AI model for diagnosing lymph node metastasis in nasopharyngeal carcinoma
Official title: Development and Validation of a Deep Learning Model for Diagnosing Lymph Node Metastasis in Nasopharyngeal Carcinoma Using Histologic Whole Slide Images and Time-dependent Magnetic Resonance Images
Run by Sun Yat-sen University · NCT06829147 · Data updated 2026-11-12
This study is testing a new AI tool that helps doctors diagnose if nasopharyngeal carcinoma has spread to lymph nodes by looking at MRI images before and after chemotherapy.
Quick facts
| Study type | Observational |
|---|---|
| Sex | All |
| Enrollment | 500 (estimated) |
| Sponsor | Sun Yat-sen University Academic / other |
| Drugs / interventions | chemotherapy, radiation |
| Locations | 1 site (Guangzhou, Guangdong) |
| Status | Recruiting |
| Started | November 19, 2024 |
| Main results expected | September 1, 2026 |
| Study ends | September 1, 2026 |
| Registry record updated | February 17, 2025 |
| Trial ID | NCT06829147 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates for this study are patients with pathologically confirmed nasopharyngeal carcinoma who have undergone initial MRI and PET/CT scans.
✕Probably not a fit
Patients who have received cervical lymph node radiotherapy or have other concurrent malignant tumors may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This study develops an artificial intelligence model to assist in diagnosing lymph node metastasis in patients with nasopharyngeal carcinoma. The model utilizes MRI images of the lymph nodes and surrounding areas, analyzing features before and after chemotherapy to track changes. It aims to automatically identify lymph nodes and predict the likelihood of metastasis based on both MRI and pathological data. The approach combines advanced imaging techniques with AI to enhance diagnostic accuracy.
Why it matters
Potential benefit: If successful, this AI model could significantly improve the accuracy of diagnosing lymph node metastasis in nasopharyngeal carcinoma, leading to better treatment decisions.
How similar studies have gone: Other studies utilizing AI for diagnostic purposes in oncology have shown promising results, suggesting potential success for this approach.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. The primary lesion was pathologically confirmed as nasopharyngeal carcinoma (WHO classification is I, II and III); 2. MRI scan was performed at the initial diagnosis (before anti-tumor treatment), and transverse and coronal MRI images before treatment were available, including T1-weighted, T2-weighted and T1-enhanced scanning sequences. 3. PET/CT scan was performed at the initial diagnosis (before anti-tumor treatment) 4. When MRI and PET/CT were inconsistent in judging the benign or malignant nature of lymph nodes, the patient agreed to undergo cervical lymph node puncture and pathological examination. Exclusion Criteria: 1. The patient has undergone cervical lymph node radiotherapy for any reason 2. Combined with other malignant tumors
Where it's running
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Department of Radiation Oncology, Sun Yat-sen University Cancer Center
Guangzhou, Guangdong, China Recruiting
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.