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Construction and Validation of a Deep Learning Model for Lymph Node Metastasis in Early Gastric Cancer

A Model for Predicting Lymph Node Metastasis in Early Gastric Cancer Based on Multi-Instance Tumor Segmentation and Classification

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500109758
Enrollment
Unknown
Registered
2025-09-24
Start date
2025-12-01
Completion date
Unknown
Last updated
2025-09-29

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

Conditions

Gastric Cancer

Interventions

Gold Standard:Pathological diagnosis
Index test:Risk prediction model for lymph node metastasis in early gastric cancer

Sponsors

Nanjing Drum Tower Hospital of Nanjing University Medical School
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Patients with stage T1 early gastric cancer who underwent surgical resection, ESD plus surgical resection, or ESD alone between 2010 and 2024, with histologically confirmed lymph node metastasis status or a minimum follow-up period of 3 years.

Exclusion criteria

Exclusion criteria: 1. Patients who received preoperative chemotherapy or radiotherapy. 2. Patients in the ESD-only group with a follow-up period of less than 3 years. 3. Patients with incomplete lymph node metastasis information. 4. Patients with other malignant tumors. 5. Patients with incomplete pathological data.

Design outcomes

Primary

MeasureTime frame
Accuracy in predicting lymph node metastasis;—

Secondary

MeasureTime frame
Reduction in the proportion of surgery ;—

Countries

China

Contacts

Public ContactGuifang Xu

Nanjing Drum Tower Hospital of Nanjing University Medical School

xuguifang@njglyy.com+86 138 5229 3376

Outcome results

None listed

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