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Opportunities and challenges of pulmonary magnetic resonance imaging: Achievements and prospects over the past decade in China
FAN Li  XIA Yi  LIU Shiyuan 

Cite this article as: Fan L, Xia Y, Liu SY. Opportunities and challenges of pulmonary magnetic resonance imaging: Achievements and prospects over the past decade in China[J]. Chin J Magn Reson Imaging, 2022, 13(10): 61-65. DOI:10.12015/issn.1674-8034.2022.10.008.

[Abstract] The lung MRI technology has been a great challenge in medical treatment for a long time. In the past 10 years, thanks to the rapid development of technology, MRI has great potential in the application of structural and functional imaging assessment of pulmonary diseases. Fast 4D acquisition with free breath, microstructure functional imaging and AI based on the clinical management strategy would be the potential research. In this review, we focus on the currently available MR functional imaging, quantitative imaging, new technologies independently developed in China and the application of artificial intelligence for pulmonary MRI, comparing with the international research, to find out the potential research in the future, in order to provide reference for the research and continuous innovation of lung MRI technology in China.
[Keywords] lung;lung cancer;pneumonia;chronic obstructive pulmonary disease;magnetic resonance imaging;functional imaging;quantitative imaging;artificial intelligence

FAN Li   XIA Yi   LIU Shiyuan*  

Department of Radiology, the Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China

Liu SY, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 81930049, 81871321, 82171926); Key R&D Program from Ministry of Science and Technology of China (No. 2022YFC2010000, 2022YFC2010002); Radiological Image Database Construction Project of National Health Commission of China (No. YXFSC2022JJSJ002).
Received  2022-10-11
Accepted  2022-10-14
DOI: 10.12015/issn.1674-8034.2022.10.008
Cite this article as: Fan L, Xia Y, Liu SY. Opportunities and challenges of pulmonary magnetic resonance imaging: Achievements and prospects over the past decade in China[J]. Chin J Magn Reson Imaging, 2022, 13(10): 61-65. DOI:10.12015/issn.1674-8034.2022.10.008.

Jiang JQ, Yin JB, Cui L, et al. Lung cancer: short-term reproducibility of intravoxel incoherent motion parameters and apparent diffusion coefficient at 3T[J]. J Magn Reson Imaging, 2018, 47(4): 1003-1012. DOI: 10.1002/jmri.25820.
Yuan M, Zhong Y, Zhang YD, et al. Volumetric analysis of intravoxel incoherent motion imaging for assessment of solitary pulmonary lesions[J]. Acta Radiol, 2017, 58(12): 1448-1456. DOI: 10.1177/0284185117698863.
Liang JY, Li J, Li ZP, et al. Differentiating the lung lesions using Intravoxel incoherent motion diffusion-weighted imaging: a meta-analysis[J/OL]. BMC Cancer, 2020, 20(1): 799 [2022-10-17]. DOI: 10.1186/s12885-020-07308-z.
Ye X, Chen S, Tian YR, et al. A preliminary exploration of the intravoxel incoherent motion applied in the preoperative evaluation of mediastinal lymph node metastasis of lung cancer[J]. J Thorac Dis, 2017, 9(4): 1073-1080. DOI: 10.21037/jtd.2017.03.110.
Zheng Y, Huang WJ, Zhang XL, et al. A Noninvasive Assessment of Tumor Proliferation in Lung cancer Patients using Intravoxel Incoherent Motion Magnetic Resonance Imaging[J]. J Cancer, 2021, 12(1): 190-197. DOI: 10.7150/jca.48589.
Jiang JQ, Fu YG, Zhang LL, et al. Volumetric analysis of intravoxel incoherent motion diffusion-weighted imaging in preoperative assessment of non-small cell lung cancer[J]. Jpn J Radiol, 2022, 40(9): 903-913. DOI: 10.1007/s11604-022-01279-w.
Wang QR, Wang DY, Zhao S, et al. Application of diffusion-weighted magnetic resonance imaging with different b-values in the puncture of lung space-occupying lesions[J]. Chin J Magn Reson Imaging, 2021, 12(8): 75-78. DOI: 10.12015/issn.1674-8034.2021.08.015.
Yan CG, Xu J, Xiong W, et al. Use of intravoxel incoherent motion diffusion-weighted MR imaging for assessment of treatment response to invasive fungal infection in the lung[J]. Eur Radiol, 2017, 27(1): 212-221. DOI: 10.1007/s00330-016-4380-9.
Peng Q, Tang W, Huang Y, et al. Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma[J]. Chin Med J (Engl), 2020, 133(20): 2403-2409. DOI: 10.1097/CM9.0000000000001074.
Yuan M, Pu XH, Xu XQ, et al. Lung adenocarcinoma: assessment of epidermal growth factor receptor mutation status based on extended models of diffusion-weighted image[J]. J Magn Reson Imaging, 2017, 46(1): 281-289. DOI: 10.1002/jmri.25572.
Fan L, Xia Y, Guan Y, et al. Capability of differentiating smokers with normal pulmonary function from COPD patients: a comparison of CT pulmonary volume analysis and MR perfusion imaging[J]. Eur Radiol, 2013, 23(5): 1234-1241. DOI: 10.1007/s00330-012-2729-2.
Xia Y, Guan Y, Fan L, et al. Dynamic contrast enhanced magnetic resonance perfusion imaging in high-risk smokers and smoking-related COPD: correlations with pulmonary function tests and quantitative computed tomography[J]. COPD, 2014, 11(5): 510-520. DOI: 10.3109/15412555.2014.948990.
Fan L, Liu SY, Xiao XS, et al. Demonstration of pulmonary perfusion heterogeneity induced by gravity and lung inflation using arterial spin labeling[J]. Eur J Radiol, 2010, 73(2): 249-254. DOI: 10.1016/j.ejrad.2008.11.019.
Xu J, Mei L, Liu L, et al. Early assessment of response to chemotherapy in lung cancer using dynamic contrast-enhanced MRI: a proof-of-concept study[J]. Clin Radiol, 2018, 73(7): 625-631. DOI: 10.1016/j.crad.2018.02.013.
Yuan M, Zhang YD, Zhu C, et al. Comparison of intravoxel incoherent motion diffusion-weighted MR imaging with dynamic contrast-enhanced MRI for differentiating lung cancer from benign solitary pulmonary lesions[J]. J Magn Reson Imaging, 2016, 43(3): 669-679. DOI: 10.1002/jmri.25018.
Yang SY, Shan F, Yan QQ, et al. A pilot study of native T1-mapping for focal pulmonary lesions in 3.0 T magnetic resonance imaging: size estimation and differential diagnosis[J]. J Thorac Dis, 2020, 12(5): 2517-2528. DOI: 10.21037/jtd.2020.03.42.
Jiang JQ, Cui L, Xiao Y, et al. B1-corrected T1 mapping in lung cancer: repeatability, reproducibility, and identification of histological types[J]. J Magn Reson Imaging, 2021, 54(5): 1529-1540. DOI: 10.1002/jmri.27844.
Li GZ, Huang RJ, Zhu M, et al. Native T1-mapping and diffusion-weighted imaging (DWI) can be used to identify lung cancer pathological types and their correlation with Ki-67 expression[J]. J Thorac Dis, 2022, 14(2): 443-454. DOI: 10.21037/jtd-22-77.
Bauman G, Santini F, Pusterla O, et al. Pulmonary relaxometry with inversion recovery ultra-fast steady-state free precession at 1.5T[J]. Magn Reson Med, 2017, 77(1): 74-82. DOI: 10.1002/mrm.26490.
Wang FN, Zhu LH, Zhou JJ. To explore the ability of 3.0T MR UTE sequence to display pulmonary nodules: comparison with CT images[J]. Radiol Pract, 2021, 36(3): 357-360. DOI: 10.13609/j.cnki.1000-0313.2021.03.013.
Xia Y, Guan Y, Liu SY, et al. The preliminary application of ultra-short echo time(UTE) MR pulmonary imaging in COPD[J]. J Clin Radiol, 2018, 37(3): 401-405. DOI: 10.13437/j.cnki.jcr.2018.03.010.
Zhao F, Zheng L, Shan F, et al. Evaluation of pulmonary ventilation in COVID-19 patients using oxygen-enhanced three-dimensional ultrashort echo time MRI: a preliminary study[J/OL]. Clin Radiol, 2021, 76(5): 391 [2022-10-10]. DOI: 10.1016/j.crad.2021.02.008.
Voskrebenzev A, Vogel-Claussen J. Proton MRI of the lung: how to tame scarce protons and fast signal decay[J]. J Magn Reson Imaging, 2021, 53(5): 1344-1357. DOI: 10.1002/jmri.27122.
Zhu XC, Chan M, Lustig M, et al. Iterative motion-compensation reconstruction ultra-short TE (iMoCo UTE) for high-resolution free-breathing pulmonary MRI[J]. Magn Reson Med, 2020, 83(4): 1208-1221. DOI: 10.1002/mrm.27998.
Ding ZK, Cheng ZH, She HJ, et al. Dynamic pulmonary MRI using motion-state weighted motion-compensation (MostMoCo) reconstruction with ultrashort TE: a structural and functional study[J]. Magn Reson Med, 2022, 88(1): 224-238. DOI: 10.1002/mrm.29204.
Chang CY, Lee TH, Liu RS, et al. Fractionated deep-inspiration breath-hold ZTE Compared with Free-breathing four-dimensional ZTE for detecting pulmonary nodules in oncological patients underwent PET/MRI[J/OL]. Sci Rep, 2021, 11(1): 17636 [2022-10-17]. DOI: 10.1038/s41598-021-94702-7.
Fang T, Meng N, Feng PY, et al. A comparative study of amide proton transfer weighted imaging and intravoxel incoherent motion MRI techniques versus (18) F-FDG PET to distinguish solitary pulmonary lesions and their subtypes[J]. J Magn Reson Imaging, 2022, 55(5): 1376-1390. DOI: 10.1002/jmri.27977.
Feng PY, Meng N, Fang T, et al. A comparative study of amide proton transfer weighted imaging and intravoxel incoherent motion imaging in the diagnosis of pathological grade of lung adenocarcinoma and its correlation with SUVmax[J]. Chin J Magn Reson Imaging, 2022, 13(8): 24-29. DOI: 10.12015/issn.1674-8034.2022.08.005.
Jiang Y, Chen J, Dong J, et al. The study of multi-nuclide 1H/19F-MR lung ventilation imaging based on atomized perfluorocarbon nanoprobe[J]. Chin J Magn Reson Imaging, 2021, 12(10): 26-31. DOI: 10.12015/issn.1674-8034.2021.10.007.
Ruan WW, Zhong JP, Guan Y, et al. Detection of smoke-induced pulmonary lesions by hyperpolarized 129Xe diffusion kurtosis imaging in rat models[J]. Magn Reson Med, 2017, 78(5): 1891-1899. DOI: 10.1002/mrm.26566.
Ruan WW, Zhong JP, Wang K, et al. Detection of the mild emphysema by quantification of lung respiratory airways with hyperpolarized xenon diffusion MRI[J]. J Magn Reson Imaging, 2017, 45(3): 879-888. DOI: 10.1002/jmri.25408.
Chen SZ, Lan YN, Li HD, et al. Relationship between lung and brain injury in COVID-19 patients: a hyperpolarized 129Xe-MRI-based 8-month follow-up[J/OL]. Biomedicines, 2022, 10(4): 781 [2022-10-17]. DOI: 10.3390/biomedicines10040781.
Zhou Q, Rao QC, Li HD, et al. Evaluation of injuries caused by coronavirus disease 2019 using multi-nuclei magnetic resonance imaging[J]. Magn Reson Lett, 2021, 1(1): 2-10. DOI: 10.1016/j.mrl.2021.100009.
Yang YQ, Zhang YF, Wang BL, et al. Coloring ultrasensitive MRI with tunable metal-organic frameworks[J]. Chem Sci, 2021, 12(12): 4300-4308. DOI: 10.1039/d0sc06969h.

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