Abstract / Summary
Background/Objectives: 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. Methods: 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. Results: 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 of endoscopic features, although none has been prospectively validated in routine clinical practice. Conclusions: 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.