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Predicting lymph node metastasis of laryngeal squamous cell carcinoma using CT radiomics and deep learning

Predicting lymph node metastasis of laryngeal squamous cell carcinoma using CT radiomics and deep learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600134112
Enrollment
Unknown
Registered
2026-10-10
Start date
2025-04-03
Completion date
Unknown
Last updated
2026-10-12

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

Conditions

Laryngeal Squamous Cell Carcinoma

Interventions

Gold Standard:Postoperative pathological diagnosis
Index test:A prediction model based on CT radiomics and deep learning, aiming to accurately predict the possibility of lymph node metastasis in patients with laryngeal cancer.

Sponsors

Qilu Hospital of Shandong University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 85 Years

Inclusion criteria

Inclusion criteria: 1. The pathological diagnosis was laryngeal squamous cell carcinoma. 2. The clinical examination, CT, B-ultrasound and MRI determined the clinical N0 stage. 3. For patients with laryngeal squamous cell carcinoma who received surgical treatment, the enhanced CT was completed within one week before the surgery.

Exclusion criteria

Exclusion criteria: 1. Not receiving preoperative neoadjuvant radiotherapy and chemotherapy 2. No multiple primary cancers or distant metastasis 3. Incomplete clinical data, imaging data or pathological report data

Design outcomes

Primary

MeasureTime frame
Area under curve(AUC);Sensitivity;Whether there is lymph node metastasis;—

Secondary

MeasureTime frame
Specificity;—

Countries

China

Contacts

Public ContactLei Dapeng

Qilu Hospital of Shandong University

leidapeng@sdu.edu.cn+86 185 6008 5656

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Oct 17, 2026