Department of Otorhinolaryngology, Head and Neck Surgery, Erlangen University Hospital, Erlangen, Germany.
Laryngoscope. 2013 Jul;123(7):1686-93. doi: 10.1002/lary.23783. Epub 2013 May 6.
OBJECTIVES/HYPOTHESIS: Quantitative analysis of endoscopic high-speed video recordings of vocal fold vibrations has been growing in importance in recent years. The videos have mainly been analyzed using subjective evaluation, but this is examiner dependent, and the results show inadequate interobserver agreement. The aims of this study were therefore to identify appropriate objective parameters for analyzing high-speed recordings to differentiate healthy voice production from organic disorders.
A total of 152 females were examined, divided into 77 healthy and 75 with four different pathological conditions: laryngeal epithelial thickening, Reinke edema, vocal fold polyps, and vocal fold cysts. Vocal fold vibrations were recorded with a high-speed camera (4,000 Hz, 256 × 256 pixels) during sustained phonation. Parameters computed from the glottal area waveform (GAW) and from phonovibrogram (PVG) were analyzed. Multiparametric linear discriminant analysis was performed to classify pathological conditions versus the healthy group.
Twenty of 44 parameters were identified that are capable of distinguishing between the individual types of pathology. PVG parameters showed better performance than GAW parameters. Parameters representing vibrational periodicity via standard deviation showed better performance than absolute parameters. In addition, linear discriminant analysis achieved reliable differentiation between healthy and pathological vocal fold vibrations: 72% for the five-class problem (all groups separately) and 88% for the two-class problem (healthy vs. all pathologies taken as one class).
The study succeeded in defining objective parameters for analyzing endoscopic high-speed videos and suggesting first parameters for differentiation between healthy dynamics and dynamics of organic pathologies.
目的/假设:近年来,对声带振动的内镜高速视频记录进行定量分析变得越来越重要。这些视频主要通过主观评估进行分析,但这种方法依赖于评估者,并且结果显示观察者间的一致性不足。因此,本研究的目的是确定分析高速记录的适当客观参数,以区分健康的发声和器质性障碍。
共检查了 152 名女性,分为 77 名健康者和 75 名患有四种不同病理状况的患者:声带上皮增厚、任克水肿、声带息肉和声带囊肿。在持续发音期间,使用高速摄像机(4000 Hz,256×256 像素)记录声带振动。从声门区波形(GAW)和嗓音图(PVG)中计算出参数。进行多参数线性判别分析,以对病理状况与健康组进行分类。
从 44 个参数中确定了 20 个参数,这些参数能够区分不同类型的病理。PVG 参数的表现优于 GAW 参数。通过标准差表示振动周期性的参数比绝对值参数表现更好。此外,线性判别分析能够可靠地区分健康和病理性声带振动:5 类问题(所有组分别)的区分率为 72%,2 类问题(健康与所有病理作为一类)的区分率为 88%。
该研究成功定义了用于分析内镜高速视频的客观参数,并提出了用于区分健康动力学和器质性病变动力学的初步参数。