Clinical trial Recruiting at 1 site Observational Ages 18 and up

Using AI to identify lymph node metastasis in gastric cancer

Official title: Hebei Medical University

Run by Hebei Medical University · NCT06534814 · Data updated 2026-11-12

This study is testing a new AI tool to see if it can better identify lymph node spread in people with gastric cancer compared to regular diagnostic methods.

Quick facts

Study typeObservational
Ages18 Years and up
SexAll
Enrollment300 (estimated)
SponsorHebei Medical University
Academic / other
Locations1 site (Shijiazhuang, Hebei)
StatusRecruiting
StartedJuly 1, 2024
Main results expectedDecember 31, 2025
Study endsJuly 30, 2030
Registry record updatedAugust 2, 2024
Trial IDNCT06534814 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Ideal candidates include adults aged 18 and older with a confirmed diagnosis of gastric cancer and suspected or confirmed lymph node involvement.

Probably not a fit

Patients who are pregnant, have severe comorbid conditions, or have previously used AI-driven diagnostic interventions for gastric cancer lymph node metastasis may not benefit from this study.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This study focuses on developing an artificial intelligence-driven model to accurately identify lymph node metastasis in patients with gastric cancer. A multidisciplinary team, including oncologists, radiologists, and data scientists, will collaborate to create this model. Participants will undergo standard diagnostic procedures, and the AI model will analyze imaging and pathological data to predict lymph node involvement. The study aims to validate the AI model's accuracy by comparing its predictions with traditional diagnostic methods.

Why it matters

Potential benefit: If successful, this approach could lead to more accurate staging and treatment planning for gastric cancer patients.

How similar studies have gone: While the use of AI in medical diagnostics is growing, this specific application for gastric cancer lymph node metastasis is relatively novel and has not been extensively tested in prior studies.

Who can join: the full rules

Show full inclusion / exclusion criteria
Inclusion Criteria:

1. Diagnosis of Gastric Cancer: Confirmed diagnosis of gastric cancer, either newly diagnosed or recurrent.
2. Lymph Node Involvement: Suspected or confirmed involvement of lymph nodes, as indicated by imaging studies or pathology reports.
3. Age: Patients aged 18 years or older.
4. Performance Status: An Eastern Cooperative Oncology Group (ECOG) performance status of 0 to 2, indicating a functional status that allows participation in the study.
5. Informed Consent: Ability to provide written informed consent to participate in the study.

Exclusion Criteria:

1. Pregnancy or Lactation: Pregnant or lactating women, due to potential risks to the fetus or infant.
2. Severe Comorbid Conditions: Presence of severe comorbid medical conditions that could interfere with the study or pose additional risks.
3. Previous AI-Driven Diagnostic Intervention: Prior use of any AI-driven diagnostic models specifically for gastric cancer lymph node metastasis.
4. Inability to Comply: Inability or unwillingness to comply with study procedures, including follow-up visits and data collection.
5. Mental or Cognitive Impairment: Conditions that impair the ability to provide informed consent or participate effectively in the study.

Where it's running

  • Department of General Surgery
    Shijiazhuang, Hebei, China
    Recruiting

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How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.