Clinical trial · Observational
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
NCT07078136CI-TRIAL-00092875recruitingClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (4)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Gastrointestinal Stromal Tumor (GIST) | Gastrointestinal Stromal Tumor | CURATED_BROADER | 0.80 |
| Leiomyoma | Leiomyoma | ONTOLOGY_EXACT | 0.98 |
| Schwannoma | Schwannoma | ONTOLOGY_EXACT | 0.98 |
| Submucosal Tumor | — | UNRESOLVED | — |
Interventions
Interventions (2)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Expert Endoscopist Assessment | Diagnostic Test | — | UNRESOLVED |
| Multimodal AI Model | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- All Participants
- description
- All enrolled patients with upper gastrointestinal subepithelial lesions confirmed by histopathology. Each participant will undergo standard diagnostic evaluation and independent multimodal AI prediction and expert endoscopist diagnosis.
- interventionNames
- Diagnostic Test: Multimodal AI Model
- Diagnostic Test: Expert Endoscopist Assessment
Primary outcomes (2)
- measure
- Diagnostic accuracy of a multimodal AI model for differentiating gastrointestinal stromal tumors (GISTs) from other upper gastrointestinal mesenchymal tumors
- timeFrame
- After the training process of the multimodal AI model is completed，on average per year
- description
- Receiver operating characteristic (ROC) analyses, sensitivity, specificity, accuracy, positive predictive value and negative predictive value will be used to evaluate the efficacy of the model
- measure
- Predictive accuracy of the multimodal AI model for risk stratification of GISTs
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
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
References
Publications (40)
- BACKGROUNDChinese Society of Digestive Endoscopy Tunnel Technology Collaboration Group, Endoscopist Branch of Chinese Medical Doctor Association, and Digestive Endoscopy Branch of Beijing Medical Association. Expert Consensus on Endoscopic Diagnosis and Treatment of Gastrointestinal Stromal Tumors in China (2020, Beijing). Chinese Journal of Digestive Endoscopy, 2021(07): 505-514.
- BACKGROUNDShen L, Cao H, Qin S, et al. Chinese Consensus on the Diagnosis and Treatment of Gastrointestinal Stromal Tumors (2017 Version). Electronic Journal of Integrated Cancer Therapy, 2018; 4(01): 31-43.
- BACKGROUNDGomes RSA, de Oliveira GHP, de Moura DTH, Kotinda APST, Matsubayashi CO, Hirsch BS, Veras MO, Ribeiro Jordao Sasso JG, Trasolini RP, Bernardo WM, de Moura EGH. Endoscopic ultrasound artificial intelligence-assisted for prediction of gastrointestinal stromal tumors diagnosis: A systematic review and meta-analysis. World J Gastrointest Endosc. 2023 Aug 16;15(8):528-539. doi: 10.4253/wjge.v15.i8.528. PMID 37663113
- RESULTAbe K, Tominaga K, Yamamiya A, Inaba Y, Kanamori A, Kondo M, Suzuki T, Watanabe H, Kawano M, Sato T, Yoshitake N, Ohwada T, Konno M, Hanatsuka K, Masuyama H, Goda K, Haruyama Y, Irisawa A; NUTSHELL20 Study group. Natural History of Small Gastric Subepithelial Lesions Less than 20 mm: A Multicenter Retrospective Observational Study (NUTSHELL20 Study). Digestion. 2023;104(3):174-186. doi: 10.1159/000527421. Epub 2022 Dec 5. PMID 36470211
- RESULTStandards of Practice Committee; Faulx AL, Kothari S, Acosta RD, Agrawal D, Bruining DH, Chandrasekhara V, Eloubeidi MA, Fanelli RD, Gurudu SR, Khashab MA, Lightdale JR, Muthusamy VR, Shaukat A, Qumseya BJ, Wang A, Wani SB, Yang J, DeWitt JM. The role of endoscopy in subepithelial lesions of the GI tract. Gastrointest Endosc. 2017 Jun;85(6):1117-1132. doi: 10.1016/j.gie.2017.02.022. Epub 2017 Apr 3. No abstract available. PMID 28385194
- RESULTLi J, Ye Y, Wang J, Zhang B, Qin S, Shi Y, He Y, Liang X, Liu X, Zhou Y, Wu X, Zhang X, Wang M, Gao Z, Lin T, Cao H, Shen L, Chinese Society Of Clinical Oncology Csco Expert Committee On Gastrointestinal Stromal Tumor. Chinese consensus guidelines for diagnosis and management of gastrointestinal stromal tumor. Chin J Cancer Res. 2017 Aug;29(4):281-293. doi: 10.21147/j.issn.1000-9604.2017.04.01.