科研项目
1、舒震宇。基于多参数MRI影像组学建立局部进展期直肠癌新辅助治疗疗效精准预测模型及临床价值评估，浙江省基础公益研究计划，面上项，LGF21H180013
2、林春苗。基于磁共振多参数成像及影像组学预测术前肝细胞肝癌微血管浸润的研究，浙江省医药卫生科技计划项目，面上B类，2021KY442
3、钟建国。基于SVM的多模态磁共振影像组学联合血清学指标构建胰腺癌术后肝转移预测模型的研究，浙江省医药卫生科技计划项目，面上B类，2021KY465
4、陈军法。基于MR影像组学精准预测凶险性前置胎盘剖宫术中出血量的研究，浙江省医药卫生科技计划项目面上，B类，2021KY508
5、邵园。基于影像组学评估大脑皮层下微结构改变构建正常脑衰老诊断模型，浙江省医药卫生科技计划项目面上，A类，2021KY067
6、徐健。形态学联合流固耦合数值模拟技术对腹主动脉破裂风险的评估研究，浙江省医药卫生科技计划项目面上，B类，2021KY474
7、俞亮。新冠疫情后国家紧急医学救援队影像配置优化设想，浙江省教育厅课题，Y202044785
8、管政。COVID-19疫情下方舱移动CT影像检查及规范体会，浙江省教育厅课题，Y202044780
科研论文
1. Shu ZY, Cui SJ, Zhang YQ, Xu YY, Hung SC, Fu LP, Pang PP, Gong XY*, Jin QY. Predicting Chronic Myocardial Ischemia Using CCTA-Based Radiomics Machine Learning Nomogram. J Nucl Cardiol. 2020 Jun 18. doi: 10.1007/s12350-020-02204-2. Epub ahead of print. PMID: 32557238. 【3.366】
2. Shu Z, Xu Y*, Shao Y, Pang P, Gong X*. Radiomics from magnetic resonance imaging may be used to predict the progression of white matter hyperintensities and identify associated risk factors. Eur Radiol. 2020 Jun;30(6):3046-3058. doi: 10.1007/s00330-020-06676-1. Epub 2020 Feb 21. PMID: 32086580. 【4.101】
3. Tang Z, Xu Y, Jin L, Aibaidula A, Lu J, Jiao Z, Wu J, Zhang H, Shen D. Deep Learning of Imaging Phenotype and Genotype for Predicting Overall Survival Time of Glioblastoma Patients. IEEE Trans Med Imaging. 2020 Jun;39(6):2100-2109. doi: 10.1109/TMI.2020.2964310. Epub 2020 Jan 6. PMID: 31905135; PMCID: PMC7289674. 【6.685】
4. Wei Yang, Qin Ye, Shuai Ming , Xingfei Hu, Zhiqiang Jiang, Qiang Shen, Linyang He, Xiangyang Gong*. Feasibility of automatic measurements of hip joints based on pelvic radiography and a deep learning algorithm. European Journal of Radiology. 132 (2020) 109303, https://doi.org/10.1016/j.ejrad.2020.109303 【2.687】
5. Wen X, Li Y, He X, Xu Y*, Shu Z, Hu X, Chen J, Jiang H, Gong X*. Prediction of Malignant Acute Middle Cerebral Artery Infarction via Computed Tomography Radiomics. Front Neurosci. 2020 Jul 7;14:708. doi: 10.3389/fnins.2020.00708. eCollection 2020.【3.707】
6. Sijia Cui, Shuai Ming, Yi Lin, Fanghong Chen, Qiang Shen, Hui Li, Gen Chen, Xiangyang Gong*, Haochu Wang*. Development and clinical application of deep learning model for lung nodules screening on CT images. Sci Rep. 2020 Aug 12;10(1):13657. doi: 10.1038/s41598-020-70629-3. PMID: 32788705【3.998】
7. Ye Q, Shen Q, Yang W, Huang S, Jiang Z, He L, Gong XY*. Development of automatic measurement for patellar height based on deep learning and knee radiographs. Eur Radiol. 2020 Sep;30(9):4974-4984. PMID: 32328760 DOI: 10.1007/s00330-020-06856-z. Epub 2020 Apr 23.【4.101】
8. Cui SJ, Tang TY, Zou XW, Su QM, Feng L, Gong XY*. Role of imaging biomarkers for prognostic prediction in patients with pancreatic ductal adenocarcinoma. Clin Radiol. 2020 Jun;75(6):478.e1-478.e11. doi: 10.1016/j.crad.2019.12.023. Epub 2020 Feb 6【2.118】
9. Shu ZY, Cui SJ, Wu X, Xu Y, Huang P, Pang PP, Zhang M. Predicting the progression of Parkinson's disease using conventional MRI and machine learning: An application of radiomic biomarkers in whole-brain white matter. Magn Reson Med. 2021 Mar;85(3):1611-1624. doi: 10.1002/mrm.28522. Epub 2020 Oct 5. PMID: 33017475. 【3.635】
10. Fu L, Li Y, Cheng A, Pang P, Shu Z*. A Novel Machine Learning-derived Radiomic Signature of the Whole Lung Differentiates Stable From Progressive COVID-19 Infection: A Retrospective Cohort Study. J Thorac Imaging. 2020 Jun 16;35(6):361–8. doi: 10.1097/RTI.0000000000000544. Epub ahead of print. PMID: 32555006; PMCID: PMC7682797. 【2.19】
11. Yu T, Lin C, Li X, Quan X. Renal Cell Carcinoma: Predicting DNA Methylation Subtyping and Its Consequences on Overall Survival With Computed Tomography Imaging Characteristics. J Comput Assist Tomogr. 2020 Sep/Oct;44(5):737-743. doi: 10.1097/RCT.0000000000001077. PMID: 32842065. 【1.285】
12. Cao F, Guan X, Ma Y, Shao Y, Zhong J*. Altered Functional Network Associated With Cognitive Performance in Early Parkinson Disease Measured by Eigenvector Centrality Mapping. Front Aging Neurosci. 2020 Oct 16;12:554660. doi: 10.3389/fnagi.2020.554660. PMID: 33178007; PMCID: PMC7596167. 【4.362】
13. Meng L, Zhang LJ, Fang SH. Pancreatic neuroendocrine neoplasms: a correlative study of imaging characteristics and histological grade. International Journal of Clinical And Experimental Medicine. 13(6):4535-4543. 【0.166】
14. Ma Y, Cao F, Xu X, Ma W. Can whole-tumor radiomics-based CT analysis better differentiate fat-poor angiomyolipoma from clear cell renal cell caricinoma: compared with conventional CT analysis? Abdom Radiol (NY). 2020 Aug;45(8):2500-2507. doi: 10.1007/s00261-020-02414-9. PMID: 31980867. 【2.429】
15. Ma Y, Ma W, Xu X, Cao F. How Does the Delta-Radiomics Better Differentiate Pre-Invasive GGNs From Invasive GGNs? Front Oncol. 2020 Jul 16;10:1017. doi: 10.3389/fonc.2020.01017. PMID: 32766129; PMCID: PMC7378390. 【4.848】
16. Xu J, Wang X, Yang P, Luo K, He X. Size-Specific Dose Estimates of Radiation Based on Body Weight and Body Mass Index for Chest and Abdomen-Pelvic CTs. Biomed Res Int. 2020 Jul 10;2020:6046501. doi: 10.1155/2020/6046501. PMID: 32733946; PMCID: PMC7369680. 【2.276】
17. Wen Y, Zhao M, Huang W, Fang S, Lin C*. Idiopathic mesenteric phlebosclerosis associated with use of Chinese herbal medicine: Two case reports. Medicine (Baltimore). 2020 Oct 16;99(42):e22813. doi: 10.1097/MD.0000000000022813. PMID: 33080758; PMCID: PMC7571907. 【1.552】
18. Wen Y, Chen W, Chen J, He X*. Retroperitoneal bronchogenic cyst resembling an adrenal tumor: two case reports and literature review. J Int Med Res. 2020 May;48(5):300060520925673. doi: 10.1177/0300060520925673. PMID: 32436418; PMCID: PMC7243399. 【1.287】
19. Sun X, Pang P, Lou L, Feng Q, Ding Z, Zhou J. Radiomic prediction models for the level of Ki-67 and p53 in glioma. J Int Med Res. 2020 May;48(5):300060520914466. doi: 10.1177/0300060520914466. PMID: 32431205; PMCID: PMC7241212. 【1.35】
20. 林春苗,陈军法,文阳,余苔痕,徐健.CT纹理分析对局部晚期胰腺癌化疗疗效的预测价值[J]. 浙江医学,2020,42(12):1282-1285 +1289 +1345.
21. 徐健,王相权,杨盼峰,谢叶雷,罗匡男,毛德旺.基于体重和体质量指数计算腹盆CT体型特异性剂量估算值的可行性[J]. 中华放射医学与防护杂志, 2020,40(07):549-553.
22. 何小龙,徐健,祝峰,吕颖果,罗匡男.前置体型特异性剂量估算值优化CT冠状动脉成像的可行性[J]. 中华放射医学与防护杂志, 2020,40(09):717-721.
23. 徐健,肖华伟,王相权,张玉江,陈福华,李玉梅.320排CT动态血管成像联合双时相CTA对颅底脑膜瘤术前评估[J]. 医学影像学杂志, 2020,30(02):178-181.
24. 徐玉芸,何晓东,余苔痕,李杰.基于CCTA的影像组学列线图用于慢性心肌缺血预测的构建与价值[J]. 心电与循环, 2020,39(05):442-448 +452 +521.
25. 徐建国,宋侨伟,沈莹,舒震宇.基于机器学习的大脑白质影像组学标签识别帕金森病早期阶段的应用研究[J]. 浙江医学, 2020,42(18):1954-1959 +1964.
26. 郑小丽,徐健,王振,舒震宇,毛德旺.层面组织结构含量与SSDE在腹盆部CT扫描中的相关性研究[J]. 医学影像学杂志, 2020,30(02):284-287.
27. 肖华伟,徐健,王相权,郑小丽.CT动态血管成像术前评估脑膜瘤[J].中国介入影像与治疗学, 2020,17(06):351-354.
28. 黄帅,邵园,明帅,杨巍,叶琴,崔思嘉,龚向阳.颅骨直接穿刺单次注血制作脑表面铁质沉积模型的可行性研究[J]. 放射学实践, 2020,35(04):447-451.
著作
1. 龚向阳、王振主译。《肝脏影像诊断图谱》，科学出版社，2020年11月出版，44.5万字。
2. 龚向阳、王振主译。《胆胰脾影像诊断图谱》，科学出版社，2020年11月出版，43.8万字。
3. 龚向阳、何波主编。《运动医学影像诊断学膝关节分册》，科学出版社，2020年12月出版，45.3万字。
继教学习班
国家级继教项目《放射科诊疗安全和持续质量改进》