervical vertebral bodies. The predictive accuracy was assessed using multiple regression analysis.
  
  
  RESULTS
  The adjusted R2 for this equation was 54.9% which is a reliable value for evaluating prediction accuracy .The average error between the predicted increment and the actual increment was 0.149 mm for our method and 5.87 mm for the method by Mito et al.
  
  
  CONCLUSIONS
  There are two items that contributed to easier and better prediction accuracy in our equation: (1) higher R2 and (2) fewer independent variables. In our subjects, the prediction accuracy was lower when using Mito et al.'s method, which could be due to genetic and environmental factors and selected age range.
  
  
  CONCLUSIONS
  These results indicate that cervical vertebral measurements, obtained in lateral cephalograms, are able to predict properly the mandibular growth potential.
authors: Department of Oral and Maxillofacial Radiology, Kerman University of Medical Sciences, Kerman, , Iran. Hajirrahimi@gmail.com.
authors: Mahkameh
authors: M
authors: Moshfeghi
authors: Hajir
authors: H
authors: Rahimi
authors: Hoda
authors: H
authors: Rahimi
authors: Mahtab
authors: M
authors: Nouri
authors: Alireza Akbarzadeh
authors: AA
authors: Bagheban
mesh_terms: D002508:Cephalometry / Q000379:methods / Q000706:statistics & numerical data; D002574:Cervical Vertebrae / Q000033:anatomy & histology*; D002648:Child; D005260:Female; D005500:Follow-Up Studies; D005544:Forecasting; D006801:Humans; D007492:Iran; D008137:Longitudinal Studies; D008334:Mandible / Q000033:anatomy & histology / Q000254:growth & development*; D012044:Regression Analysis