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RECRUITING
NCT06463392

Deep Learning-based sbORN Diagnostic Model

Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

View on ClinicalTrials.gov

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.

Official title: Development of Deep-Learning-Based Multimodal Post Radiotherapy Skull-Base Osteonecrosis and Recurrence of Nasopharyngeal Carcinoma Differential Diagnostic Model

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

312

Start Date

2024-07-01

Completion Date

2030-12-31

Last Updated

2024-10-01

Healthy Volunteers

No

Interventions

OTHER

No Intervention: Observational Cohort

No intervention is scheduled for this observational study.

Locations (1)

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

Guangzhou, Guangdong, China