1. Accuracy of 3-dimensional soft tissue prediction for orthognathic surgery in a Chinese population.
- Author
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Lee KJC, Tan SL, Low HYA, Chen LJ, Yong CW, and Chew MT
- Subjects
- Cephalometry methods, China, Face surgery, Humans, Imaging, Three-Dimensional methods, Orthognathic Surgery
- Abstract
Objectives: This study aims to determine the validity of a 3D planning software in predicting the soft tissue outcome of Chinese patients undergoing orthognathic surgery for correction of Skeletal III dentofacial deformity., Methods: Pre- and post-operative 3D facial stereophotogrammetric scans and cone beam computed tomography were taken for 10 Chinese patients who had underwent orthognathic surgery. The pre-operative 3D facial scan was integrated with the pre-operative CBCT using the ProPlan CMF software. The simulated soft tissue 3D face was then compared with the actual 3D facial scan obtained at least 6 months postoperatively. Two outcome measures were computed as follows (i) mean absolute difference between meshes (ii) percentage of points where the distance between the two meshes is 2mm or less., Results: The mean absolute difference between the predicted and actual soft tissue surface meshes for the full face and the 6 anatomic regions ranged from 0.72mm to 1.42 mm. The mean absolute distance between the meshes for all the anatomic regions were within 2 mm (p<0.05). The percentage of mesh points with less than 2mm error ranged from 72.5% to 92.5%. The accuracy of soft tissue prediction, assessed using mean absolute distance for the full face, was significantly correlated to the amount of sagittal surgical movement (r=0.707, p=0.022). The lower lip was also found to be the least accurate., Conclusions: Using ProPlan CMF, the accuracy of 3D soft tissue predictions for bimaxillary orthognathic surgery in Chinese Skeletal III patients were clinically satisfactory., Competing Interests: Conflict of Interest Nil conflict of interest to be declared, (Copyright © 2021. Published by Elsevier Masson SAS.)
- Published
- 2022
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