Department of Surgery, Division of Otolaryngology-Head & Neck Surgery, Penn State Health: Milton S. Hershey Medical Center, Hershey, Pennsylvania.
Department of Otolaryngology-Head & Neck Surgery, Drexel University College of Medicine, Philadelphia, Pennsylvania.
J Voice. 2019 May;33(3):370-374. doi: 10.1016/j.jvoice.2017.12.009. Epub 2018 Feb 13.
This study aims to assess utility of pixel-valued movement software in detecting arytenoid dislocation preoperatively.
This is a retrospective analysis.
Twenty-seven patients diagnosed with unilateral arytenoid dislocation were included. Diagnosis of arytenoid dislocation was confirmed by lack of vocal fold paralysis on preoperative laryngeal electromyography and by intraoperative findings of cricoarytenoid dislocation. A region-tracking software algorithm developed by Zhuang et al was used to analyze 27 preoperative endoscopic videos of patients diagnosed with arytenoid dislocation. Vector analysis measuring cuneiform movement during inspiration was used as an indirect measure of arytenoid movement. Values were normalized using vocal fold length. Two raters blinded to diagnosis of arytenoid dislocation measured vocal fold length and cuneiform movement on both the dislocated and the nondislocated sides.
A Wilcoxon signed-rank test indicated that the mean pixel-valued cuneiform movement and standard deviation (SD) were greater for nondislocated (159.24, SD = 73.35) than for dislocated (92.49, SD = 72.11) arytenoids (Z = 3.29, P = 0.001). The interrater correlation coefficient was 0.87 for the dislocated side and 0.75 for the nondislocated side. The intrarater correlation coefficient was 0.87 for the dislocated side and 0.91 for the nondislocated side. The receiver operating characteristic curve revealed an area under the curve between 0.76 and 0.83 (95% confidence interval 0.63-0.90). Analysis by the first and second raters revealed misdiagnosis of laterality of arytenoid dislocation in four and six patients, respectively.
The software program developed by Zhuang et al provides a high-degree of precision, with good interrater and intrarater correlation coefficients. However, high rates of misdiagnosis of arytenoid dislocation and the laborious analysis process using this software program make it of limited utility as a clinical diagnostic tool in its present state.
本研究旨在评估像素值运动软件在术前检测杓状软骨脱位中的效用。
这是一项回顾性分析。
纳入 27 例单侧杓状软骨脱位患者。术前喉肌电图证实无声带麻痹，术中发现环杓关节脱位，诊断为杓状软骨脱位。使用 Zhuang 等人开发的区域跟踪软件算法分析 27 例术前内镜视频诊断为杓状软骨脱位的患者。测量吸气时楔形运动的向量分析作为杓状软骨运动的间接测量。使用声带长度对数值进行归一化。两名对杓状软骨脱位诊断不知情的评估者测量了脱位和未脱位侧的声带长度和楔形运动。
Wilcoxon 符号秩检验表明，未脱位（159.24，SD=73.35）的像素值楔形运动平均值和标准差（SD）大于脱位（92.49，SD=72.11）的杓状软骨（Z=3.29，P=0.001）。脱位侧的组内相关系数为 0.87，未脱位侧的组内相关系数为 0.75。脱位侧的组内相关系数为 0.87，未脱位侧的组内相关系数为 0.91。受试者工作特征曲线显示曲线下面积在 0.76 到 0.83 之间（95%置信区间为 0.63-0.90）。第一和第二位评估者的分析显示，分别有 4 名和 6 名患者误诊杓状软骨侧位。
Zhuang 等人开发的软件程序提供了高度的精度，具有良好的组内和组间相关性系数。然而，该软件程序在诊断杓状软骨脱位方面存在很高的误诊率，并且分析过程繁琐，使其在目前的状态下作为一种临床诊断工具的实用性有限。
