Shi YJ, Yan S, Yang X, Guan Z, Li XT, Wang LL, Dai L, Sun YS. Early Contrast-Enhanced MR for Diagnosing Complete Tumor Response of Locally Advanced Esophageal Squamous Cell Carcinoma After Neoadjuvant Therapy: A Retrospective Comparative Study,Ann Surg Oncol,2024;31(7):4271-4280.

Wei YY#, Cai JY#, Wang LL#, Yang J, Li YL, Li XT, Zhang XT*, Shi YJ*, Tang L*.Dynamic change in the peritoneal cancer index based on CT after chemotherapy in overall survival prediction of gastric cancer patients with peritoneal metastasis,J Cancer Res Clin Oncol,150(5):222

Yan S, Li FP, Jian L, Zhu HT, Zhao B, Li XT, Shi YJ, Sun YS. CT radiomics features of meso-esophageal fat in predicting overall survival of patients with locally advanced esophageal squamous cell carcinoma treated by definitive chemoradiotherapy,BMC Cancer,BMC Cancer. 2023 May 25;23(1):477. doi: 10.1186/s12885-023-10973-5.

Shi YJ, Zhu HT, Yan S, Li XT, Zhang XY, Sun YS. A CT-Based Radiomics Nomogram Model for Differentiating Primary Malignant Melanoma of the Esophagus from Esophageal Squamous Cell Carcinoma,Biomed Res Int,Biomed Res Int. 2023 Feb 20;2023:6057196. doi: 10.1155/2023/6057196. eCollection 2023.

Shi YJ, Zhu HT, Li XT, Zhang XY, Liu YL, Wei YY, Sun YS. Histogram array and convolutional neural network of DWI for differentiating pancreatic ductal adenocarcinomas from solid pseudopapillary neoplasms and neuroendocrine neoplasms,Clin Imaging,Clin Imaging. 2023 Apr;96:15-22. doi: 10.1016/j.clinimag.2023.01.008. Epub 2023 Jan 26.

Yan-Jie Shi#, Chang Liu#, Yi-Yuan Wei1#, Xiao-Ting Li, Lin Shen*, Zhi-Hao Lu* and Ying-Shi Sun* .Quantitative CT analysis to predict esophageal fistula in patients with advanced esophageal cancer treated by chemotherapy or chemoradiotherapy.,cancer imaging,2022, 22:62

Yan S (#), Shi YJ (#), Liu C, Li XT, Zhao B, Wei YY, Shen L, Lu ZH, Sun YS＊.Quantitative CT evaluation after two cycles of induction chemotherapy to predict prognosis of patients with locally advanced oesophageal squamous cell carcinoma before undergoing definitive chemoradiotherapy/radiotherapy.,European Radiology,2023,33(1): 380-390.

Shi YJ #, Liu BN #, Li XT, Zhu HT, Wei YY, Zhao B, Sun SS, Sun YS*, Hao CY*. Establishment of a multi-parameters MRI model for predicting small lymph nodes metastases ( <10 mm) in patients with resected pancreatic ductal adenocarcinoma.,Abdom Radiol (NY) .,2022 ;47(9):3217-3228.

Shi YJ #, Yang X #, Yan S #, Li XT, Wei YY, Zhang XY, Sun YS. Primary malignant melanoma of the esophagus: differentiation from esophageal squamous cell carcinoma and leiomyoma using dynamic contrast-enhanced CT findings.,Abdom Radiol (NY) .,2022;47（8）:2747–2759

Shi YJ #, Zhu HT #, Li XT, Zhang XY, Wei YY, Yan S, Sun YS *. Radiomics analysis based on multiple parameters MR imaging in the spine: Predicting treatment response of osteolytic bone metastases to chemotherapy in breast cancer patients.,Magn Reson Imaging .,. 2022;92:10-18.

Yan-Jie Shi(#), Hai-Tao Zhu（#）, Yu Liang Liu(#), Xiao-Yan Zhang, Xiao-Ting Li, Ying-Shi Sun*. Radiomics Analysis Based on Diffusion Kurtosis Imaging and T2 Weighted Imaging for Differentiation of Pancreatic Neuroendocrine Tumors From Solid Pseudopapillary Tumors.,Frontiers in Oncology,2020, 10:1624.

Zhang XY #, Li XT #, Shi YJ #, Lu QY #, Cao W #, Zhang HM, Wang L, Zhu HT, Yu T, Guan Z, Sun RJ, Zhu HB, Wu AW, Sun YS*. Correlation Between the Distance to Mesorectal Fascia and Prognosis of cT3 Rectal Cancer: Results of a Multicenter Study From China.,Dis Colon Rectum,2022 Mar 1;65(3):322-332.

Yan-Jie Shi #, Xiao-Ting Li #, Xiao-Yan Zhang, Hai-Tao Zhu, Yu-Liang Liu, Yi-Yuan Wei, Ying-Shi Sun*. Non-gaussian models of 3-Tesla diffusion-weighted MRI for the differentiation of pancreatic ductal adenocarcinomas from neuroendocrine tumors and solid pseudopapillary neoplasms,Magn Reson Imaging .,2021;83:68-76.

基于影像组学的胃癌腹膜转移疗效评估的人工智能模型., 子课题负责人, 2020.10.1～2024.12.1, 北京市自然科学基金-重点研究专题

构建高分辨MRI影像组学模型早期预测与精确诊断局部进展期食管鳞癌放化疗联合免疫治疗继发食管瘘的前瞻性临床研究., 课题负责人, 2021.1.1～2023.12.31, 北京市属医院科研培育项目

研究生招生计划

招生年度	招生专业	学位级别	学位类型	研究方向	选拔方式	操作
2026	放射影像学	硕士	专业学位	临床技能训练与研究	推荐免试