Quantitative assessment of videolaryngostroboscopic images in patients with glottic pathologies.

INTRODUCTION: Digital imaging techniques enable exploration of novel visualization modalities of the vocal folds during phonation and definition of parameters, facilitating more precise diagnosis of voice disorders.

AIM: Application of computer vision algorithms for analysis of videolaryngostroboscopic (VLS) images aimed at qualitative and quantitative description of phonatory vibrations.

MATERIALS AND METHODS: VLS examinations were conducted for 45 females, including 15 subjects with vocal nodules, 15 subjects with glottal incompetence, and 15 normophonic females. The recorded VLS images were preprocessed, the glottis area was segmented out, and the glottal cycles were identified. The glottovibrograms were built, and then the glottal area waveforms (GAW) were quantitatively described by computing the following parameters: open quotient (OQ), closing quotient (CQ), speed quotient (SQ), minimal relative glottal area (MRGA), and a new parameter termed closure difference index (CDI).

RESULTS: Profiles of the glottal widths assessed along the glottal length differentiated the study groups (P < 0.001). Moreover, it was shown that the OQ, CQ, CDI, and MRGA indices can be considered as viable parameters for quantifying kinematics of the vocal folds for normophonic subjects and patients with diagnosed vocal nodules and glottal incompetence (P < 0.001).

CONCLUSIONS: Computer image processing and analysis methods applied to videolaryngostroboscopic images allow for their quantitative assessment. Computation of the size-related and time-related parameters characterizing glottic pathologies is of interest for evidence-based voice diagnostics. Results of the performed ROC curve analysis suggest that the evaluated parameters can distinguish patients with voice disorders from normophonic subjects.