谢传淼
专长
一、教育及工作经历
教育经历：
1988年至1994年 中山大学肿瘤防治中心 住院医师
1994年至2003年 中山大学肿瘤防治中心 主治医师
2003年至2011年 中山大学肿瘤防治中心 副主任医师
2011年至今 中山大学肿瘤防治中心 主任医师
学习经历：
1982.07—1986.07 中山医科大学 本科学士学位
1988.07—2001.07 中山大学 硕士研究生学位
2012.02-12 赴美国纽约哥伦比亚大学医疗中心放射科作访问学者
二、学术兼职
中华医学会放射学分会委员兼腹部学组副组长
中国医师协会放射医师分会第五届委员会委员
中国医师协会泌尿生殖学组副组长，对比剂学组副组长
中国抗癌协会肿瘤影像专业委员会副主任委员兼肿瘤影像专业委员会第一届青年俱乐部主任委员
中国研究型医院学会肿瘤影像专业委员会副主任委员
中国研究型医院学会磁共振专业委员会常务委员
广东省医学会肿瘤影像与大数据分会第一届主任委员
广东省抗癌协会肿瘤影像专业委员会名誉主任委员
广东省医学会放射学分会副主任委员
广东省医院协会医学影像中心管理专业委员会副主任委员
三、主持科研项目
科研方向为肿瘤影像人工智能辅助诊断。研究成果以第一/通讯作者（含共同）在Radiology、Neuro Oncology、Nature Communications等国际影像学期刊发表论文百余篇。主持国家级重点研发计划、国家自然科学基金面上项目、省级等课题十余项。主持多个国家重点研发计划项目、国家重点研发计划课题、国家自然科学基金面上项目。
四、代表性论著
在国内外期刊发表论文100余篇，其中SCI论文Radiology等50余篇。主编《头颈部疑难病例》，曾参与编写《临床肿瘤学》、《MRI临床医师必读》等
近五年代表性论著：
1. Zhang Y, Li J, Yang Q, et al. A clinically applicable AI system for detection and diagnosis of bone metastases using CT scans. Nat Commun. 2025;16(1):4444. Published 2025 May 13. doi:10.1038/s41467-025-59433-7
2. Zeng S, Yin S, Lian S, et al. A Clinical-Radiomic Combined Model based on Dual-Layer Spectral CT for Predicting Pathological T4 in Gastric Cancer. Acad Radiol. 2025;32(9):5242-5253. doi:10.1016/j.acra.2025.04.035
3. Luo X; Yang Y; Yin S; Li H; Shao Y; Zheng D; Li X; Li J; Fan W; Ban X; Lian S; Zhang Y; Zhang R; Xie C*. Automated segmentation of brain metastases with deep learning: A multi-center,randomized crossover, multi-reader evaluation study, neuro oncology, 2024, 26(11): 2140-2151
4. Geng Z, Wang S, Ma L, Zhang C, Guan Z, Zhang Y, Yin S, Lian S, Xie C. Prediction of microvascular invasion in hepatocellular carcinoma patients with MRI radiomics based on susceptibility weighted imaging and T2-weighted imaging. Radiol Med. 2024 Aug;129(8):1130-1142.
5. Ma L, Liao S, Yuan S, Li X, Zhang C, Zhou F, Geng Z, Xie C, Lu L, Xing K. Refining Risk Stratification in Hepatocellular Carcinoma by Integrating Tertiary Lymphoid Structures and Microvascular Invasion: A Multicenter Retrospective Study. Int J Surg. 2025 Jul 17.
6. Ma L, Liao S, Zhang X, Zhou F, Geng Z, Hu J, Zhang Y, Zhang C, Meng T, Wang S, Xie C. Application of Intravoxel Incoherent Motion in the Prediction of Intra-Tumoral Tertiary Lymphoid Structures in Hepatocellular Carcinoma. J Hepatocell Carcinoma. 2025 Feb 22;12:383-398.
7. Ma L, Zhang C, Wen Y, Xing K, Li S, Geng Z, Liao S, Yuan S, Li X, Zhong C, Hou J, Zhang J, Gao M, Xu B, Guo R, Wei W, Xie C, Lu L. Imaging-based surrogate classification for risk stratification of hepatocellular carcinoma with microvascular invasion to adjuvant hepatic arterial infusion chemotherapy: a multicenter retrospective study. Int J Surg. 2025 Jan 1;111(1):872-883.
8. Liao S, Zheng N, Li D, Liu C, Chen H, Cui M, Yu X, Xie C. Improved image quality and micronodule detection in thyroid spectral computed tomography using modified swimmer's position. Quant Imaging Med Surg. 2025 Feb 1;15(2):1571-1581.
9. He D, Liang H, Deng Y, et al. Modifying node-RADS in diagnosing parotid lymph node metastasis of nasopharyngeal carcinoma. Eur J Radiol. 2025;193:112451. doi:10.1016/j.ejrad.2025.112451
10. Xu G, Liu H, Ling D, Li Y, Lu N, Li X, Zhang Y, He H, Huang Z, Xie C. Acquisition and reconstruction with motion suppression DWI enhance image quality in nasopharyngeal carcinoma patients: Non-echo-planar DWI comparison with single-shot echo-planar DWI. Eur J Radiol. 2024 Dec;181:111752.
11. Zhang C, Ma LD, Zhang XL, Lei C, Yuan SS, Li JP, Geng ZJ, Li XM, Quan XY, Zheng C, Geng YY, Zhang J, Zheng QL, Hou J, Xie SY, Lu LH, Xie CM. Magnetic Resonance Deep Learning Radiomic Model Based on Distinct Metastatic Vascular Patterns for Evaluating Recurrence-Free Survival in Hepatocellular Carcinoma. J Magn Reson Imaging. 2024 Jul;60(1):231-242.
12. Ma L, Li C, Li H, Zhang C, Deng K, Zhang W, Xie C. Deep learning model based on contrast-enhanced MRI for predicting post-surgical survival in patients with hepatocellular carcinoma. Heliyon. 2024 May 16;10(11):e31451.
13. Su C, Peng C, Sun Y, Damen FC, Jiang R, Xie C, Cai K. Role of Histogram Features on Arterial Spin Labeling Perfusion Magnetic Resonance Imaging in Identifying Isocitrate Dehydrogenase Genotypes and Glioma Malignancies. Turk Neurosurg. 2024;34(4):578-587.
14. Zhang W, Lu N, He H, Liu H, Zhu F, Ma L, Luo Y, Qian L, Meng T, Xie C. Application of synthetic magnetic resonance imaging and DWI for evaluation of prognostic factors in cervical carcinoma: a prospective preliminary study. Br J Radiol. 2023 Jan 1;96(1141):20220596.
15. Ma L, Deng K, Zhang C, Li H, Luo Y, Yang Y, Li C, Li X, Geng Z, Xie C. Nomograms for Predicting Hepatocellular Carcinoma Recurrence and Overall Postoperative Patient Survival. Front Oncol. 2022 Feb 28;12:843589.
16. Zhang W, Lu N, He H, Liu H, Zhu F, Ma L, Luo Y, Qian L, Meng T, Xie C. Application of synthetic magnetic resonance imaging and DWI for evaluation of prognostic factors in cervical carcinoma: a prospective preliminary study. Br J Radiol. 2023 Jan 1;96(1141):20220596.
17. Liang J, Dai W, Li Z, Liang X, Xiao M, Xie C, Li X. Evaluating the efficacy and microenvironment changes of HER2 + gastric cancer during HLX02 and Endostar treatment using quantitative MRI. BMC Cancer. 2022 Oct 3;22(1):1033.
18. Yin S, Luo X, Yang Y, Shao Y, Ma L, Lin C, Yang Q, Wang D, Luo Y, Mai Z, Fan W, Zheng D, Li J, Cheng F, Zhang Y, Zhong X, Shen F, Shao G, Wu J, Sun Y, Luo H, Li C, Gao Y, Shen D, Zhang R, Xie C. Development and validation of a deep-learning model for detecting brain metastases on 3D post-contrast MRI: a multi-center multi-reader evaluation study. Neuro Oncol. 2022 Sep 1;24(9):1559-1570.
19. Luo X, Yang Y, Yin S, Li H, Zhang W, Xu G, Fan W, Zheng D, Li J, Shen D, Gao Y, Shao Y, Ban X, Li J, Lian S, Zhang C, Ma L, Lin C, Luo Y, Zhou F, Wang S, Sun Y, Zhang R, Xie C. False-negative and false-positive outcomes of computer aided detection on brain metastasis: secondary analysis of a multicenter, multireader study. Neuro Oncol. 2022 Aug 9:noac192.
20. Ban X, Hu H, Li Y, Yang L, Wang Y, Zhang R, Xie C, Zhou C, Duan X. Morphologic CT and MRI features of primary parotid squamous cell carcinoma and its predictive factors for differential diagnosis with mucoepidermoid carcinoma. Insights Imaging. 2022 Jul 15;13(1):119.
21. Ma L, Lian S, Liu H, Meng T, Zeng W, Zhong R, Zhong L, Xie C. Diagnostic performance of synthetic magnetic resonance imaging in the prognostic evaluation of rectal cancer. Quant Imaging Med Surg. 2022 Jul;12(7):3580-3591.
22. Yao J, Cao K, Hou Y, Zhou J, Xia Y, Nogues I, Song Q, Jiang H, Ye X, Lu J, Jin G, Lu H, Xie C, Zhang R, Xiao J, Liu Z, Gao F, Qi Y, Li X, Zheng Y, Lu L, Shi Y, Zhang L. Deep Learning for Fully Automated Prediction of Overall Survival in Patients Undergoing Resection for Pancreatic Cancer: A Retrospective Multicenter Study. Ann Surg. 2022 Jul 4.
23. Luo X, Xie H, Yang Y, Zhang C, Zhang Y, Li Y, Yang Q, Wang D, Luo Y, Mai Z, Xie C, Yin S. Radiomic Signatures for Predicting Receptor Status in Breast Cancer Brain Metastases. Front Oncol. 2022 Jun 6;12:878388.
24. Deng Y, Li C, Lv X, Xia W, Shen L, Jing B, Li B, Guo X, Sun Y, Xie C, Ke L. The contrast-enhanced MRI can be substituted by unenhanced MRI in identifying and automatically segmenting primary nasopharyngeal carcinoma with the aid of deep learning models: An exploratory study in large-scale population of endemic area. Comput Methods Programs Biomed. 2022 Apr;217:106702.
25. Lian S, Liu H, Meng T, Ma L, Zeng W, Xie C. Quantitative synthetic MRI for predicting locally advanced rectal cancer response to neoadjuvant chemoradiotherapy. Eur Radiol. 2023 Mar;33(3):1737-1745.
26. Ma L, Deng K, Zhang C, Li H, Luo Y, Yang Y, Li C, Li X, Geng Z, Xie C. Nomograms for Predicting Hepatocellular Carcinoma Recurrence and Overall Postoperative Patient Survival. Front Oncol. 2022 Feb 28;12:843589.
27. Lu N, Zhang WJ, Dong L, Chen JY, Zhu YL, Zhang SH, Fu JH, Yin SH, Li ZC, Xie CM. Dual-region radiomics signature: Integrating primary tumor and lymph node computed tomography features improves survival prediction in esophageal squamous cell cancer. Comput Methods Programs Biomed. 2021 Sep;208:106287.
28. Li X, Qi Z, Du H, Geng Z, Li Z, Qin S, Zhang X, Liang J, Zhang X, Liang W, Yang W, Xie C, Quan X. Deep convolutional neural network for preoperative prediction of microvascular invasion and clinical outcomes in patients with HCCs. Eur Radiol. 2022 Feb;32(2):771-782.
29. Meng T, He H, Liu H, Lv X, Huang C, Zhong L, Liu K, Qian L, Ke L, Xie C. Investigation of the feasibility of synthetic MRI in the differential diagnosis of non-keratinising nasopharyngeal carcinoma and benign hyperplasia using different contoured methods for delineation of the region of interest. Clin Radiol. 2021 Mar;76(3):238.e9-238.e15.
五、获奖及荣誉
曾获得湖北省科学技术奖三等奖，上海市科学技术奖二等奖，多次获得“岭南名医”荣誉称号。
更新时间：2026.4.3
