AI System for Anatomic Recognition & Lesion Detection in Nasopharyngolaryngoscopy: A Prospective Study
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: Diagnostic, Diagnostic.
- Who it may be relevant to
- Registry conditions: Nasopharyngeal Neoplasms, Laryngeal Disease. 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 →
Official title
Development and Validation of an Artificial Intelligence System for Anatomic Site Recognition and Lesion Detection Based on Electronic Nasopharyngolaryngoscopic Images: A Prospective Multicenter Study
Overview
An artificial intelligence-assisted system is trained and validated by collecting nasopharyngolaryngoscopy images from patients.
Detailed description
To address the clinical pain points of traditional nasopharyngolaryngoscopy, such as incomplete visualization, inaccurate identification, and unclear imaging, this study will retrospectively collect nasopharyngolaryngoscopy images and baseline information (including gender and age) of patients who underwent nasopharyngolaryngoscopy at participating centers for model training and validation. Deep learning algorithms will be applied to construct the model. The final clinical performance evaluation of the model will be conducted using an independent, prospectively collected test cohort.
Interventions
- Other Diagnostic
The deep learning model is trained using the training dataset and tested with the internal validation set. - Other Diagnostic
The prospective dataset is used for the comparative testing of the model and physicians.
Primary outcome measures
- performance of lesion detection [Time frame: Within 3 months after the completion of prospective data collection]
- performance of anatomic site recognition [Time frame: Within 3 months after the completion of prospective data collection]
Secondary outcome measures (1)
- Comparison of diagnostic performance between the model and physicians [Time frame: Within 3 months after the completion of prospective data collection]
Eligibility criteria
Inclusion criteria
- Age ≥ 18 years;
- Underwent standard electronic nasopharyngolaryngoscopy;
- Patients who underwent biopsy sampling have a clear pathological diagnosis;
- Signed a written informed consent form.
Exclusion criteria
- Image quality is substandard with severe motion artifacts;
- Lesion images are unclear and incomplete.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Other
Study locations
China · 1 center
- Ruijin Hospital, Shanghai Jiao Tong University School of Medicine — Shanghai
Identifiers
NCT: NCT07326358 · 2025-811