An artificial intelligence model utilizing endoscopic ultrasonography for differentiating small and micro gastric stromal tumors from gastric leiomyomas.

Journal: BMC gastroenterology
PMID: 40205374

Abstract

BACKGROUND: Gastric stromal tumors (GSTs) and gastric leiomyomas (GLs) represent the primary subtypes of gastric submucosal tumors (SMTs) characterized by distinct biological characteristics and treatment modalities. The accurate differentiation between GSTs and GLs poses a significant clinical challenge. Recent advancements in artificial intelligence (AI) leveraging endoscopic ultrasonography (EUS) have demonstrated promising results in the categorization of larger-diameter SMTs (> 2.0 cm). However, the diagnostic capacity of AI models for micro-diameter SMTs (< 1.0 cm) remains uncertain due to limited imaging features. This study seeks to develop a specialized diagnostic model utilizing EUS images to differentiate small and micro GSTs from GLs effectively.

Authors

  • Ruifeng Duan
    Department of Gastroenterology and Digestive Endoscopy Center, The Second Hospital of Jilin University, Chang Chun, Jilin, China.
  • Liwei Duan
    Department of Gastroenterology and Digestive Endoscopy Center, The Second Hospital of Jilin University, Chang Chun, Jilin, China.
  • Xin Chen
    University of Nottingham, Nottingham, United Kingdom.
  • Min Liu
    Department of Critical Care Medicine, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China.
  • Xiangyi Song
    Department of Gastroenterology and Digestive Endoscopy Center, The Second Hospital of Jilin University, Chang Chun, Jilin, China.
  • Lijuan Wei
    Department of Gastroenterology and Digestive Endoscopy Center, The Second Hospital of Jilin University, Chang Chun, Jilin, China. ljwei@jlu.edu.cn.

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