Katsumi Sachiyo, Esaki Shinichi, Hattori Koosuke, Yamano Koji, Umezaki Taizo, Murakami Shingo
Department of Otolaryngology, Head and Neck Surgery, Nagoya City University Graduate School of Medical Sciences and Medical School, Kawasumi 1, Mizuho-cho, Mizuho-ku, Nagoya 467-0001, Japan.
Department of Otolaryngology, Head and Neck Surgery, Nagoya City University Graduate School of Medical Sciences and Medical School, Kawasumi 1, Mizuho-cho, Mizuho-ku, Nagoya 467-0001, Japan; Department of Virology, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.
Auris Nasus Larynx. 2015 Aug;42(4):275-83. doi: 10.1016/j.anl.2015.01.002. Epub 2015 Feb 2.
The prognosis for facial nerve palsy (FNP) depends on its severity. Currently, many clinicians use the Yanagihara, House-Brackmann, and/or Sunnybrook grading systems to assess FNP. Although these assessments are performed by experts, inter- and intra-observer disagreements have been demonstrated. The quantitative and objective analyses of the degree of FNP would be preferred to monitor functional changes and to plan and evaluate therapeutic interventions in patients with FNP. Numerous two-dimensional (2-D) assessments have been proposed, however, the limitations of 2-D assessment have been reported. The purpose of this study was to introduce a three-dimensional (3-D) image generation system for the analysis of facial nerve palsy (FNP) and to show the correlation between the severity of FNP assessed by this method and two conventional systems.
Five independent facial motions, resting, eyebrow raise, gentle eye closure, full smile with lips open and whistling were recorded with our system and the images were then analyzed using our software. The regional and gross facial symmetries were analyzed. The predicted scores were calculated and compared to the Yanagihara and H-B grading scores. We analyzed 15 normal volunteers and 42 patients with FNP.
The results showed that 3-D analysis could measure mouth movement in the anteroposterior direction, whereas two-dimensional analysis could not. The system results showed good correlation with the clinical results from the Yanagihara (r(2)=0.86) and House-Brackmann (r(2)=0.81) grading scales.
This objective method can produce consistent results that align with two conventional systems. Therefore, this method is ideally suited for use in a routine clinical setting.
面神经麻痹（FNP）的预后取决于其严重程度。目前，许多临床医生使用柳原、豪斯-布拉克曼和/或桑尼布鲁克分级系统来评估FNP。尽管这些评估由专家进行，但观察者间和观察者内的分歧已得到证实。对FNP程度进行定量和客观分析，将更有助于监测功能变化，并为FNP患者制定和评估治疗干预措施。已经提出了许多二维（2-D）评估方法，然而，二维评估的局限性也已被报道。本研究的目的是引入一种用于分析面神经麻痹（FNP）的三维（3-D）图像生成系统，并展示通过该方法评估的FNP严重程度与两种传统系统之间的相关性。
使用我们的系统记录五个独立的面部动作，即休息、抬眉、轻轻闭眼、嘴唇张开的全笑和吹口哨，然后使用我们的软件对图像进行分析。分析区域和整体面部对称性。计算预测分数，并与柳原和H-B分级分数进行比较。我们分析了15名正常志愿者和42名FNP患者。
结果表明，三维分析可以测量嘴巴在前后方向的运动，而二维分析则无法做到。系统结果与柳原（r(2)=0.86）和豪斯-布拉克曼（r(2)=0.81）分级量表的临床结果显示出良好的相关性。
这种客观方法可以产生与两种传统系统一致的结果。因此，该方法非常适合在常规临床环境中使用。
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