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Recruiting NCT07835087

NCT07835087 Image-Guided Platform-Assisted Sentinel Lymph Node Retrieval in Early Gastric Cancer

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Clinical Trial Summary
NCT ID NCT07835087
Status Recruiting
Phase —
Sponsor Beijing Friendship Hospital
Condition Early Gastric Cancer
Study Type INTERVENTIONAL
Enrollment 36 participants
Start Date 2026-08-14
Primary Completion 2027-08-14

Eligibility & Interventions

Sex All sexes
Min Age 18 Years
Max Age 80 Years
Study Type INTERVENTIONAL
Interventions
Image-Guided Retrieval Specimen PlatformTraditional Palpation-Based Sentinel Lymph Node Retrieval

Eligibility Fast-Check

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What to Expect as a Participant

You will actively receive the study intervention — which may be a drug, biologic, device, or procedure.

This trial targets 36 participants in total. It began in 2026-08-14 with a primary completion date of 2027-08-14.

⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.

Brief Summary

This prospective, single-center, randomized controlled trial aims to evaluate the clinical effectiveness of an Image-Guided Platform assisted by a deep learning model for sentinel lymph node (SLN) retrieval in patients with early gastric cancer undergoing laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery (LECS-SNNS). A total of 36 eligible participants will be randomly assigned in a 1:1 ratio to either the Image-Guided Platform group or the Traditional Palpation group. Both groups will undergo standardized indocyanine green fluorescence-guided sentinel lymphatic basin dissection and initial retrieval of fluorescent sentinel lymph nodes. In the experimental group, the remaining sentinel lymphatic basin (SLB) tissue will be examined using the Image-Guided Platform, which integrates radiographic and optical imaging with a deep learning model to identify and localize suspected lymph nodes. In the control group, LN retrieval will be performed using traditional visual inspection and palpation. The primary objective is to determine whether Image-Guided Platform-assisted LN retrieval increases the total number of SLNs retrieved intraoperatively compared with Traditional Palpation. Secondary objectives include assessment of LN retrieval efficiency, pathological findings, additional LN identification during permanent pathological examination, concordance between intraoperative frozen-section and permanent pathological examination, and other procedural, pathological, technical, and clinical outcomes relevant to the feasibility and performance of the Image-Guided Platform and deep learning model.

Eligibility Criteria

Inclusion Criteria: 1. Age between 18 and 80 years, inclusive. 2. Eastern Cooperative Oncology Group (ECOG) performance status of 0-2 and considered able to tolerate surgery and anesthesia. 3. Histologically confirmed gastric adenocarcinoma based on preoperative endoscopic biopsy. 4. Clinical stage cT1N0M0 based on multidisciplinary evaluation and appropriate preoperative examinations, including endoscopy and imaging, or patients after non-curative endoscopic submucosal dissection (ESD) who are considered appropriate candidates for further surgical treatment. 5. Adequate hepatic, renal, cardiac, pulmonary, and bone marrow function to tolerate the planned surgical and perioperative management. 6. Considered clinically suitable for laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery (LECS-SNNS). 7. Able to understand the study procedures and provide written informed consent voluntarily. Exclusion Criteria: 1. Patients who meet the absolute indications for endoscopic submucosal dissection according to the applicable Chinese gastric cancer treatment guidelines. 2. Contraindications to the use of the lymphatic tracer or to endoscopic examination. 3. Unable to undergo ESD or failure of ESD treatment. 4. Inability to determine the extent of tracer staining or fluorescence mapping. 5. Contraindications to surgery, including clinically significant coagulation disorders or severe cardiopulmonary dysfunction. 6. Previous gastrointestinal surgery, chemotherapy, or radiotherapy. 7. Preoperative imaging indicating bulky, conglomerated, or markedly enlarged metastatic lymph nodes. 8. Concurrent malignancy involving another organ system, or intraoperative confirmation of metastatic gastric cancer or a non-gastric primary malignancy. 9. Pregnancy or breastfeeding. 10. Psychiatric disorders, cognitive impairment, or other conditions that impair the ability to provide informed consent or comply with study procedures. 11. Any other condition that, in the investigator's judgment, makes the individual unsuitable for participation in the study.

Contact & Investigator

Central Contact

Zhi Zheng, MD

✉ zhengzhi@ccmu.edu.cn

📞 +86-18311002896

Frequently Asked Questions

Who can join the NCT07835087 clinical trial?

This trial is open to participants of all sexes, aged 18 Years or older, up to 80 Years, studying Early Gastric Cancer. Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.

Is NCT07835087 currently recruiting?

Yes, NCT07835087 is actively recruiting participants. Contact the research team at zhengzhi@ccmu.edu.cn for enrollment information.

Where is the NCT07835087 trial being conducted?

This trial is being conducted at Beijing, China.

Who is sponsoring the NCT07835087 clinical trial?

NCT07835087 is sponsored by Beijing Friendship Hospital. The trial plans to enroll 36 participants.

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ClinicalMetric — Independent clinical trial intelligence platform. Not affiliated with NIH, ClinicalTrials.gov, the U.S. FDA, or any pharmaceutical company, hospital, or clinical research organization. Trial data is sourced from ClinicalTrials.gov for informational purposes only and does not constitute medical advice. Do not make any treatment, enrollment, or health decisions based solely on information found here — always consult a qualified healthcare professional. Full Disclaimer  ·  Last Reviewed: November 2026  ·  Data Methodology