主持课题

1、肿瘤相关抗原芯片在筛选肺癌自身抗体谱中的应用；经费来源：院所基本科研业务费

2、CT定量分析对早期肺腺癌术前分型的应用研究；经费来源：中央高校基本科研业务费/协和青年基金

3、定量影像学作为生物标记物在早期肺腺癌中的应用研究，经费来源：国家自然科学基金

参与课题

1、来源：国家重点研发计划，名称：肺癌筛查和干预技术及方案研究

2、来源：国家自然科学基金面上项目， 名称：Ⅰ期肺腺癌术后复发转移相关的影像组学及基因组学预后标志物研究

3、来源：北京协和医学院协和青年科研基金，名称：影像组学对肺亚实性结节生长预测的研究

4、来源：北京市科技计划，名称：早期肺癌筛查和影像学诊断研究

5、来源：院所科研课题，名称：肺多发磨玻璃结节HRCT表现与病理学对照研究

6、来源：国家自然科学基金面上项目，名称：惰性生长方式肺腺癌自然生长规律的初步观察及病理基础研究

1. 李蒙, 路晓东, 刘吉华. 两岁男孩原发性肝细胞癌1例报告[J]. 实用医学影像杂志, 2006, 7 (1): 53-54.

2. 李蒙, 吴宁, 林冬梅, 罗德红, 戴景蕊, 周纯武. 炎性肌纤维母细胞瘤的多层螺旋CT表现[J]. 中国医学影像技术, 2008, 24 (12): 1995-1998.

3. 李蒙, 吴宁. PET/CT在肺癌分期中的应用[J]. 国际医学放射学杂志, 2008, 31 (6): 449-452.

4. 李蒙, 吴宁, 梁颖, 郑容, 刘瑛, 张雯杰, 赵平. 18F-FDG PET-CT在非小细胞肺癌术前区域淋巴结分期中的价值[J]. 中华肿瘤杂志, 2009, 31 (4): 288-292.

5. 李蒙, 吴宁, 郑容, 刘瑛, 梁颖, 张雯杰, 赵平. 18F-FDG PET/CT结合胸部屏气螺旋CT扫描对非小细胞肺癌术前T分期的价值[J]. 中国医学影像技术, 2010, 26(1): 5-9.

6. 李蒙, 吴宁, 刘瑛. 肺上皮样血管内皮瘤的影像学表现[J]. 癌症进展, 2012, 10 (5): 450-456.

7. Li Meng, Wu Ning, Liu Ying, Zheng Rong, Liang Ying, Zhang Wenjie, Zhao Ping. Regional nodal staging with 18F-FDG PET–CT in non-small cell lung cancer: Additional diagnostic value of CT attenuation and dual-time-point imaging. European Journal of Radiology. 2012, 81 (8):1886-1890. 

8. Li Meng, Wu Ning, Zheng Rong, Liang Ying, Liu Ying, Zhang Wenjie, Li Ni, Zhao Ping. Primary tumor PET/CT [18F] FDG uptake is an independent predictive factor for regional lymph node metastasis in patients with non-small cell lung cancer. Cancer Imaging 2013 Feb 7; 12:566-72. 

9. Li Meng, Zhang Li, Wu Ning, Huang Wenting, Lv Ning.Imaging findings of primary splenic lymphoma: a review of 17 cases in which diagnosis was made at splenectomy. PLoS One. 2013 Nov 21; 8 (11): e80264.

10. Li Meng, Feng Shi-Chao, Wu Ning, Zhang Li.Scout-Based Automated Tube Potential Selection Technique (kV Assist) in EnhancedChest Computed Tomography: Effects on Radiation Exposure and Image Quality.Journal of Computer Assisted Tomography. 2017 May/Jun; 41 (3): 442-445. 

11. Li Meng, Wu Ning, Zhang Li, Sun Wei, Wang Jianwei, Lv Lv, Ren Jiansong, Lin Dongmei. Pathologic N0 Status in Clinical T1N0M0 Lung Adenocarcinoma is Predictable by the Solid Component Proportion with Quantitative CT Number Analysis. Scientific Reports. 2017 Dec 1; 7(1): 16810. 

12. Li Meng, Wu Ning, Zhang Li, Sun Wei, Liu Ying, LvLv, Ren Jiansong, Lin Dongmei. Solid component proportion is an important predictor of tumor invasiveness in clinical stage T1N0M0(cT1N0M0) lung adenocarcinoma. Cancer Imaging.2018 May 4; 18 (1):18. 

13. Li Meng, Zhang Li, Tang Wei, Jin Yu-Jing, Qi Lin-Lin, Wu Ning. Identification of epidermal growth factor receptor mutations in pulmonary adenocarcinoma using dual-energy spectral computed tomography. European Radiology. 2019 Jun; 29(6): 2989-2997. 

14. Li M, Zhang L, Liang X, Huang WT, Ma JW, Wan Y, Wu N. Primary colorectal lymphoma: computed tomography and double-contrast barium enema examination findings with histopathological correlation in 19 patients. Annals of Translational Medicine. 2019; 7(14): 308.

15. Li M, Zhang L, Tang W, Ma PQ, Zhou LN, Jin YJ, QiLL, Wu N. Quantitative features of dual-energy spectral computed tomography for solid lung adenocarcinoma with EGFR and KRAS mutations, and ALK rearrangement: a preliminary study. Translational Lung Cancer Research 2019;8(4):401-412. 

16. Li M, Wan Y, Zhang L, Zhou LN, Shi Z, Zhang R, Hou YL, Wu N. Synchronous multiple lung cancers presenting as multifocal pure ground glass nodules: are whole-body positron emission tomography/computed tomography and brain enhanced magnetic resonance imaging necessary? TranslationalLung Cancer Research 2019;8(5):649-657. 

17. Li M, Zhang L, Xu X-J, Shi Z, Zhao X-M. CT and MRI features of tumors and tumor-like lesions in the abdominal wall. Quantitative Imaging in Medicine and Surgery 2019;9(11): 1820-1839.

18. Li M, Zhang L, Tang W, Duan JC, Jin YJ, Qi LL, Wu N. Dual-energy spectral CT characteristics in surgically resected lung adenocarcinoma: comparison between Kirsten rat sarcoma viral oncogene mutations and epidermal growth factor receptor mutations. Cancer Imaging. 2019 Nov29;19(1):77. 

19. Li M. Chest CT features and their role in COVID-19[published online ahead of print, 2020 Apr 16]. Radiol Infect Dis. doi:10.1016/j.jrid.2020.04.001.