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Recruiting NCT07551466

NCT07551466 AI Model for Early Gastric Cancer Diagnosis Using Endoscopic Imaging

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Clinical Trial Summary
NCT ID NCT07551466
Status Recruiting
Phase —
Sponsor The First Affiliated Hospital of Soochow University
Condition Early Gastric Cancer
Study Type OBSERVATIONAL
Enrollment 100 participants
Start Date 2026-05-01
Primary Completion 2026-12-01

Eligibility & Interventions

Sex All sexes
Min Age 18 Years
Max Age 80 Years
Study Type OBSERVATIONAL
Interventions
No intervention (observational study)

Eligibility Fast-Check

Enter your details for a quick preliminary check. This does not replace medical advice.

What to Expect as a Participant

This is an observational study. You will not receive an experimental treatment; researchers will collect data based on your existing condition or standard treatment.

This trial targets 100 participants in total. It began in 2026-05-01 with a primary completion date of 2026-12-01.

⚠ 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

Early gastric cancer (EGC) is often difficult to detect accurately during endoscopic examination due to subtle morphological features and variability among endoscopists. Artificial intelligence (AI) has shown promise in improving diagnostic performance; however, most existing models lack interpretability and rely on single-modality imaging. This study aims to develop and evaluate an explainable multimodal artificial intelligence model for the diagnosis of early gastric cancer using endoscopic imaging. The model integrates features derived from white-light imaging and image-enhanced endoscopy, along with quantitative image features and clinical data, to improve diagnostic accuracy and provide interpretable decision support. The primary outcome is the diagnostic performance of the AI model for detecting early gastric cancer, evaluated by area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. The results of this study are expected to provide evidence for the clinical utility of explainable AI in endoscopic diagnosis and support the development of reliable human-AI collaborative diagnostic systems.

Eligibility Criteria

Inclusion Criteria: * Age ≥18 years * Suspicious gastric lesions identified on white-light imaging (WLI) * Preoperative biopsy indicating precancerous lesions (dysplasia or intraepithelial neoplasia) or adenocarcinoma, with preoperative magnifying endoscopy with narrow-band imaging (ME-NBI) performed * Patients meeting the absolute indications for endoscopic submucosal dissection (ESD) and who underwent ESD Exclusion Criteria: * Non-adenocarcinoma histological types (e.g., lymphoma) * Patients who did not undergo ME-NBI examination or did not receive ESD * Lesions invading the muscularis propria or deeper layers * Missing or indeterminate postoperative histopathological results

Contact & Investigator

Central Contact

Li he Liu

✉ lhliu2024@stu.suda.edu.cn

📞 +8615943593759

Frequently Asked Questions

Who can join the NCT07551466 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 NCT07551466 currently recruiting?

Yes, NCT07551466 is actively recruiting participants. Contact the research team at lhliu2024@stu.suda.edu.cn for enrollment information.

Where is the NCT07551466 trial being conducted?

This trial is being conducted at Suzhou, China.

Who is sponsoring the NCT07551466 clinical trial?

NCT07551466 is sponsored by The First Affiliated Hospital of Soochow University. The trial plans to enroll 100 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