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中国医科大学第四临床学院放射科党支部书记、放射科主任。教授、主任医师、博士生导师。先后主持/负责各级课题8项,含国家自然基金项目3项,近五年以通讯作者或并列通讯作者发表SCI论文19篇,最高IF值19.7分,总IF分值超过100分。参编国家级规划教材4部;副主编及参编著作各2部。任中华放射学会青委、乳腺学组委员;中国抗癌协会肿瘤影像专委会委员;中国放射医师分会乳腺学组委员,辽宁省医师协会副会长,沈阳市放射学会主委、辽宁省生命科学学会放射学分会主委等。培养研究生共计17人,学术学位6人,专业学位11人,2019级研究生获评中国医科大学校级优秀论文、辽宁省优秀论文;2020级研究生获评中国医科大学优秀毕业生。
近五年:
2015-2020已结题:科技部重大专项 1项(参与单位负责人,60万),所属专项:重大慢性非传染性疾病防控研究,所属项目:基于分子影像和影像组学的乳腺癌早诊、疗效评价与预后预测新技术研发,项目编号:2017YFC1309100
2020-2023已结题: 国家自然科学基金面上项目 1项(负责人,55万),项目名称:多模态MRI影像组学模型对乳腺癌新辅助治疗疗效的早期预判研究,项目编号:81971695
2022-2024在研: 辽宁省应用基础研究1项(负责人,30万),项目名称:构建基于弛豫定量技术的无造影剂MRI影像模型实现乳腺癌新辅助治疗疗效的早期预测,项目编号:2022JH2/101300027
2024-2027在研: 国家自然科学基金面上项目 1项(负责人,60万),项目名称:肿瘤微环境关键细胞标记的影像病理组学模型对乳腺癌新辅助治疗疗效的早期分层预判研究,项目编号:82371947
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支持扩展名:.rar .zip .doc .docx .pdf .jpg .png .jpeg近五年:
2015-2020:科技部重大专项 1项(参与单位负责人,60万),所属专项:重大慢性非传染性疾病防控研究,所属项目:基于分子影像和影像组学的乳腺癌早诊、疗效评价与预后预测新技术研发,项目编号:2017YFC1309100
2020-2023: 国家自然科学基金面上项目 1项(负责人,55万),项目名称:多模态MRI影像组学模型对乳腺癌新辅助治疗疗效的早期预判研究,项目编号:81971695
2022-2024: 辽宁省应用基础研究1项(负责人,30万),项目名称:构建基于弛豫定量技术的无造影剂MRI影像模型实现乳腺癌新辅助治疗疗效的早期预测,项目编号:2022JH2/101300027
2024-2027: 国家自然科学基金面上项目 1项(负责人,60万),项目名称:肿瘤微环境关键细胞标记的影像病理组学模型对乳腺癌新辅助治疗疗效的早期分层预判研究,项目编号:82371947
发表论文
1.Siyao Du, Si Gao, Mengfan Wang, Lina Zhang*. Multiparametric MRI Radiomics for the Identification of HER2-Low Breast Cancers. Radiology. 2024 Jan;310(1):e232092.
2.Mengfan Wang # , Siyao Du # , Si Gao , Ruimeng Zhao , Shasha Liu , Wenhong Jiang , Can Peng , Ruimei Chai , Lina Zhang*. MRI-based tumor shrinkage patterns after early neoadjuvant therapy in breast cancer: correlation with molecular subtypes and pathological response after therapy. Breast Cancer Res. 2024 Feb 12;26(1):26.
3.Guoliang Huang #, Siyao Du #, Si Gao , Liangcun Guo , Ruimeng Zhao , Xiaoqian Bian , Lizhi Xie , Lina Zhang*. Molecular subtypes of breast cancer identified by dynamically enhanced MRI radiomics: the delayed phase cannot be ignored. Insights Imaging. 2024 May 31;15(1):127.
4.Wenhong Jiang #, Siyao Du #, Si Gao , Lizhi Xie , Zichuan Xie , Mengfan Wang , Can Peng , Jing Shi *, Lina Zhang*. Correlation between synthetic MRI relaxometry and apparent diffusion coefficient in breast cancer subtypes with different neoadjuvant therapy response. Insights Imaging. 2023 Sep 29;14(1):162.
5.Xiaoqian Bian#, Siyao Du#, Zhibin Yue#, Si Gao, Ruimeng Zhao, Guoliang Huang, Liangcun Guo, Can Peng, Lina Zhang*. Potential antihuman epidermal growth factor receptor 2 target therapy beneficiaries: the role of MRI-based radiomics in distinguishing human epidermal growth factor receptor 2-low status of breast cancer. J Magn Reson Imaging. 2023 Nov;58(5):1603-1614.
6.Ruimeng Zhao#, Siyao Du#, Si Gao, Jing Shi*, Lina Zhang*. Time course changes of synthetic relaxation time during neoadjuvant chemotherapy in breast cancer: the optimal parameter for treatment response evaluation. J Magn Reson Imaging. 2023 Oct;58(4):1290-1302.
7.Shasha Liu#, Siyao Du#, Si Gao, Yuee Teng, Feng Jin*, Lina Zhang*. A delta-radiomic lymph node model using dynamic contrast enhanced MRI for the early prediction of axillary response after neoadjuvant chemotherapy in breast cancer patients. BMC Cancer 2023;23(1):15.
8.Siyao Du, Si Gao, Ruimeng Zhao, Hongbo Liu, Yan Wang, Xixun Qi, Shu Li, Jibin Cao, Lina Zhang*. Contrast-free MRI quantitative parameters for early prediction of pathological response to neoadjuvant chemotherapy in breast cancer. European radiology 2022;32(8):5759-5772.
9.Liangcun Guo#, Siyao Du#, Si Gao, Ruimeng Zhao, Guoliang Huang, Feng Jin, Yuee Teng*, Lina Zhang*. Delta-radiomics based on dynamic contrast-enhanced MRI predicts pathologic complete response in breast cancer patients treated with neoadjuvant chemotherapy. Cancers 2022;14(14).
10.Duo Hong, Lina Zhang*, Ke Xu*, Xiaoting Wan, Yan Guo. Prognostic value of pre-treatment CT radiomics and clinical factors for the overall survival of advanced (IIIB-IV) lung adenocarcinoma patients. Front Oncol 2021;11:628982.
11.Siyao Du, Si Gao, Lina Zhang*, Xiaoping Yang, Xixun Qi, Shu Li. Improved discrimination of molecular subtypes in invasive breast cancer: Comparison of multiple quantitative parameters from breast MRI. Magnetic resonance imaging 2021;77:148-158.
12.Mengshi Dong, Gang Hou, Shu Li, Nan Li, Lina Zhang*, Ke Xu*. Preoperatively estimating the malignant potential of mediastinal lymph nodes: a pilot study toward establishing a robust radiomics model based on contrast-enhanced CT imaging. Front Oncol 2020;10:558428.
13.Xiaoping Yang, Mengshi Dong, Shu Li, Ruimei Chai, Zheng Zhang, Nan Li, Lina Zhang*. Diffusion-weighted imaging or dynamic contrast-enhanced curve: a retrospective analysis of contrast-enhanced magnetic resonance imaging-based differential diagnoses of benign and malignant breast lesions. European radiology 2020;30(9):4795-4805.
14.Quan Cai#, Siyao Du#, Si Gao#, Guoliang Huang#, Zheng Zhang, Shu Li, Xin Wang, Peiling Li, Peng Lv, Gang Hou, Lina Zhang*. A model based on CT radiomic features for predicting RT-PCR becoming negative in coronavirus disease 2019 (COVID-19) patients. BMC Med Imaging 2020;20(1):118.
15.Siyao Du#, Si Gao#, Guoliang Huang, Shu Li, Wei Chong, Ziyi Jia, Gang Hou, Yi Xiang J. Wang, Lina Zhang*. Chest lesion CT radiological features and quantitative analysis in RT-PCR turned negative and clinical symptoms resolved COVID-19 patients. Quant Imaging Med Surg 2020;10(6):1307-1317.
16.Duo Hong, Ke Xu*, Lina Zhang*, Xiaoting Wan, Yan Guo. Radiomics signature as a predictive factor for EGFR mutations in advanced lung adenocarcinoma. Front Oncol 2020;10:28.
17.Ting Luo#, Ke Xu#, Zheng Zhang, Lina Zhang*, Shandong Wu. Radiomic features from computed tomography to differentiate invasive pulmonary adenocarcinomas from non-invasive pulmonary adenocarcinomas appearing as part-solid ground-glass nodules. Chin J Cancer Res 2019;31(2):329-338.
18.Mengshi Dong#, Likun Xia#, Min Lu, Chao Li, Ke Xu*, Lina Zhang*. A failed top-down control from the prefrontal cortex to the amygdala in generalized anxiety disorder: Evidence from resting-state fMRI with Granger causality analysis. Neurosci Lett 2019;707:134314.
19.Bin Hu#, Ke Xu#, Zheng Zhang, Ruimei Chai, Shu Li, Lina Zhang*. A radiomic nomogram based on an apparent diffusion coefficient map for differential diagnosis of suspicious breast findings. Chin J Cancer Res 2018;30(4):432-438.
2019年12月辽宁省科学技术进步奖 二等奖
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