Deep Learning-based sbORN Diagnostic Model
Development of Deep-Learning-Based Multimodal Post Radiotherapy Skull-Base Osteonecrosis and Recurrence of Nasopharyngeal Carcinoma Differential Diagnostic Model
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
312 participants
Jul 1, 2024
OBSERVATIONAL
Conditions
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
Plain Language Summary
Simplified for easier understanding
This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.
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Interventions
No intervention is scheduled for this observational study.
Locations(1)
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NCT06463392