Gastric Cancer Adenocarcinoma MetastaticNCT06957678
AI-Based Prediction of Lymph Node Metastasis in Gastric Cancer Using Preoperative Multimodal Data
An observational study of Gastric Cancer Adenocarcinoma Metastatic and Lymph Node Metastasis, run by Qun Zhao at 1 site in China.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Gastric Cancer Adenocarcinoma Metastatic, Lymph Node Metastasis, Artificial Intelligence (AI) in Diagnosis
- What is being tested?
- Artificial Intelligence-Based Predictive Model for Lymph Node Metastasis
- How many people
- 1,200 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2025to 31 Dec 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- Adult, Older adult
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.
Who may be able to join
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site
the Fourth Hospital of Hebei Medical University
Shijiazhuang, None Selected, 050011
About this study
Official title: 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.
- Conditions
- Gastric Cancer Adenocarcinoma Metastatic, Lymph Node Metastasis, Artificial Intelligence (AI) in Diagnosis
- Being tested
- Artificial Intelligence-Based Predictive Model for Lymph Node Metastasis
- Medical subject headings
- Lymphatic Metastasis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial Intelligence-Based Predictive Model for Lymph Node MetastasisDiagnostic test
The intervention is an artificial intelligence-based predictive model developed using preoperative multimodal data, including contrast-enhanced CT images, preoperative histopathological findings, and clinical features. The model is designed to predict (1) the presence or absence of lymph node metastasis, (2) the specific lymph node stations involved, and (3) the individual lymph nodes involved. Each lymph node's metastatic status is confirmed by serial pathological sectioning of surgically retrieved nodes, ensuring a highly accurate reference standard for model training and validation. This distinguishes the intervention from traditional imaging-based assessments and from other AI models that do not use individually validated lymph node pathology.
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic Accuracy of the AI Model in Predicting Presence of Lymph Node Metastasis in Gastric Cancer
Measured: From Preoperative Evaluation to Completion of Postoperative Pathological Analysis (Approximately 4-6 Weeks)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 May 2025
- Study start1 Jan 2025
- Primary completion31 Dec 2025 (estimated)
- Study completion31 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Gastric Cancer Adenocarcinoma MetastaticStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Qun Zhao
- Sponsor type
- University, hospital or other
- Collaborators
- Renmin Hospital of Wuhan University, Nanjing University School of Medicine, Baoding First Central Hospital, Hengshui People's Hospital, No.1 Hospital of Shijiazhuang City, The Second Affiliated Hospital of Xingtai Medical College
- Responsible party
- Sponsor-investigator, Qun Zhao, Hebei Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06957678
- Sponsor's protocol ID
- GC-RAD-AI-2025-02
- Status last verified
- Apr 2025
- First submitted
- 26 Apr 2025
- Last updated
- 4 May 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 4 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence-Based Prediction of Lymph Node Metastasis and Nodal Station Involvement in Gastric Cancer Using Preoperative Multimodal Imaging and Pathology Data
- ClinicalTrials.gov ID
- NCT06957678
- Acronym / sponsor ID
- GC-RAD-AI-2025-02
- Conditions
- Gastric Cancer Adenocarcinoma Metastatic, Lymph Node Metastasis, Artificial Intelligence (AI) in Diagnosis
- Study type
- Observational
- Recruitment status
- Enrolling by invitation
- Enrolment
- 1,200 participants (estimated)
- Lead sponsor
- Qun ZhaoUniversity, hospital or other
- Collaborators
- Renmin Hospital of Wuhan University, Nanjing University School of Medicine, Baoding First Central Hospital, Hengshui People's Hospital, No.1 Hospital of Shijiazhuang City, The Second Affiliated Hospital of Xingtai Medical College
- Study start
- 1 Jan 2025 (actual)
- Primary completion
- 31 Dec 2025 (estimated)
- Study completion
- 31 Dec 2025 (estimated)
- First posted
- 4 May 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (6 listed)
- 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
Key exclusion criteria (5 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial Intelligence-Based Predictive Model for Lymph Node MetastasisThe intervention is an artificial intelligence-based predictive model developed using preoperative multimodal data, including contrast-enhanced CT images, preoperative histopathological findings, and clinical features. The model is designed to predict (1) the presence or absence of lymph node metastasis, (2) the specific lymph node stations involved, and (3) the individual lymph nodes involved. Each lymph node's metastatic status is confirmed by serial pathological sectioning of surgically retrieved nodes, ensuring a highly accurate reference standard for model training and validation. This distinguishes the intervention from traditional imaging-based assessments and from other AI models that do not use individually validated lymph node pathology. | Diagnostic test | – |
Primary outcome
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)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 May 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Gastric Cancer Adenocarcinoma Metastatic and Lymph Node Metastasis, run by Qun Zhao at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: enrolling by invitation, as of the sponsor's last update on 4 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 4 May 2025.