Literature DB >> 32100178

An automatic approach to establish clinically desired final dental occlusion for one-piece maxillary orthognathic surgery.

Han Deng1, Peng Yuan1, Sonny Wong2, Jaime Gateno1,3, Fred A Garrett2, Randy K Ellis2, Jeryl D English2, Helder B Jacob2, Daeseung Kim1, Joshua C Barber4, William Chen5, James J Xia6,7.   

Abstract

PURPOSE: One critical step in routine orthognathic surgery is to reestablish a desired final dental occlusion. Traditionally, the final occlusion is established by hand articulating stone dental models. To date, there are still no effective solutions to establish the final occlusion in computer-aided surgical simulation. In this study, we consider the most common one-piece maxillary orthognathic surgery and propose a three-stage approach to digitally and automatically establish the desired final dental occlusion.
METHODS: The process includes three stages: (1) extraction of points of interest and teeth landmarks from a pair of upper and lower dental models; (2) establishment of Midline-Canine-Molar (M-C-M) relationship following the clinical criteria on these three regions; and (3) fine alignment of upper and lower teeth with maximum contacts without breaking the established M-C-M relationship. Our method has been quantitatively and qualitatively validated using 18 pairs of dental models.
RESULTS: Qualitatively, experienced orthodontists assess the algorithm-articulated and hand-articulated occlusions while being blind to the methods used. They agreed that occlusion results of the two methods are equally good. Quantitatively, we measure and compare the distances between selected landmarks on upper and lower teeth for both algorithm-articulated and hand-articulated occlusions. The results showed that there was no statistically significant difference between the algorithm-articulated and hand-articulated occlusions.
CONCLUSION: The proposed three-stage automatic dental articulation method is able to articulate the digital dental model to the clinically desired final occlusion accurately and efficiently. It allows doctors to completely eliminate the use of stone dental models in the future.

Keywords:  Computer-aided surgical simulation; Digital dental occlusion; Feature extraction; Orthognathic surgery

Mesh:

Year:  2020        PMID: 32100178      PMCID: PMC7484002          DOI: 10.1007/s11548-020-02125-y

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


  10 in total

1.  Automated digital dental articulation.

Authors:  James J Xia; Yu-Bing Chang; Jaime Gateno; Zixiang Xiong; Xiaobo Zho
Journal:  Med Image Comput Comput Assist Interv       Date:  2010

2.  Virtual occlusion in planning orthognathic surgical procedures.

Authors:  N Nadjmi; W Mollemans; A Daelemans; G Van Hemelen; F Schutyser; S Bergé
Journal:  Int J Oral Maxillofac Surg       Date:  2010-03-11       Impact factor: 2.789

3.  Interactive tooth partition of dental mesh base on tooth-target harmonic field.

Authors:  Bei-ji Zou; Shi-jian Liu; Sheng-hui Liao; Xi Ding; Ye Liang
Journal:  Comput Biol Med       Date:  2014-11-13       Impact factor: 4.589

4.  An automatic and robust algorithm of reestablishment of digital dental occlusion.

Authors:  Yu-Bing Chang; James J Xia; Jaime Gateno; Zixiang Xiong; Xiaobo Zhou; Stephen T C Wong
Journal:  IEEE Trans Med Imaging       Date:  2010-06-07       Impact factor: 10.048

5.  Haptic simulation framework for determining virtual dental occlusion.

Authors:  Wen Wu; Hui Chen; Yuhai Cen; Yang Hong; Balvinder Khambay; Pheng Ann Heng
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-09-06       Impact factor: 2.924

6.  Some features of highly reiterated DNA in rat genome.

Authors:  S Szala; M Chorazy
Journal:  Acta Biochim Pol       Date:  1972       Impact factor: 2.149

7.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

8.  Accuracy of the computer-aided surgical simulation (CASS) system in the treatment of patients with complex craniomaxillofacial deformity: A pilot study.

Authors:  James J Xia; Jaime Gateno; John F Teichgraeber; Andrew M Christensen; Robert E Lasky; Jeremy J Lemoine; Michael A K Liebschner
Journal:  J Oral Maxillofac Surg       Date:  2007-02       Impact factor: 1.895

9.  Accuracy of a computer-aided surgical simulation protocol for orthognathic surgery: a prospective multicenter study.

Authors:  Sam Sheng-Pin Hsu; Jaime Gateno; R Bryan Bell; David L Hirsch; Michael R Markiewicz; John F Teichgraeber; Xiaobo Zhou; James J Xia
Journal:  J Oral Maxillofac Surg       Date:  2012-06-12       Impact factor: 1.895

10.  Automatic Tooth Segmentation of Dental Mesh Based on Harmonic Fields.

Authors:  Sheng-hui Liao; Shi-jian Liu; Bei-ji Zou; Xi Ding; Ye Liang; Jun-hui Huang
Journal:  Biomed Res Int       Date:  2015-08-27       Impact factor: 3.411

  10 in total
  3 in total

1.  Clinical Evaluation of Digital Dental Articulation for One-Piece Maxillary Surgery.

Authors:  Sonny Wong; Han Deng; Jaime Gateno; Peng Yuan; Fred A Garrett; Randy K Ellis; Jeryl D English; Helder B Jacob; Daeseung Kim; James J Xia
Journal:  J Oral Maxillofac Surg       Date:  2020-01-07       Impact factor: 1.895

2.  Clinical feasibility evaluation of digital dental articulation for three-piece maxillary orthognathic surgery: a proof-of-concept study.

Authors:  C J Frick; H H Deng; J D English; H B Jacob; T Kuang; M K Grissom; D Kim; J Gateno; J J Xia
Journal:  Int J Oral Maxillofac Surg       Date:  2022-02-17       Impact factor: 2.986

3.  Plaster Casts vs. Intraoral Scans: Do Different Methods of Determining the Final Occlusion Affect the Simulated Outcome in Orthognathic Surgery?

Authors:  Daniel Awad; Andy Häfner; Siegmar Reinert; Susanne Kluba
Journal:  J Pers Med       Date:  2022-08-05
  3 in total

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