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Related Experiment Video

Updated: Apr 18, 2026

Author Spotlight: Advancing Awake Nasotracheal Intubation with Flexible Video Rhino-Laryngoscopes

Author Spotlight: Advancing Awake Nasotracheal Intubation with Flexible Video Rhino-Laryngoscopes

Published on: August 2, 2024

Real-time AI-assisted quality control during nasopharyngolaryngoscopy: a randomized controlled trial.

Yun Li¹, Bin Ye^2,3, Yuanyuan Li¹

¹Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.

NPJ Digital Medicine

|April 16, 2026

Summary

An AI quality control system, ENDOVISTA-ENT, significantly improved anatomical coverage during nasopharyngolaryngoscopy (NPL) examinations. This intelligent system enhances procedural completeness without increasing examination time, benefiting endoscopists of all experience levels.

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Area of Science:

Otolaryngology
Medical Imaging
Artificial Intelligence in Medicine

Background:

Nasopharyngolaryngoscopy (NPL) quality is operator-dependent, risking missed findings due to incomplete examinations.
Standardized NPL procedures are crucial for accurate diagnosis and patient care.

Purpose of the Study:

To develop and evaluate ENDOVISTA-ENT, an AI-powered system for real-time quality control during NPL.
To assess the impact of AI assistance on anatomical coverage and procedural completeness in NPL.

Main Methods:

Development of ENDOVISTA-ENT, an AI system trained on 3,630 NPL videos for real-time anatomical coverage monitoring.
Prospective, double-centre, randomized controlled trial involving 318 patients comparing AI-assisted vs. conventional NPL.

Main Results:

ENDOVISTA-ENT-assisted NPL achieved significantly higher mean anatomical coverage (93.08%) compared to conventional NPL (83.50%, P < 0.0001).
Improvements in coverage were observed across all endoscopist experience levels, notably for junior practitioners.
AI assistance did not significantly increase examination duration.

Conclusions:

Real-time AI-assisted quality control systems like ENDOVISTA-ENT can standardize NPL workflows.
The system enhances procedural completeness and anatomical site coverage during NPL examinations.
AI tools offer valuable support for improving endoscopist performance and diagnostic accuracy in ENT procedures.