Deep Learning-based sbORN Diagnostic Model

Recruiting now

Conditions studied: Nasopharyngeal Carcinoma, Herpesvirus 4, Human

In brief

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.

Key facts

Study ID
NCT06463392
Run by
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
People needed
312
Starts
2024-07-01
Expected to finish
2030-12-31
Last updated by the study team
2024-10-01

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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