Background: Oesophageal, gastroesophageal, and gastric malignancies are often diagnosed at locally advanced stage and multimodal therapy is recommended to increase the chances of survival. However, given the significant variation in treatment response, there is a clear imperative to refine patient stratification. The aim of this narrative review was to explore the existing evidence and the potential of radiomics to improve staging and prediction of treatment response of oesogastric cancers. Methods: The references for this review article were identified via MEDLINE (PubMed) and Scopus searches with the terms “radiomics”, “texture analysis”, “oesophageal cancer”, “gastroesophageal junction cancer”, “oesophagogastric junction cancer”, “gastric cancer”, “stomach cancer”, “staging”, and “treatment response” until May 2024. Results: Radiomics proved to be effective in improving disease staging and prediction of treatment response for both oesophageal and gastric cancer with all imaging modalities (TC, MRI, and 18F-FDG PET/CT). The literature data on the application of radiomics to gastroesophageal junction cancer are very scarce. Radiomics models perform better when integrating different imaging modalities compared to a single radiology method and when combining clinical to radiomics features compared to only a radiomics signature. Conclusions: Radiomics shows potential in noninvasive staging and predicting response to preoperative therapy among patients with locally advanced oesogastric cancer. As a future perspective, the incorporation of molecular subgroup analysis to clinical and radiomic features may even increase the effectiveness of these predictive and prognostic models.
背景：食管、胃食管结合部及胃恶性肿瘤常在局部晚期阶段被诊断，推荐采用多模式治疗以提高生存机会。然而，鉴于治疗反应存在显著差异，优化患者分层显得尤为重要。本文旨在通过叙述性综述，探讨现有证据及影像组学在改善食管胃结合部癌分期与治疗反应预测方面的潜力。 方法：本综述通过MEDLINE（PubMed）和Scopus数据库检索截至2024年5月的文献，检索词包括“影像组学”“纹理分析”“食管癌”“胃食管结合部癌”“食管胃结合部癌”“胃癌”“分期”及“治疗反应”。 结果：研究表明，影像组学能有效提升食管癌和胃癌的分期准确性及治疗反应预测能力，且适用于所有影像学检查方法（CT、MRI和18F-FDG PET/CT）。目前关于影像组学在胃食管结合部癌中应用的文献数据仍非常有限。相较于单一影像学方法，整合不同影像模态的影像组学模型表现更优；与单纯使用影像组学特征相比，结合临床特征与影像组学特征能进一步提升模型性能。 结论：影像组学在局部晚期食管胃结合部癌的无创分期及术前治疗反应预测方面展现出潜力。未来，将分子亚组分析与临床及影像组学特征相结合，有望进一步提升这些预测和预后模型的有效性。
肿瘤(癌症)患者之家