Vocal Fold Polyp

This is a prospective observational clinical study designed to evaluate the performance of artificial intelligence (AI) algorithms applied to upper aerodigestive tract (UADT) video-endoscopy. The study assesses three main tasks: lesion detection (localization), classification (benign vs malignant), and segmentation of tumor margins. AI algorithms will be applied to endoscopic video data acquired during routine clinical practice without influencing clinical decision-making. The system will process images in real time and store data for subsequent analysis. AI outputs will be compared with physician assessment and reference standard histopathology to evaluate diagnostic performance.

Vocal hyperfunction (VH) is the most commonly treated class of voice disorders by speech-language pathologists and voice therapy is the primary curative treatment. Patients and clinicians report that generalizing improved voicing into daily life is the most significant barrier to successful therapy. We will test if extending biofeedback into the patient's daily life using ambulatory voice monitoring will significantly improve generalization during therapy and if individual patient factors, like how easily they can modify their voice and engagement during therapy, moderate the effects of the biofeedback.