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.
Age > 18 years
Injury originating from the upper aero-digestive tract
Recording of the video-endoscopic examination
Patient known to undergo a biopsy of the lesion or clinical follow-up for lesion with known biopsy (e.g. laryngeal papillomatosis) or suffering from Reinke's edema (in this pathology, in fact, biopsy is not necessary since the diagnosis is clinical)
Submucosal lesion
Patients with previous operations on the upper aero-digestive tract
Patients with previous radiotherapy of the head and neck district
Poor compliance on endoscopic examination
Istituto Italiano di Tecnologia
Lead sponsor
Hospital Clinic of Barcelona
Collaborator
CRO "Centro Clinical Trials" IRCCS Ospedale Policlinico San Martino
Collaborator
Universitaire Ziekenhuizen KU Leuven
Collaborator
Università degli Studi 'G. d'Annunzio' Chieti e Pescara
Collaborator
Universita degli Studi di Genova
Collaborator
Scuola Superiore di Studi Universitari e di Perfezionamento Sant'Anna
Collaborator