Multivariate Analysis of Vocal Fold Vibrations on Various Voice Disorders Using High-Speed Digital Imaging

• Published in: Applied sciences Vol. 11; no. 14; p. 6284
• Main Authors: Yamauchi, Akihito, Imagawa, Hiroshi, Yokonishi, Hisayuki, Sakakibara, Ken-Ichi, Tayama, Niro
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 07.07.2021
• Subjects: Clinical medicine; Digital imaging; digital kymography; high-speed digital imaging; Hypotheses; laryngotopography; Methods; Multivariate analysis; Patients; Quantitative analysis; Surgeons; vocal fold vibration; voice disorder; Japan
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app11146284

Although many quantitative parameters have been devised to describe abnormalities in vocal fold vibration, little is known about the priority of these parameters. We conducted a prospective study using high-speed digital imaging to elucidate disease-specific key parameters (KPs) to characterize the vocal fold vibrations of individual voice disorders. From 304 patients with various voice disorders and 46 normal speakers, high-speed digital imaging of a sustained phonation at a comfortable pitch and loudness was recorded and parameters from visual-perceptual rating, laryngotopography, digital kymography, and glottal area waveform were calculated. Multivariate analysis was then applied to these parameters to elucidate the KPs to explain each voice disorder in comparison to normal subjects. Four key parameters were statistically significant for all laryngeal diseases. However, the coefficient of determination (R2) was very low (0.29). Vocal fold paralysis (8 KPs, R2 = 0.76), sulcus vocalis (4 KPs, R2 = 0.74), vocal fold scarring (1 KP, R2 = 0.68), vocal fold atrophy (6 KPs, R2 = 0.53), and laryngeal cancer (1 KP, R2 = 0.52) showed moderate-to-high R2 values. The results identified different KPs for each voice disorder; thus, disease-specific analysis is a reasonable approach.