← Back to Clinical Trials
Recruiting NCT06463392

NCT06463392 Deep Learning-based sbORN Diagnostic Model

◆ AI Clinical Summary
Plain-language summary for patients
Clinical Trial Summary
NCT ID NCT06463392
Status Recruiting
Phase
Sponsor Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Condition Nasopharyngeal Carcinoma
Study Type OBSERVATIONAL
Enrollment 312 participants
Start Date 2024-07-01
Primary Completion 2029-12-31

Eligibility & Interventions

Sex All sexes
Min Age 18 Years
Max Age N/A
Study Type OBSERVATIONAL
Interventions
No Intervention: Observational Cohort

Eligibility Fast-Check

Enter your details for a quick preliminary check. This does not replace medical advice.

What to Expect as a Participant

This is an observational study. You will not receive an experimental treatment; researchers will collect data based on your existing condition or standard treatment.

This trial targets 312 participants in total. It began in 2024-07-01 with a primary completion date of 2029-12-31.

⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.

Brief Summary

Skull-base osteonecrosis (sbORN) is a severe long-term complication of nasopharyngeal carcinoma (NPC) post radiotherapy, which significantly diminish the quality of life, increase the risk of internal carotid artery rupture, and is frequently misdiagnosed as NPC recurrence. Novel diagnostic tools are therefore clinically significant. In this study, the investigators seek to ask if a deep-learning-based model shows a significantly higher sensitivity than radiologists. With a cross-sectional design, the investigators aim to recruit 312 participants in Sun Yat-sen Memorial Hospital, Guangzhou, China that meet the eligibility criteria.

Eligibility Criteria

Inclusion Criteria: * Equal to or older than 18 years old. * A history of histologically confirmed nonkeratinizing undifferentiated nasopharyngeal carcinoma. * A history of radical radiotherapy at nasopharynx. * Complete remission six months post radical radiotherapy according to RECIST 1.1. * No evidence of distant metastasis upon recruitment. * Diagnosis of sbORN given by senior radiologist with 2-4 Likert scores. * Consent to biopsy awake or under general anesthesia. * Consent to perform blood tests, EBV DNA, EBV IgAs, and MRI inspection of nasopharynx and neck. * With a written consent. Exclusion Criteria: * MRI artifacts or other factors that interfere radiological diagnosis and region of interest contouring. * Suspected lesion is not confined to nasopharynx and skull-base.

Contact & Investigator

Central Contact

Xiang-Wei Kong, Ph.D.

✉ kongxw8@mail.sysu.edu.cn

📞 0086-020-34071439

Frequently Asked Questions

Who can join the NCT06463392 clinical trial?

This trial is open to participants of all sexes, aged 18 Years or older, studying Nasopharyngeal Carcinoma. Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.

Is NCT06463392 currently recruiting?

Yes, NCT06463392 is actively recruiting participants. Contact the research team at kongxw8@mail.sysu.edu.cn for enrollment information.

Where is the NCT06463392 trial being conducted?

This trial is being conducted at Guangzhou, China.

Who is sponsoring the NCT06463392 clinical trial?

NCT06463392 is sponsored by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University. The trial plans to enroll 312 participants.

Related Trials

ClinicalMetric — Independent clinical trial intelligence platform. Not affiliated with NIH, ClinicalTrials.gov, the U.S. FDA, or any pharmaceutical company, hospital, or clinical research organization. Trial data is sourced from ClinicalTrials.gov for informational purposes only and does not constitute medical advice. Do not make any treatment, enrollment, or health decisions based solely on information found here — always consult a qualified healthcare professional. Full Disclaimer  ·  Last Reviewed: April 2026  ·  Data Methodology