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Prospective validation of an artificial intelligence fusion model for diagnosing the status of cervical lymph nodes in oral tumors based on enhanced CT

Construction and validation of an artificial intelligence fusion model for diagnosing the status of cervical lymph nodes in oral tumors based on enhanced CT

Status
Active, not recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500113216
Enrollment
Unknown
Registered
2025-11-26
Start date
2025-12-01
Completion date
Unknown
Last updated
2025-12-01

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

Conditions

Oral squamous cell carcinoma

Interventions

Gold Standard:The pathological results of paraffin sections from the post-operative specimens (including the division of lymph nodes, their quantity, and the presence of metastasis) were used as the g
Index test:artificial intelligence fusion model for diagnosing the status of cervical lymph nodes in oral tumors based on enhanced CT

Sponsors

Peking University Hospital of Stomatology
Lead Sponsor

Eligibility

Sex/Gender
All
Age
10 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1. Primary oral cancer. Preoperative diagnosis revealed suspicious metastatic lymph nodes, and a neck lymph node dissection surgery was performed at our hospital. 2. The postoperative pathological diagnosis was clear. The primary lesion was squamous cell carcinoma. The number and metastasis status of the lymph nodes in the neck dissection were clearly defined. 3. The clinical data are detailed. The enhanced CT scan was taken 20 days before the surgery at our hospital.

Exclusion criteria

Exclusion criteria: 1. Preoperative radiotherapy or chemotherapy had been performed. 2. The quality of the enhanced CT images was poor.

Design outcomes

Primary

MeasureTime frame
Sensitivity;Specificity;Accuracy;AUC;Precision;

Countries

China

Contacts

Public ContactZhang Wenbo

Peking University Hospital of Stomatology

michaelzhang1016@126.com+86 186 1064 1577

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026