RecruitingNCT07078136

Multicenter Observational Study of Multimodal AI for Upper GI Mesenchymal Tumor Diagnosis

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


Sponsor

Huazhong University of Science and Technology

Enrollment

130 participants

Start Date

Jul 28, 2025

Study Type

OBSERVATIONAL

Conditions

Summary

This study develops a multimodal AI model using endoscopic ultrasound, white-light endoscopy, and clinical information to support the diagnosis of upper GI mesenchymal tumors and the risk stratification of gastric GISTs.


Eligibility

Min Age: 18 Years

Inclusion Criteria10

  • 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
  • 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)
  • 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)
  • EUS images must not contain artificial annotations, such as measurement scales, biopsy needles, Doppler signals, or elastography overlays
  • 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 Criteria6

  • 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

Interventions

DIAGNOSTIC_TESTMultimodal AI Model

Patients' endoscopic images, EUS images, and clinical data will be analyzed by a multimodal AI model for lesion classification and GIST risk stratification.

DIAGNOSTIC_TESTExpert Endoscopist Assessment

Endoscopic ultrasound images will be interpreted by experienced endoscopists for comparison with the AI model.


Locations(1)

Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology

Wuhan, Hubei, China

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NCT07078136


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