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.

中文翻译：

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胃上皮下肿瘤的诊断进展。

上皮下肿瘤 (SETs) 的诊断有时很困难，因为病变上存在覆盖的黏膜，这阻碍了通过常规内窥镜检查和使用标准活检钳进行组织取样的光学诊断。通过使用计算机断层扫描和超声内镜 (EUS) 的成像方式是强制性的，以无创地收集目标的信息并选择候选者进行进一步评估。特别是 EUS 是一种不可或缺的诊断方式，用于精确评估病变和评估恶性肿瘤的可能性。EUS 的诊断能力似乎随着对比增强或弹性成像的联合使用而增加。组织学是获得最终诊断的金标准。组织取样需要特殊技术来打破粘膜屏障。虽然 EUS 引导的细针穿刺 (EUS-FNA) 是常用的，但黏膜切割活检和黏膜切开辅助活检是从病变暴露表面明确获取组织的可比方法，并且对于小型 SET 似乎比 EUS-FNA 更有用. 人工智能 (AI) 的最新进展有可能彻底改变 SET 的诊断策略。包括人工智能辅助诊断在内的非侵入性方法的开发和建立有望为侵入性组织学诊断提供替代方案。人工智能 (AI) 的最新进展有可能彻底改变 SET 的诊断策略。包括人工智能辅助诊断在内的非侵入性方法的开发和建立有望为侵入性组织学诊断提供替代方案。人工智能 (AI) 的最新进展有可能彻底改变 SET 的诊断策略。包括人工智能辅助诊断在内的非侵入性方法的开发和建立有望为侵入性组织学诊断提供替代方案。