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Development and Validation of a Deep Learning Model to Predict Distant Metastases in Nasopharyngeal Carcinoma Using Whole Slide Imaging and MRI

NCT06831357 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 500

Last updated 2025-02-25

No results posted yet for this study

Summary

An AI model was developed to predict the likelihood of distant metastasis in patients with nasopharyngeal cancer based on pathology slides and MRI scans of the primary tumor. The model was validated using data from multiple centers. It was then applied to patients with advanced stages who were recommended to undergo PET/CT scans based on the NCCN or CSCO guidelines. This AI model can accurately screen patients with high risk of distant metastasis at the time of initial diagnosis to receive PET/CT, avoid excessive examination of patients with low risk of distant metastasis, save medical resources and reduce the economic burden on patients.

Conditions

  • Nasopharyngeal Cancinoma (NPC)
  • Distant Metastasis

Sponsors & Collaborators

  • First Affiliated Hospital, Sun Yat-Sen University

    collaborator OTHER

  • Fifth Affiliated Hospital, Sun Yat-Sen University

    collaborator OTHER

  • Affiliated Cancer Hospital & Institute of Guangzhou Medical University

    collaborator OTHER

  • The Affiliated Panyu Center Hospital of Guangzhou Medical University

    collaborator UNKNOWN

  • Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

    collaborator OTHER

  • Qingyuan People's Hospital

    collaborator OTHER

  • Sun Yat-sen University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-02-15
Primary Completion
2026-12-31
Completion
2026-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06831357 on ClinicalTrials.gov