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A Deep Learning Model for Diagnosing Lymph Node Metastasis in Nasopharyngeal Carcinoma(NPC)

Recruitingn/aAges any - anyAllSun Yat-sen University
NCT06829147 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

(I) AI Model for Diagnosing Lymph Node Metastasis We developed an AI model to help diagnose whether a single lymph node in nasopharyngeal cancer has spread. The model uses MRI images of the lymph node and the area around it. It includes: 1.Automatically identifying the lymph nodes and the primary tumor. 2.Analyzing MRI images of the lymph node and surrounding area. 3.Using MRI scans before and after chemotherapy to track changes in the lymph node. (II) AI Model for Predicting Lymph Node Metastasis We created an AI model that predicts whether a lymph node in a specific area has cancer. This model uses a combination of the primary tumor's pathology and MRI images of both the tumor and lymph node. It also tracks changes in the lymph node over time. The model includes: 1.Analyzing the tumor's pathology to identify specific lymphatic structures. 2.Using MRI scans to predict the likelihood of

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📋 Eligibility rules (as published)
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
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What it tests

  • Not listed
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Where

1 site
Department of Radiation Oncology, Sun Yat-sen University Cancer Center
Guangzhou, China
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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