title: Validation of adult height prediction based on automated bone age determination in the Paris Longitudinal Study of healthy children.
abstract: BACKGROUND
  An adult height prediction model based on automated determination of bone age was developed and validated in two studies from Zurich, Switzerland. Varied living conditions and genetic backgrounds might make the model less accurate.
  
  
  OBJECTIVE
  To validate the adult height prediction model on children from another geographical location.
  
  
  METHODS
  We included 51 boys and 58 girls from the Paris Longitudinal Study of children born 1953 to 1958. Radiographs were obtained once or twice a year in these children from birth to age 18. Bone age was determined using the BoneXpert method. Radiographs in children with bone age greater than 6 years were considered, in total 1,124 images.
  
  
  RESULTS
  The root mean square deviation between the predicted and the observed adult height was 2.8 cm for boys in the bone age range 6-15 years and 3.1 cm for girls in the bone age range 6-13 years. The bias (the average signed difference) was zero, except for girls below bone age 12, where the predictions were 0.8 cm too low.
  
  
  CONCLUSIONS
  The accuracy of the BoneXpert method in terms of root mean square error was as predicted by the model, i.e. in line with what was observed in the Zurich studies.
authors.affiliation: Tübingen University Children's Hospital, Hoppe-Seyler-Str. 1, D-72076, Tübingen, Germany. David.martin@med.uni-tuebingen.de.|Filderklinik, Im Haberschlai 7, D-70794, Filderstadt, Germany. David.martin@med.uni-tuebingen.de.
authors.forename: David D
authors.initials: DD
authors.lastname: Martin
authors.affiliation: Tübingen University Children's Hospital, Hoppe-Seyler-Str. 1, D-72076, Tübingen, Germany.
authors.forename: Jan
authors.initials: J
authors.lastname: Schittenhelm
authors.affiliation: Visiana, Holte, Denmark.
authors.forename: Hans Henrik
authors.initials: HH
authors.lastname: Thodberg
mesh_terms: D000293:Adolescent; D000328:Adult; D000365:Age Determination by Skeleton / Q000379:methods* / Q000706:statistics & numerical data*; D017677:Age Distribution; D000375:Aging / Q000502:physiology*; D001827:Body Height / Q000502:physiology*; D002648:Child; D002675:Child, Preschool; D005260:Female; D005602:France / Q000453:epidemiology; D006225:Hand / Q000000981:diagnostic imaging*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008137:Longitudinal Studies; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D017678:Sex Distribution; D013557:Switzerland / Q000453:epidemiology; D055815:Young Adult
keywords: Automated image analysis; Bone age; Child; Height prediction; Model; Radiography; Validation