Prospective Cohort Study of the Development of AI Diagnosing Subepithelial Lesions of the Gastrointestinal Tract

UMIN ID: UMIN000054285

Registered date:30/04/2024

Basic Information

• Recruitment status: Recruiting
• Health condition(s) or Problem(s) studied: Cases undergoing EUS examination aimed at diagnosis, tissue sampling, and follow-up for suspected submucosal tumors of the gastrointestinal tract
• Date of first enrollment: 2024/04/30
• Target sample size: 720
• Countries of recruitment: Japan
• Study type: Observational

Outcome(s)

• Primary Outcome: Accuracy in SEL's three-category differentiation (GIST, leiomyoma, and others) in EUS by an AI diagnostic system
• Secondary Outcome: Diagnostic performances (sensitivity, specificity, positive predictive value, negative predictive value, accuracy) of an AI diagnostic system and expert physicians in the two-category differentiation (GIST, others) of SEL; diagnostic performances in multi-category classification (accuracy, sensitivity per category); diagnostic capabilities of non-expert physicians; diagnostic capabilities of various biopsy procedures; and EUS findings contributing to diagnosis

Key inclusion & exclusion criteria

• Age minimum: 18years-old
• Age maximum: Not applicable
• Gender: Male and Female
• Exclude criteria: Patients deemed unsuitable as research subjects by the principal investigator; patients lacking the capacity to consent

Related Information

• Primary Sponsor: Nagoya University
• Source(s) of Monetary Support: Nagoya University