Hallac Rami R, Thrikutam Nikhitha, Chou Pang-Yun, Huang Rong, Seaward James R, Kane Alex A
Department of Plastic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Analytical Imaging and Modeling Center, Children's Medical Center, Dallas, TX, USA.
Cleft Palate Craniofac J. 2020 Apr;57(4):430-437. doi: 10.1177/1055665619887628. Epub 2019 Nov 14.
Facial normalcy, as measured with 2-dimensional or 3-dimensional photographs, has been documented in the healthy pediatric population. However, static images convey far from a complete representation of an individual's daily interactions with peers. Craniofacial surgery induces changes to soft or osseous tissues and thereby affects dynamic facial expression. To-date, there has not been rigorous, dynamic quantification of normal facial expression. In this study, we used 4-dimensional (4D) imaging to assess the facial expression of healthy children to provide a normative reference point for craniofacial surgeons.
A total of 36 healthy pediatric volunteers underwent 4D video recordings while performing a maximal voluntary smile. A face template containing 884 landmarks was registered and tracked throughout the videos using Dimensional Imaging software. Participants were divided into 2 smile groups: open-lip smile and closed-lip smile. Kinematic analysis of smiles was calculated for every landmark from its position in the resting frame to its terminal displacement.
Composite smiles and Euclidean distance maps were generated displaying areas of greatest displacement near the oral commissures. There was significant difference between closed-lip and open-lip groups in regions of eyes and cheeks. In addition, the open-lip smile group demonstrated significantly greater displacement in the oral commissure on the left side compared to the right ( < .05); whereas, in the closed-lip group, the eyes and cheeks moved significantly more on the right side.
This study presents an innovative method that can be used to evaluate facial expressions to help craniofacial surgeons restore functional movement in patients with facial anomalies.
通过二维或三维照片测量的面部正常情况已在健康儿童群体中得到记录。然而，静态图像远不能完整呈现个体与同龄人日常互动的情况。颅面外科手术会引起软组织或骨组织的变化，从而影响面部动态表情。迄今为止，尚未有对正常面部表情进行严格的动态量化研究。在本研究中，我们使用四维（4D）成像技术评估健康儿童的面部表情，为颅面外科医生提供一个标准参考点。
共有36名健康儿童志愿者在进行最大程度的自主微笑时接受了4D视频记录。使用维度成像软件在整个视频中对包含884个地标点的面部模板进行配准和跟踪。参与者被分为两组微笑类型：露唇微笑和闭唇微笑。对每个地标点从静止帧位置到最终位移进行微笑的运动学分析。
生成了复合微笑和欧几里得距离图，显示出口角附近位移最大的区域。在眼睛和脸颊区域，闭唇组和露唇组之间存在显著差异。此外，露唇微笑组左侧口角的位移明显大于右侧（<.05）；而在闭唇组中，右侧眼睛和脸颊的移动更为明显。
本研究提出了一种创新方法，可用于评估面部表情，以帮助颅面外科医生恢复面部异常患者的功能运动。
