AI-Based Prediction of Lymph Node Metastasis in Gastric Cancer Using Preoperative Multimodal Data

April 26, 2025 updated by: Qun Zhao

Artificial Intelligence-Based Prediction of Lymph Node Metastasis and Nodal Station Involvement in Gastric Cancer Using Preoperative Multimodal Imaging and Pathology Data

This study aims to develop and validate an artificial intelligence (AI) system that can predict whether lymph node metastasis has occurred in patients with gastric cancer before surgery. Using preoperative imaging and pathology data, the AI models will not only predict if metastasis is present but also identify which specific lymph node stations or individual lymph nodes are involved. All lymph nodes will be carefully removed during surgery and examined one by one with detailed pathological methods to ensure accurate diagnosis. The goal is to improve the accuracy of lymph node assessment and assist doctors in making better treatment decisions.

Study Overview

Status

Enrolling by invitation

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Estimated)

1200

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • None Selected
      • Shijiazhuang, None Selected, China, 050011
        • The Fourth Hospital of Hebei Medical University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

N/A

Sampling Method

Probability Sample

Study Population

The study will enroll adult patients diagnosed with gastric adenocarcinoma who are scheduled to undergo curative-intent gastrectomy with lymphadenectomy. Participants must have completed preoperative imaging studies and histopathological evaluation. All enrolled patients will have individually retrieved lymph nodes evaluated by detailed pathological examination to provide a definitive reference for lymph node metastasis status.

Description

Inclusion Criteria:

  • Age 18 years or older

Histologically confirmed gastric adenocarcinoma

Scheduled for curative-intent gastrectomy with lymphadenectomy

Completed preoperative imaging with contrast-enhanced CT or MRI

Available preoperative biopsy pathology report

Able and willing to provide written informed consent

Exclusion Criteria:

  • Evidence of distant metastasis on preoperative imaging

Prior chemotherapy, radiotherapy, or major abdominal surgery

Severe comorbidities contraindicating surgery

Incomplete or poor-quality preoperative imaging or pathology data

Pregnancy or lactation

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
Diagnostic Accuracy of the AI Model in Predicting Presence of Lymph Node Metastasis in Gastric Cancer
Time Frame: From Preoperative Evaluation to Completion of Postoperative Pathological Analysis (Approximately 4-6 Weeks)
From Preoperative Evaluation to Completion of Postoperative Pathological Analysis (Approximately 4-6 Weeks)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Qun Zhao

Collaborators

Nanjing University School of Medicine
Renmin Hospital of Wuhan University
Baoding First Central Hospital
Hengshui People's Hospital
No.1 Hospital of Shijiazhuang City
The Second Affiliated Hospital of Xingtai Medical College

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2025

Primary Completion (Estimated)

December 31, 2025

Study Completion (Estimated)

December 31, 2025

Study Registration Dates

First Submitted

April 26, 2025

First Submitted That Met QC Criteria

April 26, 2025

First Posted (Actual)

May 4, 2025

Study Record Updates

Last Update Posted (Actual)

May 4, 2025

Last Update Submitted That Met QC Criteria

April 26, 2025

Last Verified

April 1, 2025

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • GC-RAD-AI-2025-02

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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