Two-stage simulation method to improve facial soft tissue prediction accuracy for orthognathic surgery

Daeseung Kim; Chien Ming Chang; Dennis Chun Yu Ho; Xiaoyan Zhang; Shunyao Shen; Peng Yuan; Huaming Mai; Guangming Zhang; Xiaobo Zhou; Jaime Gateno; Michael A.K. Liebschner; James J. Xia

doi:10.1007/978-3-319-46720-7_65

Two-stage simulation method to improve facial soft tissue prediction accuracy for orthognathic surgery

Daeseung Kim, Chien Ming Chang, Dennis Chun Yu Ho, Xiaoyan Zhang, Shunyao Shen, Peng Yuan, Huaming Mai, Guangming Zhang, Xiaobo Zhou, Jaime Gateno, Michael A.K. Liebschner, James J. Xia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

It is clinically important to accurately predict facial soft tissue changes prior to orthognathic surgery. However,the current simulation methods are problematic,especially in clinically critical regions. We developed a two-stage finite element method (FEM) simulation model with realistic tissue sliding effects. In the 1^st stage,the facial soft-tissue-change following bone movement was simulated using FEM with a simple sliding effect. In the 2^nd stage,the tissue sliding effect was improved by reassigning the bone-soft tissue mapping and boundary condition. Our method has been quantitatively and qualitatively evaluated using 30 patient datasets. The two-stage FEM simulation method showed significant accuracy improvement in the whole face and the critical areas (i.e.,lips,nose and chin) in comparison with the traditional FEM method.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
Editors	Sebastian Ourselin, Leo Joskowicz, Mert R. Sabuncu, William Wells, Gozde Unal
Publisher	Springer Verlag
Pages	559-567
Number of pages	9
ISBN (Print)	9783319467191
DOIs	https://doi.org/10.1007/978-3-319-46720-7_65
Publication status	Published - 2016
Externally published	Yes
Event	1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece Duration: Oct 21 2016 → Oct 21 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9900 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
Country/Territory	Greece
City	Athens
Period	10/21/16 → 10/21/16

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-46720-7_65

Cite this

Kim, D., Chang, C. M., Ho, D. C. Y., Zhang, X., Shen, S., Yuan, P., Mai, H., Zhang, G., Zhou, X., Gateno, J., Liebschner, M. A. K., & Xia, J. J. (2016). Two-stage simulation method to improve facial soft tissue prediction accuracy for orthognathic surgery. In S. Ourselin, L. Joskowicz, M. R. Sabuncu, W. Wells, & G. Unal (Eds.), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings (pp. 559-567). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9900 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46720-7_65

Two-stage simulation method to improve facial soft tissue prediction accuracy for orthognathic surgery. / Kim, Daeseung; Chang, Chien Ming; Ho, Dennis Chun Yu et al.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. ed. / Sebastian Ourselin; Leo Joskowicz; Mert R. Sabuncu; William Wells; Gozde Unal. Springer Verlag, 2016. p. 559-567 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9900 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kim, D, Chang, CM, Ho, DCY, Zhang, X, Shen, S, Yuan, P, Mai, H, Zhang, G, Zhou, X, Gateno, J, Liebschner, MAK & Xia, JJ 2016, Two-stage simulation method to improve facial soft tissue prediction accuracy for orthognathic surgery. in S Ourselin, L Joskowicz, MR Sabuncu, W Wells & G Unal (eds), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9900 LNCS, Springer Verlag, pp. 559-567, 1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, Athens, Greece, 10/21/16. https://doi.org/10.1007/978-3-319-46720-7_65

Kim D, Chang CM, Ho DCY, Zhang X, Shen S, Yuan P et al. Two-stage simulation method to improve facial soft tissue prediction accuracy for orthognathic surgery. In Ourselin S, Joskowicz L, Sabuncu MR, Wells W, Unal G, editors, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Springer Verlag. 2016. p. 559-567. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46720-7_65

Kim, Daeseung ; Chang, Chien Ming ; Ho, Dennis Chun Yu et al. / Two-stage simulation method to improve facial soft tissue prediction accuracy for orthognathic surgery. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. editor / Sebastian Ourselin ; Leo Joskowicz ; Mert R. Sabuncu ; William Wells ; Gozde Unal. Springer Verlag, 2016. pp. 559-567 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "It is clinically important to accurately predict facial soft tissue changes prior to orthognathic surgery. However,the current simulation methods are problematic,especially in clinically critical regions. We developed a two-stage finite element method (FEM) simulation model with realistic tissue sliding effects. In the 1st stage,the facial soft-tissue-change following bone movement was simulated using FEM with a simple sliding effect. In the 2nd stage,the tissue sliding effect was improved by reassigning the bone-soft tissue mapping and boundary condition. Our method has been quantitatively and qualitatively evaluated using 30 patient datasets. The two-stage FEM simulation method showed significant accuracy improvement in the whole face and the critical areas (i.e.,lips,nose and chin) in comparison with the traditional FEM method.",

author = "Daeseung Kim and Chang, {Chien Ming} and Ho, {Dennis Chun Yu} and Xiaoyan Zhang and Shunyao Shen and Peng Yuan and Huaming Mai and Guangming Zhang and Xiaobo Zhou and Jaime Gateno and Liebschner, {Michael A.K.} and Xia, {James J.}",

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AU - Yuan, Peng

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AU - Gateno, Jaime

AU - Liebschner, Michael A.K.

AU - Xia, James J.

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AB - It is clinically important to accurately predict facial soft tissue changes prior to orthognathic surgery. However,the current simulation methods are problematic,especially in clinically critical regions. We developed a two-stage finite element method (FEM) simulation model with realistic tissue sliding effects. In the 1st stage,the facial soft-tissue-change following bone movement was simulated using FEM with a simple sliding effect. In the 2nd stage,the tissue sliding effect was improved by reassigning the bone-soft tissue mapping and boundary condition. Our method has been quantitatively and qualitatively evaluated using 30 patient datasets. The two-stage FEM simulation method showed significant accuracy improvement in the whole face and the critical areas (i.e.,lips,nose and chin) in comparison with the traditional FEM method.

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Two-stage simulation method to improve facial soft tissue prediction accuracy for orthognathic surgery

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