ORIGINAL RESEARCH article

Front. Oncol.

Sec. Head and Neck Cancer

Volume 15 - 2025 | doi: 10.3389/fonc.2025.1582011

This article is part of the Research TopicAdvancing Cancer Imaging Technologies: Bridging the Gap from Research to Clinical Practice Volume IIView all 7 articles

Comparison of Clinical Nasal Endoscopy, Optical Biopsy, and Artificial Intelligence in Early Diagnosis and Treatment Planning in Laryngeal Cancer: A Prospective Observational Study

Provisionally accepted
Ruifang  HuRuifang HuXianping  LiuXianping LiuYong  ZhangYong ZhangDongguang  QinDongguang Qin*
  • Shanxi Provincial Cancer Hospital, Taiyuan, China

The final, formatted version of the article will be published soon.

Laryngeal cancer accounts for approximately 2% of all cancers globally and is considered one of the most aggressive types of head and neck cancer. Prompt diagnosis is crucial to improving survival and function. Direct laryngoscopy and imaging modalities are conventional diagnostic methods. However, laryngeal cancer diagnosis can be delayed, and early subtle mucosal changes can be missed. Flexible nasal endoscopy, particularly when integrated with artificial intelligence and optical biopsy methods, has shown promise in the early detection of laryngeal cancer. Yet, there is little literature on the combined experiences of these modalities.This prospective observational study involved 142 patients with suspected laryngeal cancer. All included patients underwent flexible nasal endoscopy with topical anesthesia. The patients were assessed using one or more optical biopsy techniques (Narrow Band Imaging [NBI], SPIES, or ISCAN), depending on available equipment and whether the lesions were visible. AI algorithms were retrospectively applied to endoscopic images to categorize lesions as cancerous or non-cancerous depending on vascular, textural, and color characteristics. The AI model was trained on a different pre-annotated dataset, and the images from the study cohort were not used to train the AI model -this methodologically ensures no bias has been introduced into the evaluation. Histopathology was used as the reference standard. Diagnostic performance was calculated using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).The study revealed superior sensitivity (95.2%) and specificity (96.5%) with AIenhanced endoscopy compared to conventional endoscopy (89.6%, 92.4%), respectively. Optical biopsy methods provided better visualization of lesions; however, not all patients had all three modalities in a single procedure. Diagnostic delay was shortened with a median time of 15 to 7 days (<0.001). Inter-rater agreement was strong overall (κ=0.84), with hoarseness having the most reliability, most likely due to better exposure of the glottis.AI and selectively applied optical biopsy methods improved diagnostic accuracy in nasal endoscopy and reduced time delays for the early detection and management of laryngeal cancer. Further study in multicenters will allow for further validation of this work.

Keywords: Laryngeal cancer, Nasal endoscopy, artificial intelligence, Diagnostic accuracy, Early detection

Received: 23 Feb 2025; Accepted: 25 Apr 2025.

Copyright: © 2025 Hu, Liu, Zhang and Qin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dongguang Qin, Shanxi Provincial Cancer Hospital, Taiyuan, China

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.