To Develop and Validate a Nasoendoscopic Intelligent Diagnostic System for Nasopharyngeal Carcinoma
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: rigid nasal endoscopes.
- Who it may be relevant to
- Registry conditions: Otolaryngological Disease, Artificial Intelligence. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Overview
Nasopharyngeal carcinoma (NPC) occurs at a high frequency in southern China, northern Africa, and Alaska, with a reported incidence of 30 cases per 100 000 in Guangdong Province. Endoscopic examination and biopsy are the main methods used for detection and diagnosis of NPC. Early NPC patients achieve favourable prognoses after concurrent radiotherapy and chemotherapy in compassion with advanced NPC patients. Here, the investigators focused on the utility of artificial intelligence to detect early NPC, which based on white light imaging (WLI) and Narrow-band imaging (NBI) nasoendoscopic examination. Having access to this unique population provides an unprecedented opportunity to investigate the effect of intelligent system on diverse nasopharyngeal lesions detection and develop a novel Computer-Aided Diagnosis System.
Interventions
- Diagnostic test rigid nasal endoscopes
The endoscope is introduced through the nasal passage to observe, in sequence, the posterior nostril, superior and posterior walls of the nasopharynx, torus tubarius, pharyngeal opening of the auditory tube, and Rosenmu¨ller recess. The imaging light mode is set to conventional WLI and subsequently switch to NBI during the procedure, and representative images are collected and preserve for further analysis. All lesions, detected by either WLI or NBI, are biopsied.
Primary outcome measures
- Pathological diagnosis [Time frame: baseline]
Secondary outcome measures (1)
- Lesion range [Time frame: baseline]
Eligibility criteria
Inclusion criteria
- Older than 18 years of age
Exclusion criteria
- Refuse to sign the informed consent statement
- Patients who have contraindications, e.g. coagulation dysfunction, drug allergy.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Study design
- Observational model
- Other
Study locations
China · 3 centers
- First Affiliated Hospital of Sun Yat-sen University — Guangzhou
- Sun Yat-Sen University Cancer Center — Guangzhou
- Kiang Wu Hospital — Macao
Publications
- He R, Jie P, Hou W, Long Y, Zhou G, Wu S, Liu W, Lei W, Wen W, Wen Y. Real-time artificial intelligence-assisted detection and segmentation of nasopharyngeal carcinoma using multimodal endoscopic data: a multi-center, prospective study. EClinicalMedicine. 2025 Feb 15;81:103120. doi: 10.1016/j.eclinm.2025.103120. eCollection 2025 Mar. PMID 40026832
Identifiers
NCT: NCT04547673 · ZSYY2020