Drug-induced sleep endoscopy (DISE) is a diagnostic technique for 3D dynamic anatomical visualisation of upper airway obstruction during sedated sleep. There is a lack of standardised procedure and objective measurement associated with information capture, information management, evaluation of DISE findings, treatment planning, and treatment outcomes. The objective of this study is to present clinical feasibility results using a DISE DATA FUSION system for capturing, merging, displaying and storing anatomical data from an endoscopic imaging system and cardiorespiratory data from an anaesthesiological monitoring system simultaneously in real-time during DISE. This prospective cohort study included 20 patients presenting with symptoms of sleep related breathing disorders undergoing drug-induced sedation endoscopy and had volunteered for DISE DATA FUSION system to be used during their DISE assessment. The DISE DATA FUSION system was used to capture, merge, display, and store anatomical changes from an endoscopic imaging system and cardiorespiratory changes from an anaesthesiological monitoring system simultaneously in real time during drug-induced sedation endoscopy assessment. In all 20 patients, anatomical obstructions at different levels of the pharyngeal lumen (soft palate, velum, tonsils, oropharynx lateral wall, base of tongue, and epiglottis) with a different obstruction configuration and severity were captured simultaneously in real time with its associated cardiorespiratory parameters. Furthermore, a composite video consisting of an anatomical image, blood oxygen level, pulse rate, blood pressure, and timestamp was created for every obstructive event. Our system provides a useful and better way of capturing, merging, visualising, and storing anatomical data/physiological data simultaneously during DISE in real time. Furthermore, it enhances the understanding of the impact of the anatomical severity due to the simultaneous display of the cardiovascular parameters at that specific time of anatomical obstruction for optimising surgical decision based on DISE.
Keywords: DISE; Data fusion; Data visualisation; Drug-induced sleep endoscopy; Medical device; Medical innovation; Obstructive sleep apnea; Upper airway obstruction.