Ultrasound-based artificial intelligence in gastroenterology and hepatology.

Ji-Qiao Liu, Jia-Yu Ren, Xiao-Lan Xu, Li-Yan Xiong, Yue-Xiang Peng, Xiao-Fang Pan, Christoph F Dietrich, Xin-Wu Cui

Journal: World journal of gastroenterology 2022;28(38):5530-5546

PMID: 36304086

Abstract

Artificial intelligence (AI), especially deep learning, is gaining extensive attention for its excellent performance in medical image analysis. It can automatically make a quantitative assessment of complex medical images and help doctors to make more accurate diagnoses. In recent years, AI based on ultrasound has been shown to be very helpful in diffuse liver diseases and focal liver lesions, such as analyzing the severity of nonalcoholic fatty liver and the stage of liver fibrosis, identifying benign and malignant liver lesions, predicting the microvascular invasion of hepatocellular carcinoma, curative transarterial chemoembolization effect, and prognoses after thermal ablation. Moreover, AI based on endoscopic ultrasonography has been applied in some gastrointestinal diseases, such as distinguishing gastric mesenchymal tumors, detection of pancreatic cancer and intraductal papillary mucinous neoplasms, and predicting the preoperative tumor deposits in rectal cancer. This review focused on the basic technical knowledge about AI and the clinical application of AI in ultrasound of liver and gastroenterology diseases. Lastly, we discuss the challenges and future perspectives of AI.

©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.

Address: Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China.; Department of Ultrasound, Wuhan Third Hospital, Tongren Hospital of Wuhan University, Wuhan 430030, Hubei Province, China.; Health Medical Department, Dalian Municipal Central Hospital, Dalian 116000, Liaoning Province, China.; Department Allgemeine Innere Medizin, Kliniken Hirslanden Beau Site, Salem und Permanence, Bern 3003, Switzerland.; Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China. [email protected].
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