嗜酸性食管炎诊断检测的进展：当前方法、局限性与新兴技术

文献信息

中文摘要

背景： 嗜酸性食管炎（EoE）是一种由异常2型（Th2）免疫反应引起的食管慢性疾病。它是儿童和成人吞咽困难的主要原因。内镜联合活检仍是诊断的标准方法，但其侵入性及需要重复操作促使人们研究替代和补充方法。方法：本叙述性综述综合了关于EoE诊断和疾病评估的既有和新兴模式的证据，包括微创采样技术、功能和结构评估、黏膜阻抗、分子诊断、基于组织的评估以及人工智能（AI）辅助方法。结果：微创方法可能有助于诊断或纵向监测，而补充模式可提供对疾病结构、功能、组织学和分子特征的评估。在回顾性图像数据集中，AI模型在自动嗜酸性粒细胞定量和内镜特征检测方面表现出高性能，但尚无一种在常规临床实践中得到前瞻性验证。结论：尽管有这些进展，由于成本、可及性以及在不同人群中验证的差异性，广泛采用仍然受限。需要进一步的前瞻性和外部验证来确定这些模式在主流实践中的作用。

英文摘要

Eosinophilic esophagitis (EoE) is a chronic disease of the esophagus caused by an abnormal type 2 (Th2) immune response. It is a leading cause of dysphagia in both pediatric and adult populations. Endoscopy with biopsy remains the standard approach for diagnosis, but its invasive nature and need for repeated procedures have prompted investigation of alternative and complementary approaches. A narrative review was conducted to synthesize evidence on established and emerging modalities for EoE diagnosis and disease assessment, including minimally invasive sampling techniques, functional and structural assessment, mucosal impedance, molecular diagnostics, tissue-based assessment, and artificial intelligence (AI)-assisted approaches. Minimally invasive approaches may facilitate diagnosis or longitudinal monitoring, while complementary modalities provide assessment of structural, functional, histologic, and molecular features of disease. In retrospective image datasets, AI models have demonstrated high performance for automated eosinophil quantification and detection f endoscopic features, although none has been prospectively validated in routine clinical practice. Despite these advances, widespread adoption remains limited by cost, accessibility, and variability in validation across diverse populations. Further prospective and external validation is needed to establish the role of these modalities in mainstream practice.