T1 Gastric Cancer Lymph Node Metastasis Early Gastric Cancer Artificial Intelligence-Assisted Diagnosis Multimodal Data IntegrationNCT07124754
Multimodal Deep Learning for Lymph Node Metastasis Prediction and Physician Performance Assessment in T1 Gastric Cancer
An observational study of T1 Gastric Cancer Lymph Node Metastasis Early Gastric Cancer Artificial Intelligence-Assisted Diagnosis Multimodal Data Integration, run by Qun Zhao at 1 site in China.
Trial summary
This study aims to develop and validate an artificial intelligence (AI) model that integrates clinical, pathological, and imaging data to predict the presence of lymph node metastasis (LNM) in patients with T1-stage gastric cancer. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- T1 Gastric Cancer Lymph Node Metastasis Early Gastric Cancer Artificial Intelligence-Assisted Diagnosis Multimodal Data Integration
- What is being tested?
- Multimodal Artificial Intelligence Diagnostic Model for Lymph Node Metastasis in T1 Gastric Cancer
- How many people
- 300 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2025to 30 Dec 2025
- How long will I take part?
- 36 Months
- 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 years and older
- All sexes
- Adult, Older adult
Study population: Patients diagnosed with T1-stage gastric adenocarcinoma who undergo radical gastrectomy with lymph node dissection at participating centers. Participants must have available preoperative clinical, imaging, and pathological data for AI model input and postoperative histopathological confirmation of lymph node status.
Who may be able to join
- Age 18 years or older
- Histologically confirmed primary gastric adenocarcinoma
- Clinical stage T1 (T1a or T1b) confirmed by endoscopy and imaging
- Undergoing radical gastrectomy with lymph node dissection
- Preoperative data available: clinical variables, CT imaging, and pathology slides
- Written informed consent provided
Who cannot join
- History of other malignancies within the past 5 years
- Received neoadjuvant chemotherapy or radiotherapy
- Incomplete clinical or pathological data
- Poor quality or missing CT or histopathology images
- Patients with distant metastasis (M1) at diagnosis
- Inability or refusal to provide informed consent
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, 1 recruiting
- Recruiting
the Fourth Hospital of Hebei Medical University
Shijiazhuang, None Selected, 050011
Ping'an Ding, 031186095363, ding_ping_an@hebmu.edu.cn
About this study
Official title: Development and Validation of a Multimodal Artificial Intelligence Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer and Its Impact on Physician Diagnostic Performance
This study aims to develop and validate an artificial intelligence (AI) model that integrates clinical, pathological, and imaging data to predict the presence of lymph node metastasis (LNM) in patients with T1-stage gastric cancer.
The study will also compare the diagnostic performance of physicians with and without AI assistance, including clinicians with varying levels of experience.
The goal is to improve early decision-making and support more personalized treatment strategies for patients with early gastric cancer.
- Being tested
- Multimodal Artificial Intelligence Diagnostic Model for Lymph Node Metastasis in T1 Gastric Cancer
- Keywords
- T1 Gastric Cancer Lymph Node Metastasis Early Gastric Cancer Artificial Intelligence-Assisted Diagnosis Multimodal Data Integration
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Multimodal Artificial Intelligence Diagnostic Model for Lymph Node Metastasis in T1 Gastric CancerDiagnostic test
This intervention involves the use of a custom-built artificial intelligence (AI) diagnostic model that integrates multimodal data-including clinical variables, histopathological features, and imaging data-to predict lymph node metastasis in patients with T1-stage gastric cancer.
The model provides risk probability scores and classification outputs that assist physicians in diagnostic decision-making.
The AI system will be compared with physician performance at different levels of experience (resident, attending, senior) to assess its impact on diagnostic accuracy and clinical decision support.
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic Accuracy of the AI Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer
Measured: Immediately after surgery (within 7 days postoperatively, based on final pathological report)
Diagnostic Accuracy of the AI Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer
Measured: At the time of final pathological diagnosis (typically within 3-7 days after surgery)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Aug 2025
- Study start1 Jan 2025
- Primary completion30 Dec 2025 (estimated)
- Study completion30 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for T1 Gastric Cancer Lymph Node Metastasis Early Gastric Cancer Artificial Intelligence-Assisted Diagnosis Multimodal Data IntegrationStudies 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
- 300 participants (estimated)
- Target duration
- 36 Months
Sponsor and investigators
- Lead sponsor
- Qun Zhao
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Qun Zhao, Hebei Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07124754
- Sponsor's protocol ID
- GC-RAD-AI-2025-04
- Status last verified
- Aug 2025
- First submitted
- 3 Aug 2025
- Last updated
- 15 Aug 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 15 Aug 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development and Validation of a Multimodal Artificial Intelligence Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer and Its Impact on Physician Diagnostic Performance
- ClinicalTrials.gov ID
- NCT07124754
- Acronym / sponsor ID
- GC-RAD-AI-2025-04
- Keywords
- T1 Gastric Cancer Lymph Node Metastasis Early Gastric Cancer Artificial Intelligence-Assisted Diagnosis Multimodal Data Integration
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 300 participants (estimated)
- Lead sponsor
- Qun ZhaoUniversity, hospital or other
- Study start
- 1 Jan 2025 (actual)
- Primary completion
- 30 Dec 2025 (estimated)
- Study completion
- 30 Dec 2025 (estimated)
- First posted
- 15 Aug 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) model that integrates clinical, pathological, and imaging data to predict the presence of lymph node metastasis (LNM) in patients with T1-stage gastric cancer.
The study will also compare the diagnostic performance of physicians with and without AI assistance, including clinicians with varying levels of experience.
The goal is to improve early decision-making and support more personalized treatment strategies for patients with early gastric cancer.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 36 Months
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Patients diagnosed with T1-stage gastric adenocarcinoma who undergo radical gastrectomy with lymph node dissection at participating centers. Participants must have available preoperative clinical, imaging, and pathological data for AI model input and postoperative histopathological confirmation of lymph node status.
Key inclusion criteria (6 listed)
- Age 18 years or older
- Histologically confirmed primary gastric adenocarcinoma
- Clinical stage T1 (T1a or T1b) confirmed by endoscopy and imaging
- Undergoing radical gastrectomy with lymph node dissection
- Preoperative data available: clinical variables, CT imaging, and pathology slides
Key exclusion criteria (6 listed)
- History of other malignancies within the past 5 years
- Received neoadjuvant chemotherapy or radiotherapy
- Incomplete clinical or pathological data
- Poor quality or missing CT or histopathology images
- Patients with distant metastasis (M1) at diagnosis
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 |
|---|---|---|
| Multimodal Artificial Intelligence Diagnostic Model for Lymph Node Metastasis in T1 Gastric CancerThis intervention involves the use of a custom-built artificial intelligence (AI) diagnostic model that integrates multimodal data-including clinical variables, histopathological features, and imaging data-to predict lymph node metastasis in patients with T1-stage gastric cancer. The model provides risk probability scores and classification outputs that assist physicians in diagnostic decision-making. The AI system will be compared with physician performance at different levels of experience (resident, attending, senior) to assess its impact on diagnostic accuracy and clinical decision support. | Diagnostic test | – |
Primary outcome
Diagnostic Accuracy of the AI Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer
Time frame: Immediately after surgery (within 7 days postoperatively, based on final pathological report)
Diagnostic Accuracy of the AI Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer
Time frame: At the time of final pathological diagnosis (typically within 3-7 days after surgery)
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 15 Aug 2025.
- Individual participant dataSharing planned: Undecided
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 Fourth Hospital of Hebei Medical University
Shijiazhuang, China
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 T1 Gastric Cancer Lymph Node Metastasis Early Gastric Cancer Artificial Intelligence-Assisted Diagnosis Multimodal Data Integration, 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 6 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: looking for participants now, as of the sponsor's last update on 15 Aug 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?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic Accuracy of the AI Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer (time frame: Immediately after surgery (within 7 days postoperatively, based on final pathological report)). The study lists 2 primary outcomes in all. 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 15 Aug 2025.