Takahashi Kosuke, Ozawa Eisuke, Shimakura Akane, Mori Tomotaka, Miyaaki Hisamitsu, Nakao Kazuhiko
Department of Gastroenterology and Hepatology, Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki 852-8501, Japan.
Diagnostics (Basel). 2024 Feb 8;14(4):374. doi: 10.3390/diagnostics14040374.
Gallbladder (GB) disease is classified into two broad categories: GB wall-thickening and protuberant lesions, which include various lesions, such as adenomyomatosis, cholecystitis, GB polyps, and GB carcinoma. This review summarizes recent advances in the differential diagnosis of GB lesions, focusing primarily on endoscopic ultrasound (EUS) and related technologies. Fundamental B-mode EUS and contrast-enhanced harmonic EUS (CH-EUS) have been reported to be useful for the diagnosis of GB diseases because they can evaluate the thickening of the GB wall and protuberant lesions in detail. We also outline the current status of EUS-guided fine-needle aspiration (EUS-FNA) for GB lesions, as there have been scattered reports on EUS-FNA in recent years. Furthermore, artificial intelligence (AI) technologies, ranging from machine learning to deep learning, have become popular in healthcare for disease diagnosis, drug discovery, drug development, and patient risk identification. In this review, we outline the current status of AI in the diagnosis of GB.
胆囊(GB)疾病分为两大类:胆囊壁增厚和突出性病变,其中包括各种病变,如腺肌症、胆囊炎、胆囊息肉和胆囊癌。本综述总结了胆囊病变鉴别诊断的最新进展,主要聚焦于内镜超声(EUS)及相关技术。基础B型EUS和对比增强谐波EUS(CH-EUS)已被报道对胆囊疾病的诊断有用,因为它们可以详细评估胆囊壁增厚和突出性病变。我们还概述了EUS引导下细针穿刺抽吸(EUS-FNA)用于胆囊病变的现状,因为近年来关于EUS-FNA有一些零散的报道。此外,从机器学习到深度学习的人工智能(AI)技术在医疗保健领域已广泛应用于疾病诊断、药物发现、药物开发和患者风险识别。在本综述中,我们概述了AI在胆囊诊断中的现状。