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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

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06463392
Enrollment
312
Registered
2024-06-17
Start date
2024-07-01
Completion date
2030-12-31
Last updated
2024-10-01

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Herpesvirus 4, Human, Nasopharyngeal Carcinoma

Keywords

Nasopharyngeal Carcinoma, Skull-base Osteonecrosis, Radiotherapy, Epstein-Barr Virus

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.

Interventions

OTHERNo Intervention: Observational Cohort

No intervention is scheduled for this observational study.

Sponsors

Sun Yat-sen University
CollaboratorOTHER
Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
CollaboratorUNKNOWN
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Lead SponsorOTHER

Study design

Observational model
CASE_CONTROL
Time perspective
CROSS_SECTIONAL

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

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.

Design outcomes

Primary

MeasureTime frame
Area under curve of the differential diagnosis of sbORN and NPC recurrence delivered by the deep-learning-based multimodal model.Baseline
Area under curve of the differential diagnosis of sbORN and NPC recurrence delivered by the radiologists.Baseline

Secondary

MeasureTime frame
Average surface distance of the MRI contouring between the deep-learning-based multimodal model and the radiologists.Baseline
Sensitivity of the differential diagnosis of sbORN and NPC recurrence delivered by the deep-learning-based multimodal model.Baseline
Specificity of the differential diagnosis of sbORN and NPC recurrence delivered by the deep-learning-based multimodal model.Baseline
F1 score of the differential diagnosis of sbORN and NPC recurrence delivered by the deep-learning-based multimodal model.Baseline
Positive predictive value of the differential diagnosis of sbORN and NPC recurrence delivered by the deep-learning-based multimodal model.Baseline
Negative predictive value of the differential diagnosis of sbORN and NPC recurrence delivered by the deep-learning-based multimodal model.Baseline
Sensitivity of the differential diagnosis of sbORN and NPC recurrence delivered by the radiologists.Baseline
Specificity of the differential diagnosis of sbORN and NPC recurrence delivered by the radiologists.Baseline
F1 score of the differential diagnosis of sbORN and NPC recurrence delivered by the radiologists.Baseline
Positive predictive value of the differential diagnosis of sbORN and NPC recurrence delivered by the radiologists.Baseline
Negative predictive value of the differential diagnosis of sbORN and NPC recurrence delivered by the radiologists.Baseline
Dice similarity coefficient of the MRI contouring between the deep-learning-based multimodal model and the radiologists.Baseline

Other

MeasureTime frame
The concentration of albumin in the peripheral blood.Baseline
The number of red blood cells in the peripheral blood.Baseline
The history of diabetes mellitus.Baseline
The history of hypertension.Baseline
The number of white blood cells in the peripheral blood.Baseline
The number of neutrophils in the peripheral blood.Baseline
The number of basophils in the peripheral blood.Baseline
The number of eosinophils in the peripheral blood.Baseline
The copy number of Epstein-Barr Virus (EBV) DNA.Baseline
The titer of EBV VCA IgA.Baseline
The titer of EBV EBNA1 IgA.Baseline
The titer of EBV EA IgA.Baseline
The concentration of total protein in the peripheral blood.Baseline

Countries

China

Contacts

Primary ContactXiang-Wei Kong, Ph.D.
kongxw8@mail.sysu.edu.cn0086-020-34071439

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026