AI System for Anatomic Recognition & Lesion Detection in Nasopharyngolaryngoscopy: A Prospective Study

Shanghai Jiao Tong University

Status: Enrolling

Conditions: Laryngeal Disease; Nasopharyngeal Neoplasms

Treatments: Other: Diagnostic

Study type: Observational

Funder types: Other

Identifiers

NCT07326358

2025-811

Details and patient eligibility

About

An artificial intelligence-assisted system is trained and validated by collecting nasopharyngolaryngoscopy images from patients.

Full 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.

Enrollment: 500 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

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.

Trial design

500 participants in 2 patient groups

Model training and validation cohorts

Description:

A deep learning model is trained using the training dataset and validated with the internal validation set.

Treatment:

Other: Diagnostic

Other: Diagnostic

Prospective test cohort

Description:

Patients are prospectively enrolled, nasopharyngolaryngoscopy examination videos are collected, and the video data are processed to form a prospective test dataset, which is then used for testing.

Treatment:

Other: Diagnostic

Other: Diagnostic