Facial morphospace: a clinical quantitative analysis of the three-dimensional face in patients with cleft lip and palate

• 作者: Chihiro Tanikawa
• 来源期刊: 整形与美容研究（英文版）
• 年，卷（期）: 2020,（9）
• 所属期刊栏目: Original Article
• 页码范围: 18-33
• 页数: 16页
• 语种: 英文
• DOI: 10.20517/2347-9264.2020.136

摘要

Aim: The aims were: (1) to examine the clinical application of a geometric morphometric method (GMM) that quantifies the three-dimensional (3D) configuration of the facial soft tissues in patients with a repaired unilateral cleft lip and palate (UCLP); and (2) to determine the morphological characteristics that distinguish between non-cleft participants and patients with UCLP.Methods: 3D facial images at rest were recorded from Japanese patients with a repaired UCLP (Cleft group; n = 60) and healthy adults featuring a straight type facial profile with normal occlusion (Control group; n = 200) using 3D photogrammetric cameras. For each participant, wire mesh fitting was conducted based on the assignment of landmarks to each 3D facial image. This method generated landmark-based GMM models consisting of 6017 nodes on the fitted wire mesh. For each node, the mean and standard deviation were determined in the Control group and were used as the normative range of the faces. With this normative range, the Z-scores before and after surgery were evaluated for patients with UCLP who underwent orthognathic bimaxillary surgery. Further, the morphological characteristics of the Cleft group were evaluated using a principal component (PC) regression analysis that distinguished between two subject groups. In addition, K-means clustering analysis and MANOVA were used to examine the morphological variation of the Cleft group. Results: A patient with UCLP was evaluated with the system. After surgery, the normal area increased by 8％-20％ on all axes, which means that the surgery was effective for normalizing the patient's face. However, even after surgery, the protrusion of the lower lip and asymmetry remained. Nine PCs were extracted, and seven PCs were selected for the regression model to discriminate two subject groups, e.g., midfacial retrusion, nasal bump, and chin protrusion. The MANOVA also revealed significant differences between both the Cleft and Control groups and the sex subgroups, and the effects of cleft on the facial morphology was found to be related to sex (all, P < 0.01).Conclusion: The clinical application of GMM was confirmed to be effective. GMM detected variations of the Cleft group and morphological characteristics. GMM is considered to be a powerful tool to quantitatively evaluate faces in clinics.