Advancements in the Diagnosis of Gastric Subepithelial Tumors

• Published in: Gut and liver Vol. 16; no. 3; pp. 321 - 330
• Main Authors: Goto, Osamu, Kaise, Mitsuru, Iwakiri, Katsuhiko
• Format: Journal Article
• Language: English
• Published: Korea (South) Editorial Office of Gut and Liver 01.05.2022; Gastroenterology Council for Gut and Liver; 거트앤리버 소화기연관학회협의회
• Subjects: endosonography; gastrointestinal stromal tumor; Review; subepithelial tumor; 내과학; Endosonography; Subepithelial tumor; Gastrointestinal stromal tumor
• ISSN: 1976-2283; 2005-1212
• DOI: 10.5009/gnl210242

A diagnosis of subepithelial tumors (SETs) is sometimes difficult due to the existence of overlying mucosa on the lesions, which hampers optical diagnosis by conventional endoscopy and tissue sampling with standard biopsy forceps. Imaging modalities, by using computed tomography and endoscopic ultrasonography (EUS) are mandatory to noninvasively collect the target's information and to opt candidates for further evaluation. Particularly, EUS is an indispensable diagnostic modality for assessing the lesions precisely and evaluating the possibility of malignancy. The diagnostic ability of EUS appears increased by the combined use of contrast-enhancement or elastography. Histology is the gold standard for obtaining the final diagnosis. Tissue sampling requires special techniques to break the mucosal barrier. Although EUS-guided fine-needle aspiration (EUS-FNA) is commonly applied, mucosal cutting biopsy and mucosal incision-assisted biopsy are comparable methods to definitively obtain tissues from the exposed surface of lesions and seem more useful than EUS-FNA for small SETs. Recent advancements in artificial intelligence (AI) have a potential to drastically change the diagnostic strategy for SETs. Development and establishment of noninvasive methods including AI-assisted diagnosis are expected to provide an alternative to invasive, histological diagnosis.