Abstract

The human facial skeleton consists of multiple segments and causes difficulty during analytic processes. We developed image analysis software to quantify the amount of injury and validate the smooth curvature of the surface after facial bone reduction surgery. Three-dimensional computed tomography images of facial bone were obtained from 40 patients who had undergone open reduction surgery to treat unilateral zygomaticomaxillary fractures. Analytic software was developed based on the discrete curvature of a triangular mesh model. The discrete curvature values were compared before and after surgery using two regions of interest. For the inferior orbital rim, the weighted average of curvature changed from 0.543 ± 0.034 to 0.458 ± 0.042. For the anterior maxilla, the weighted average of curvature changed from 0.596 ± 0.02 to 0.481 ± 0.031, showing a significant decrement (P < 0.05). The curvature was further compared with the unaffected side using the Bray–Curtis similarity index (BCSI). The BCSI of the inferior orbital rim changed from 0.802 ± 0.041 to 0.904 ± 0.015, and that for the anterior maxilla changed from 0.797 ± 0.029 to 0.84 ± 0.025, demonstrating increased similarity (P < 0.05). In computational biology, adequate analytic software is crucial. The newly developed software demonstrated significant differentiation between pre- and postoperative curvature values. Modification of formulas and software will lead to further advancements.

Details

Title
Objective analysis of facial bone fracture CT images using curvature measurement in a surface mesh model
Author
Kim, Jeenam 1 ; Seo, Chaneol 1 ; Yoo, Jung Hwan 1 ; Choi, Seung Hoon 2 ; Ko, Kwang Yeon 2 ; Choi, Hyung Jin 2 ; Lee, Ki Hyun 2 ; Choi, Hyungon 1 ; Shin, Donghyeok 1 ; Kim, HyungSeok 2 ; Lee, Myung Chul 1 

 Konkuk University, Department of Plastic and Reconstructive Surgery, School of Medicine, Seoul, Korea (GRID:grid.258676.8) (ISNI:0000 0004 0532 8339) 
 Konkuk University, Department of Computer Science and Engineering, Seoul, Korea (GRID:grid.258676.8) (ISNI:0000 0004 0532 8339) 
Pages
1932
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2771824694
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.