Development and Application of an Artificial Intelligence-driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis

August 1, 2024 updated by: Qun Zhao, Hebei Medical University

Hebei Medical University

The clinical trial titled "Development and Application of an Artificial Intelligence-Driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis" aims to enhance the detection and treatment of gastric cancer through the utilization of cutting-edge artificial intelligence (AI) technology. This study will develop an AI-driven model designed to accurately identify lymph node metastasis in patients with gastric cancer, which is crucial for staging the disease and planning effective treatment strategies.

The trial will involve a multidisciplinary team of oncologists, radiologists, data scientists, and AI experts who will collaborate to create a robust and precise identification system. Participants will undergo standard diagnostic procedures, and the AI model will analyze imaging and pathological data to predict lymph node involvement.

By comparing the AI model's predictions with traditional diagnostic methods, the study seeks to validate the model's accuracy and efficiency. This approach is expected to improve early detection rates, reduce diagnostic errors, and ultimately lead to better clinical outcomes for patients with gastric cancer. The successful implementation of this AI-driven model could revolutionize the current standards of care and serve as a blueprint for integrating AI technologies in other cancer diagnoses and treatments.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Estimated)

300

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
    • Hebei
      • Shijiazhuang, Hebei, China, 050011
        • Recruiting
        • Department of General Surgery
        • Principal Investigator:
          • Qun Zhao, Doctor
        • Contact:

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

Non-Probability Sample

Study Population

The study population for the clinical trial titled "Development and Application of an Artificial Intelligence-Driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis (AID-GLNM)" will consist of patients diagnosed with gastric cancer, with a focus on those exhibiting lymph node involvement.

Description

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.

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
Measure Description
Time Frame
Identification of metastatic lymph nodes
Time Frame: 2025-12-31
A prediction model based on artificial intelligence technology was constructed to accurately identify metastatic perigastric lymph nodes before surgery.
2025-12-31

Collaborators and Investigators

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

Sponsor

Hebei Medical University

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)

July 1, 2024

Primary Completion (Estimated)

December 31, 2025

Study Completion (Estimated)

July 30, 2030

Study Registration Dates

First Submitted

July 25, 2024

First Submitted That Met QC Criteria

August 1, 2024

First Posted (Actual)

August 2, 2024

Study Record Updates

Last Update Posted (Actual)

August 2, 2024

Last Update Submitted That Met QC Criteria

August 1, 2024

Last Verified

August 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • FUTURE08

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.

Clinical Trials on The Primary Focus of This Study is on Gastric Cancer

Clinical Trials on AI-Driven Identification Model for Gastric Cancer Lymph Node Metastasis (AID-GLNM)

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in Uruguay

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

Subscribe