Validation of End-to-End Difficult Airway Pathway Planning Algorithm (EAP-LC)

Patients with laryngeal cancer often present with varying degrees of airway narrowing or anatomical distortion, making airway management particularly challenging. Awake flexible bronchoscopic intubation is a widely accepted and important strategy to ensure airway safety in this population. Currently, the selection of the intubation pathway mainly relies on visual assessment of preoperative computed tomography (CT) images and the clinical experience of anesthesiologists, lacking objective and quantifiable tools for airway pathway planning.

Our research group has developed an end-to-end airway pathway planning algorithm for laryngeal cancer patients (EAP-LC), which can automatically generate predicted nasal or oral intubation pathways based on preoperative pharyngeal and upper airway CT images. Preliminary simulation analyses based on retrospective CT data demonstrated that the algorithm is capable of identifying airway narrowing and generating trajectories that are close to clinically feasible intubation paths (preliminary data, under review). However, to date, no study has directly compared the algorithm-predicted pathways with actual intubation trajectories obtained during awake flexible bronchoscopic intubation. Therefore, a prospective clinical validation study is required to evaluate the spatial consistency and clinical feasibility of the EAP-LC algorithm.

Without altering routine clinical treatment or anesthetic management, this study aims to evaluate the clinical accuracy, safety, and feasibility of the EAP-LC algorithm by comparing the intubation pathways predicted from preoperative CT images with the real-world trajectories recorded during awake flexible bronchoscopic intubation. The results of this study are expected to provide a more precise and objective decision-support tool for airway management in patients with laryngeal cancer.