Literature DB >> 27856149

Accuracy of three-dimensional soft tissue prediction for Le Fort I osteotomy using Dolphin 3D software: a pilot study.

C M Resnick1, R R Dang2, S J Glick3, B L Padwa2.   

Abstract

Three-dimensional (3D) soft tissue prediction is replacing two-dimensional analysis in planning for orthognathic surgery. The accuracy of different computational models to predict soft tissue changes in 3D, however, is unclear. A retrospective pilot study was implemented to assess the accuracy of Dolphin 3D software in making these predictions. Seven patients who had a single-segment Le Fort I osteotomy and had preoperative (T0) and >6-month postoperative (T1) cone beam computed tomography (CBCT) scans and 3D photographs were included. The actual skeletal change was determined by subtracting the T0 from the T1 CBCT. 3D photographs were overlaid onto the T0 CBCT and virtual skeletal movements equivalent to the achieved repositioning were applied using Dolphin 3D planner. A 3D soft tissue prediction (TP) was generated and differences between the TP and T1 images (error) were measured at 14 points and at the nasolabial angle. A mean linear prediction error of 2.91±2.16mm was found. The mean error at the nasolabial angle was 8.1±5.6°. In conclusion, the ability to accurately predict 3D soft tissue changes after Le Fort I osteotomy using Dolphin 3D software is limited.
Copyright © 2016 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  3D prediction; Le Fort I osteotomy; orthognathic surgery; virtual treatment planning

Mesh:

Year:  2016        PMID: 27856149     DOI: 10.1016/j.ijom.2016.10.016

Source DB:  PubMed          Journal:  Int J Oral Maxillofac Surg        ISSN: 0901-5027            Impact factor:   2.789


  10 in total

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2.  Accuracy of Soft Tissue Prediction of 2 Virtual Planning Systems in Patients Undergoing Intraoral Quadrangular Le Fort II Osteotomy.

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Authors:  Ali Modabber; Tanja Baron; Florian Peters; Kristian Kniha; Golamreza Danesh; Frank Hölzle; Nassim Ayoub; Stephan Christian Möhlhenrich
Journal:  Sci Rep       Date:  2022-03-23       Impact factor: 4.379

  10 in total

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