Evaluation of Ricketts' and Bolton's growth prediction algorithms embedded in two diagnostic imaging and cephalometric software

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• 作者：Matthew Sagun^a ; Budi Kusnoto^b ; ^{bkusno1@uic.edu" class="auth_mail" title="E-mail the corresponding author} ; ^{bkusno1@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Carla A. Evans^c ; Maria Therese Galang-Boquiren^d ; Grace Viana^e ; Ales Obrez^f
• 关键词：Growth-prediction ; Computerized ; Diagnostic ; Ricketts ; Bolton ; Algorithm
• 刊名：Journal of the World Federation of Orthodontists
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：4
• 期：4
• 页码：146-150
• 全文大小：843 K

文摘

Accurate assessment and prediction of skeletal and dentofacial growth are very important for planning orthodontic treatment and achieving stable and esthetic outcomes. Several algorithms (e.g. Bolton and Ricketts) for predicting craniofacial growth using lateral cephalograms are available to clinicians in commercial computer software packages.

Methods

This retrospective study compares the reliability of craniofacial growth of three growth prediction algorithms currently available in Dolphin Imaging™ 11.0 and RMODS-JOE CEPH^® programs. Lateral cephalograms of skeletal normal class I of 56 untreated children obtained from the Craniofacial Growth Legacy Collection of the American Association of Orthodontists Foundation (AAOF) were used to evaluate the Ricketts and Bolton growth prediction algorithms in Dolphin Imaging™ 11.0 as well as the Ricketts growth prediction algorithm in RMODS-JOE CEPH^®. The groups were subdivided by growth prediction algorithm, gender, chronological age, developmental age and length of rediction. Student t-tests were used to compare the mean differences of the growth predictions tested.

Results and discussions

This study showed no differences with respect to developmental age and gender, but the two-year predictions appear to be more valid than the four-year predictions. The Bolton growth prediction algorithm in Dolphin Imaging 11.0 and the Ricketts growth prediction algorithm in RMODS-JOE CEPH^® were more alike among the three.

Conclusions

The three growth prediction algorithms tested indicated to be within a 1.5 mm clinical reference when compared with the actual growth of the same subject studied for the majority of the landmarks assessed, indicating their clinically reference acceptability specially for a two year prediction.