AI using endoscopic ultrasound and white-light endoscopy to diagnose upper GI mesenchymal tumors
Multicenter Observational Study of a Multimodal AI Model Using EUS, White-Light Endoscopy, and Clinical Data for Diagnosis of Upper GI Mesenchymal Tumors and Risk Stratification of Gastric GISTs
This project will test a multimodal AI tool that uses endoscopic ultrasound, white-light endoscopy images, and clinical data to help diagnose and risk-stratify upper gastrointestinal subepithelial tumors in adults who have had endoscopy.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 130 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Huazhong University of Science and Technology Academic / other |
| Locations | 1 site (Wuhan, Hubei) |
| Trial ID | NCT07078136 on ClinicalTrials.gov |
What this trial studies
This multicenter observational project combines retrospective image datasets for training and validation with prospectively recruited cases for independent testing. High-quality endoscopic ultrasound (EUS) images, white-light endoscopy (WLE) images, and clinical data are collected under strict quality-control criteria. A multimodal AI model integrates these inputs via a multi-branch fusion strategy and is compared to expert endoscopists using cross-validation on prospectively gathered data. The primary comparisons are diagnostic classification of subepithelial lesions and risk stratification of gastric GISTs, with performance measured against histopathological reference standards.
Who should consider this trial
Good fit: Adults (age ≥18) with an upper gastrointestinal subepithelial lesion who have undergone white-light endoscopy and completed EUS, with histopathological confirmation or adequate biopsy/sampling, are ideal candidates.
Not a fit: Patients without high-quality EUS/WLE images, without histopathologic confirmation or sampling, pediatric patients, or those with lesions outside the upper GI tract are unlikely to benefit from this protocol.
Why it matters
Potential benefit: If successful, the AI could improve diagnostic accuracy and risk stratification for upper GI mesenchymal tumors, helping guide appropriate treatment and potentially reducing unnecessary procedures.
How similar studies have performed: According to existing literature, no prior multimodal AI model has reported diagnostic performance for both SEL classification and gastric GIST risk stratification, so this approach is novel and largely unproven in combination.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age ≥ 18 years old * Patients with an upper gastrointestinal subepithelial lesion (SEL) identified by white-light endoscopy and who have completed an endoscopic ultrasound (EUS) examination * Patients with a histopathological diagnosis of GIST confirmed by surgical or endoscopic resection, or other SELs confirmed by surgical resection, EUS-guided sampling, or other biopsy techniques * EUS image quality meets the following quality control standards 1. Equipment requirements: Olympus EU-ME2/ME1 processor (Olympus Medical Systems Corp., Tokyo, Japan); radial EUS scope (GF-UE260/GF-UE240; Olympus, Tokyo, Japan) or linear EUS scope (GF-UCT260/GF-UCT240; Olympus, Tokyo, Japan); miniature probe (UM2R/3R; Olympus, Tokyo, Japan); Pentax ARIETTA 850 processor (Pentax, Tokyo, Japan); radial EUS scope (EG-3670URK, Pentax, Tokyo, Japan); linear EUS scope (EG-3870UT, Pentax, Tokyo, Japan); Fujifilm SU-8000 or SU-9000 processor; linear EUS scope (EG-580UT, Fujifilm, Tokyo, Japan); radial EUS scope (EG-580UR, Fujifilm, Tokyo, Japan) 2. EUS images clearly showing the lesion and surrounding tissue characteristics (at least 5 images or video); must include at least one image of the maximum lesion diameter, one image showing the layer of origin, and one image demonstrating the growth pattern (intraluminal/extraluminal) 3. EUS images must not contain artificial annotations, such as measurement scales, biopsy needles, Doppler signals, or elastography overlays 4. Image resolution must be at least 448 × 448 pixels * WLE (white-light endoscopy) image quality meets the following standards: images must clearly show the lesion location, mucosal features, and margins; at least one close-up and one distant view * Complete clinical data and histopathological reports must be available Exclusion Criteria: * Age \< 18 years old * Absolute contraindications for EUS examination, history of gastric surgery, pregnancy, severe comorbidities, or known allergy to anesthetic agents * EUS examination terminated prematurely due to esophageal stricture, obstruction, large space-occupying lesions, rapid changes in heart rate or respiratory rate, patient intolerance, or excessive residual food * EUS image quality does not meet the required quality control standards * Pathological specimens do not meet diagnostic requirements: insufficient biopsy tissue (only R0 resection specimens are accepted for the GIST group), or incomplete immunohistochemical staining (missing CD117/CD34/DOG-1 expression report for the GIST group) * Pathological results indicate that the lesion is a metastatic tumor originating from another site
Where this trial is running
Wuhan, Hubei
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology — Wuhan, Hubei, China (Recruiting)
Study contacts
- Study coordinator: Bin Cheng
- Email: b.cheng@tjh.tjmu.edu.cn
- Phone: +8613986097542
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.