局部进展期胃癌约占所有胃癌的75%，手术切除肿瘤是首选治疗方式，但存在术后复发率高和总体生存率低的临床预后难题。准确评价局部进展期胃癌手术预后可指导临床决策，但目前基于临床病理指标的方法尚不能准确预测预后。申请人和国外研究团队的研究证实，使用影像组学方法，挖掘蕴含于肿瘤影像中的深层特征，可用于肿瘤患者的疗效评价和预后预测，为进展期胃癌手术后的预后预测提供了新思路。本项目拟：1、基于影像组学技术，挖掘并筛选胃癌影像中的与预后高度关联的影像组学特征，组成影像组学特征标签；2、检测并量化胃癌预后相关分子标志物的表达；3、融合影像组学特征标签、预后相关分子靶向标志物和常规临床病理指标，构建并验证预后预测模型，对局部进展期胃癌预后进行个体化预测。本研究的结果，将为临床医师预测局部进展期胃癌手术切除后的预后结局提供辅助工具，对患者进行个体化预后预测，指导临床决策。

Local advanced gastric cancer accounts for about 75% of all gastric cancers. Although surgical resection is the preferred treatment option for local advanced gastric cancer patients, they encountered with high recurrence rate and low overall survival rate. Therefore, precise evaluation of the clinical outcome for local advanced gastric cancer patients following surgical removal can aid in decision-making, however, the current method based on clinical pathological indicators cannot accurately predict the prognosis. Our previous research and other researchers' results indicated that radiomics can extracted imaging feature from the medical imaging of the tumors to decode the clinical information including treatment evaluation and prognosis prediction for local advanced gastric cancer. This project is to: (1) extract and select the key radiomics features from the gastric cancer imaging, which is highly associated with the prognosis of the patients; (2) investigate and quantify the molecular markers related to the prognosis of gastric cancer; (3) integrate radiomics features, clinical and pathological variables, and molecular markers to build the prognostic prediction model for local advanced gastric cancer, and the prediction model will be validated. The results of this project will provide an adjunct tool for clinicians to individualized predict the prognosis of local advanced gastric cancer after surgical resection, which will aid in clinical decision-making in precise medicine for the patient management.