Sarhan François-Régis, Olivetto Matthieu, Ben Mansour Khalil, Neiva Cécilia, Colin Emilien, Choteau Baptiste, Marie Jean-Paul, Testelin Sylvie, Marin Frédéric, Dakpé Stéphanie
UR 7516 CHIMERE, Université de Picardie Jules Verne, Amiens, France.
Maxillofacial Surgery Department, CHU Amiens-Picardie, Amiens, France.
Clin Anat. 2023 Apr;36(3):492-502. doi: 10.1002/ca.23999. Epub 2023 Jan 24.
Most techniques for evaluating unilateral impairments in facial movement yield subjective measurements. The objective of the present study was to define a reference dataset and develop a visualization tool for clinical assessments. In this prospective study, a motion capture system was used to quantify facial movements in 30 healthy adults and 2 patients. We analyzed the displacements of 105 reflective markers placed on the participant's face during five movements (M1-M5). For each marker, the primary endpoint was the maximum amplitude of displacement from the static position (M0) in an analysis of variance. The measurement precision was 0.1 mm. Significant displacements of markers were identified for M1-M5, and displacement patterns were defined. The patients and age-matched healthy participants were compared with regard to the amplitude of displacement. We created a new type of radar plot to visually represent the diagnosis and facilitate effective communication between medical professionals. In proof-of-concept experiments, we collected quantitative data on patients with facial palsy and created a patient-specific radar plot. Our new protocol for clinical facial motion capture ("quantified analysis of facial movement," QAFM) was accurate and should thus facilitate the long-term clinical follow-up of patients with facial palsy. To take account of the limitations affecting the comparison with the healthy side, we created a dataset of healthy facial movements; our method might therefore be applicable to other conditions in which movements on one or both sides of the face are impaired. The patient-specific radar plot enables clinicians to read and understand the results rapidly.
大多数评估面部运动单侧损伤的技术都产生主观测量结果。本研究的目的是定义一个参考数据集，并开发一种用于临床评估的可视化工具。在这项前瞻性研究中，使用运动捕捉系统对30名健康成年人和2名患者的面部运动进行量化。我们分析了在五种运动（M1 - M5）过程中放置在参与者面部的105个反光标记的位移。对于每个标记，主要终点是在方差分析中从静态位置（M0）的最大位移幅度。测量精度为0.1毫米。确定了M1 - M5标记的显著位移，并定义了位移模式。比较了患者和年龄匹配的健康参与者的位移幅度。我们创建了一种新型雷达图，以直观地呈现诊断结果，并促进医学专业人员之间的有效沟通。在概念验证实验中，我们收集了面瘫患者的定量数据，并创建了患者特异性雷达图。我们新的临床面部运动捕捉方案（“面部运动量化分析”，QAFM）准确无误，因此应有助于面瘫患者的长期临床随访。为了考虑影响与健康侧比较的局限性，我们创建了一个健康面部运动数据集；因此，我们的方法可能适用于面部一侧或两侧运动受损的其他情况。患者特异性雷达图使临床医生能够快速读取和理解结果。
