Videokymography in Voice Disorders: What to Look For?

TLDR

Videokymography is a novel, convenient method for visualizing laryngeal behavior, but systematic research mapping its relevant features is scarce. This study aimed to specify and systematically categorize vocal fold vibratory patterns in voice disorders using videokymographic imaging. Using a cross‑sectional descriptive design, 45 subjects provided 100 videokymographic images extracted from a database of over 7,000 examinations, which were visually analyzed to identify prominent vibratory features. The analysis yielded ten feature categories—including traditional mucosal waves and new, previously obscured irregularities—whose variation indicates distinct behavioral origins of voice disorders and offers a basis for objective documentation and monitoring in clinical practice.

Abstract

Objectives: Kymographic imaging through videokymography has been recognized as a convenient, novel way to display laryngeal behavior, yet little systematic research has been done to map the relevant features displayed in such images. Here we have aimed at specification of these features to enable systematic visual characterization and categorization of vocal fold vibratory patterns in voice disorders. Methods: A cross-sectional, descriptive design was used. We selected 45 subjects and extracted 100 videokymographic images from the archive of more than 7,000 videokymographic examinations of subjects with a wide range of voice disorders. The images showed a large variety of vocal fold vibratory behaviors during sustained phonations. We visually identified the prominent features that distinguished the vibration patterns across the images. Results: We divided the findings into 10 feature categories. They included refined traditional features (eg, mucosal waves), as well as additional features that are obscured in strobolaryngoscopy (eg, different types of irregularities, left-right frequency differences, shapes of lateral and medial peaks, cycle aberrations). Conclusions: The variations in the identified features reveal different behavioral origins of voice disorders. The findings open new possibilities for objective documentation and for monitoring vocal fold behavior in clinical practice through kymographic imaging.