摘要越来越多的研究结果表明，肿瘤微环境对胰腺癌的生物学行为有重要影响。作为肿瘤微环境的重要组成部分，肿瘤间质在胰腺癌发生发展及化疗耐药中发挥重要作用。肿瘤间质比可间接反映肿瘤细胞与微环境的关系，近年来日益受到重视。目前，很多研究结果显示，肿瘤间质比低是可切除胰腺癌预后的保护因素，且此部分患者更适合吉西他滨和白蛋白结合型紫杉醇联合用药的化疗方案，但该结果尚无定论，距离指导精准治疗仍有差距，需进一步研究探索。在传统病理学和影像学评估的基础上，加入人工智能深度学习模型，有助于实现对肿瘤间质比的精准评价，并基于这一指标对胰腺癌患者进行分层和精准诊疗。

abstractsAn increasing number of studies suggested that the tumor microenvironment exerts a substantial influence on the pathophysiology of pancreatic cancer. As a crucial component of the tumor microenvironment,the tumor stroma plays a pivotal role in the occurrence,development,and chemotherapy resistance of pancreatic cancer. By serving as a proxy for the interaction between tumor cells and the microenvironment,the tumor stroma ratio(TSR) has emerged as a focal point of investigation in recent years. At present,numerous studies show that a low TSR is a protective factor for the prognosis of resectable pancreatic cancer. Additionally, patients with a low TSR are more suitable for the gemcitabine and albumin-bound paclitaxel chemotherapy regimen. But these researches are not conclusive, and there is still a gap between guiding precision treatment. Further research and exploration are required. Integration of artificial intelligence deep learning models into traditional pathological and imaging assessments facilitates precise evaluation of the TSR. It can also enable stratification and precision treatment of pancreatic cancer patients based on this index.