Advances in Ultrasound Measurement of Upper Airway Parameters to Predict Difficult Airways in Patients with OSAS

Obstructive sleep apnea syndrome (OSAS) is a common disease characterized by repeated upper airway collapse during sleep. Obstruction, collapse, and stenosis are due to abnormalities of the upper airway anatomy is an important factor in the pathogenesis of OSAS, and the characteristics of a narrowed or obstructed upper airway anatomy increase the difficulty of tracheal intubation, and the risk of a difficult airway at the time of anaesthesia induction is significantly higher. Traditional bedside predictors of difficult laryngoscopy include the modified mallampati test (MMT), thyromental distance (TMD), mouth opening (MO), neck mobility, and upper and lower lip occlusion test. It has been pointed out that traditional assessment methods are based on observation and measurement of the patient’s body surface, which are incomplete and inadequate, and that traditional assessment methods require the patient to be awake and to cooperate with the physician to complete the assessment. Therefore, there is an urgent need for more reliable, objective, and non-invasive preoperative assessment methods. Ultrasound has the advantages of real-time observation of the upper respiratory tract, easy operation, low cost, and no exposure to ionizing radiation. In recent years, it has gradually been applied to preoperative airway assessment, and ultrasound is used to measure the internal structure of the patient’s airway and related organ tissues. The measured parameters include the thickness of the anterior neck soft tissue at the levels of the epiglottis, hyoid bone, vocal cords, thyrohyoid membrane, and thyroid isthmus plane, as well as the volume of the tongue, the thickness of the tongue, and the hyoid bone distance ratio, etc. Recent research efforts have focused on determining validated critical values for these ultrasound parameters and developing standardized scanning protocols. Additionally, combining multiple ultrasound parameters or integrating them with traditional predictive indicators has shown enhanced predictive performance.