Date: March 2021.
Source: International Journal of Legal Medicine. https://doi.org/10.1007/s00414-021-02559-2.
Abstract: Lips are the main part of the lower facial soft tissue and are vital to forensic facial approximation (FFA). Facial soft tissue thickness (FSTT) and linear measurements in three dimensions are used in the quantitative analysis of lip morphology. With most FSTT analysis methods, the surface of soft tissue is unexplicit. Our study aimed to determine FSTT and explore the relationship between the hard and soft tissues of lips in different skeletal occlusions based on cone-beam CT (CBCT) and 3dMD images in a Chinese population. The FSTT of 11 landmarks in CBCT and 29 lip measurements in CBCT and 3dMD of 180 healthy Chinese individuals (90 males, 90 females) between 18 and 30 years were analyzed. The subjects were randomly divided into two groups with different skeletal occlusions distributed equally: 156 subjects in the experimental group to establish the prediction regression formulae of lip morphology and 24 subjects in the test group to assess the accuracy of the formulae. The results indicated that FSTT in the lower lip region varied among different skeletal occlusions. Furthermore, sex discrepancy was noted in the FSTT in midline landmarks and linear measurements. Measurements showing the highest correlation between soft and hard tissues were between total upper lip height and Ns-Pr (0.563 in males, 0.651 in females). The stepwise multiple regression equations were verified to be reliable with an average error of 1.246 mm. The method of combining CBCT with 3dMD provides a new perspective in predicting lip morphology and expands the database for FFA.
Article: Lip morphology estimation models based on three-dimensional images in a modern adult population from China.
Authors: Jia-min Zhao, Ling-ling Ji, Meng-qi Han, Qing-nan Mou, Guang Chu, Teng Chen, Shao-yi Du, Yu-xia Hou and Yu-cheng Guo. Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China.