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Three-dimensional soft tissue prediction in orthognathic surgery: a clinical comparison of Dolphin,ProPlan CMF,and probabilistic finite element modelling
Authors:P.G.M. Knoops  A. Borghi  R.W.F. Breakey  J. Ong  N.U.O. Jeelani  R. Bruun  S. Schievano  D.J. Dunaway  B.L. Padwa
Affiliation:1. UCL Great Ormond Street Institute of Child Health, London, UK;2. Craniofacial Unit, Great Ormond Street Hospital for Children, London, UK;3. Department of Plastic and Oral Surgery, Boston Children’s Hospital & Harvard School of Dental Medicine, Boston, Massachusetts, USA
Abstract:Three-dimensional surgical planning is used widely in orthognathic surgery. Although numerous computer programs exist, the accuracy of soft tissue prediction remains uncertain. The purpose of this study was to compare the prediction accuracy of Dolphin, ProPlan CMF, and a probabilistic finite element method (PFEM). Seven patients (mean age 18 years; five female) who had undergone Le Fort I osteotomy with preoperative and 1-year postoperative cone beam computed tomography (CBCT) were included. The three programs were used for soft tissue prediction using planned and postoperative maxillary position, and these were compared to postoperative CBCT. Accurate predictions were obtained with each program, indicated by root mean square distances: RMSDolphin = 1.8 ± 0.8 mm, RMSProPlan = 1.2 ± 0.4 mm, and RMSPFEM = 1.3 ± 0.4 mm. Dolphin utilizes a landmark-based algorithm allowing for patient-specific bone-to-soft tissue ratios, which works well for cephalometric radiographs but has limited three-dimensional accuracy, whilst ProPlan and PFEM provide better three-dimensional predictions with continuous displacements. Patient or population-specific material properties can be defined in PFEM, while no soft tissue parameters are adjustable in ProPlan. Important clinical considerations are the topological differences between predictions due to the three algorithms, the non-negligible influence of the mismatch between planned and postoperative maxillary position, and the learning curve associated with sophisticated programs like PFEM.
Keywords:soft tissue prediction  virtual surgery planning  orthognathic surgery  craniofacial surgery  Dolphin  ProPlan CMF  finite element modelling
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