The application value of magnetic resonance imaging for the differentiation of benign and malignant pulmonary nodules
-
摘要: 胸部CT是目前最常用的肺结节良恶性鉴别的影像学方法,但其存在辐射负担;而MRI没有辐射风险,可以多参数成像,并已被广泛应用于全身。但MRI在肺结节的应用受到一些限制,原因如肺的低质子信号导致的低信噪比、肺与临近软组织界面的磁化率伪影和心肺运动伪影。随着MRI抗运动伪影技术、超短回波时间序列、功能磁共振和影像组学/人工智能技术的不断发展,MRI在肺结节良恶性鉴别方面具有极大的潜力。本文综述了MRI在肺结节良恶性鉴别定性和定量方面的应用价值,MRI可以作为CT、PET/CT鉴别肺结节良恶性的很好的补充检查手段。Abstract: Chest CT is the most commonly used imaging method for the differentiation of benign and malignant pulmonary nodules currently, but it exists radiation burden. MRI has no radiation risk, and it can be multi-parametric imaging and has been widely used throughout the whole body. However, the application of MRI in pulmonary nodules is somewhat limited because of the reason such as low signal-to-noise ratio due to the low proton signal of the lung, susceptibility artifacts at the interface between the lung and adjacent soft tissues, and cardiopulmonary motion artifacts. Following with the constant development of MRI anti-motion artifact techniques, ultrashort echo time sequences, functional MRI and radiomics/artificial intelligence techniques, MRI shows huge potential for the differentiation of benign and malignant pulmonary nodules. This article reviews the application value of MRI in the qualitative and quantitative differentiation of benign and malignant pulmonary nodules, MRI can be used as a good complementary examination tools on the basis of CT and PET/CT examination for the differentiation of benign and malignant pulmonary nodules.
-
Key words:
- pulmonary nodules /
- benign and malignant /
- differentiation /
- magnetic resonance imaging
-
[1] Ohno Y, Takenaka D, Yoshikawa T, et al. Efficacy of ultrashort echo time pulmonary MRI for lung nodule detection and lungRADS classification[J]. Radiology, 2022, 302(3): 697-706. doi: 10.1148/radiol.211254 [2] Liu H, Chen RH, Tong C, et al. MRI versus CT for the detection of pulmonary nodules: a meta- analysis[J]. Medicine, 2021, 100(42): e27270. doi: 10.1097/MD.0000000000027270 [3] Meier- Schroers M, Homsi R, Schild HH, et al. Lung cancer screening with MRI: characterization of nodules with different nonenhanced MRI sequences[J]. Acta Radiol, 2019, 60(2): 168-76. doi: 10.1177/0284185118778870 [4] Sim AJ, Kaza E, Singer L, et al. A review of the role of MRI in diagnosis and treatment of early stage lung cancer[J]. Clin Transl Radiat Oncol, 2020, 24: 16-22. [5] Schiebler ML, Parraga G, Gefter WB, et al. Synopsis from expanding applications of pulmonary MRI in the clinical evaluation of lung disorders: fleischner society position paper[J]. Chest, 2021, 159(2): 492-5. doi: 10.1016/j.chest.2020.09.075 [6] Wan KC, Lu AM, Takahashi Edwin A, et al. Can MRI contribute to pulmonary nodule analysis?[J]. J Magn Reson Imaging, 2019, 49 (7): e256-64. [7] Wielpütz MO. MRI of pulmonary nodules: closing the gap on CT [J]. Radiology, 2022, 302(3): 707-8. doi: 10.1148/radiol.212516 [8] Meier-Schroers M, Homsi R, Gieseke J, et al. Lung cancer screening with MRI: evaluation of MRI for lung cancer screening by comparison of LDCT-and MRI-derived Lung-RADS categories in the first two screening rounds[J]. Eur Radiol, 2019, 29(2): 898-905. doi: 10.1007/s00330-018-5607-8 [9] Huang YS, Niisato E, Su MY M, et al. Applying compressed sensing volumetric interpolated breath-hold examination and spiral ultrashort echo time sequences for lung nodule detection in MRI [J]. Diagnostics, 2021, 12(1): 93. doi: 10.3390/diagnostics12010093 [10] Huang YS, Niisato E, Su MY M, et al. Detecting small pulmonary nodules with spiral ultrashort echo time sequences in 1.5 T MRI [J]. Magn Reson Mater Phys Biol Med, 2021, 34(3): 399-409. doi: 10.1007/s10334-020-00885-x [11] Delacoste J, Dunet V, Dournes G, et al. MR volumetry of lung nodules: a pilot study[J]. Front Med, 2019, 6: 18. doi: 10.3389/fmed.2019.00018 [12] Yu N, Duan H, Yang CB, et al. Free- breathing radial 3D fatsuppressed T1-weighted gradient echo (r-VIBE) sequence for assessment of pulmonary lesions: a prospective comparison of CT and MRI[J]. Cancer Imaging, 2021, 21(1): 68. doi: 10.1186/s40644-021-00441-3 [13] 李大鹏, 于波, 吴明英, 等. 磁共振3D-VIBE序列联合生化指标水平检测在肺结节诊断研究[J]. 浙江创伤外科, 2022, 27(4): 804-6. https://www.cnki.com.cn/Article/CJFDTOTAL-ZJCW202204087.htm [14] 王福南, 朱柳红, 周建军. 探讨3.0T磁共振UTE序列对肺结节的显示能力: 与CT图像对比[J]. 放射学实践, 2021, 36(3): 357-60. https://www.cnki.com.cn/Article/CJFDTOTAL-FSXS202103019.htm [15] Wang FN, Lin X, Lin C, et al. Ability of three-dimensional 3-Tesla ultrashort echo time magnetic resonance imaging to display the morphological characteristics of pulmonary nodules: a sensitivity analysis[J]. Quant Imaging Med Surg, 2023, 13(3): 1792-801. doi: 10.21037/qims-22-118 [16] Wielpütz MO, Lee HY, Koyama H, et al. Morphologic characterization of pulmonary nodules with ultrashort TE MRI at 3T[J]. Am J Roentgenol, 2018, 210(6): 1216-25. doi: 10.2214/AJR.17.18961 [17] Ohno Y, Kauczor H, Hatabu H, et al. MRI for solitary pulmonary nodule and mass assessment: current state of the art[J]. J Magn Reson Imaging, 2018, 47(6): 1437-58. doi: 10.1002/jmri.26009 [18] Usuda K, Iwai S, Yamagata A, et al. Novel insights of T2-weighted imaging: significance for discriminating lung cancer from benign pulmonary nodules and masses[J]. Cancers, 2021, 13(15): 3713. doi: 10.3390/cancers13153713 [19] Dang S, Ma G, Duan H, et al. Free-breathing BLADE fatsuppressed T2 weighted turbo spin echo sequence for distinguishing lung cancer from benign pulmonary nodules or masses: a pilot study[J]. Magn Reson Imaging, 2023, 102: 79-85. doi: 10.1016/j.mri.2022.12.025 [20] 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): 2517-28. doi: 10.21037/jtd.2020.03.42 [21] Yan QQ, Yi YQ, Shen J, et al. Preliminary study of 3 T-MRI native T1- mapping radiomics in differential diagnosis of non- calcified solid pulmonary nodules/masses[J]. Cancer Cell Int, 2021, 21(1): 539. doi: 10.1186/s12935-021-02195-1 [22] Shen G, Kuang A. Letter to the editor re Magnetic resonance imaging of pulmonary nodules: accuracy in a granulomatous disease-endemic region[J]. Eur Radiol, 2017, 27(10): 4015-6. doi: 10.1007/s00330-017-4798-8 [23] Koyama H, Ohno Y, Seki S, et al. Value of diffusion-weighted MR imaging using various parameters for assessment and characterization of solitary pulmonary nodules[J]. Eur J Radiol, 2015, 84(3): 509-15. doi: 10.1016/j.ejrad.2014.11.024 [24] Concatto NH, Watte G, Marchiori E, et al. Reply to letter to the editor re: Magnetic resonance imaging of pulmonary nodules: accuracy in a granulomatous disease-endemic region[J]. Eur Radiol, 2017, 27(10): 4017-8. doi: 10.1007/s00330-017-4799-7 [25] Guan HX, Pan YY, Wang YJ, et al. Comparison of various parameters of DWI in distinguishing solitary pulmonary nodules [J]. Curr Med Sci, 2018, 38(5): 920-4. doi: 10.1007/s11596-018-1963-5 [26] Wan Q, Deng YS, Lei Q, et al. Differentiating between malignant and benign solid solitary pulmonary lesions: are intravoxel incoherent motion and diffusion kurtosis imaging superior to conventional diffusion-weighted imaging?[J]. Eur Radiol, 2019, 29 (3): 1607-15. doi: 10.1007/s00330-018-5714-6 [27] Xiang L, Yang H, Qin Y, et al. Differential value of diffusion kurtosis imaging and intravoxel incoherent motion in benign and malignant solitary pulmonary lesions[J]. Frontiers in Oncology, 2023, 12: 1075072. doi: 10.3389/fonc.2022.1075072 [28] Can TB, Uzan G. Comparison of the diagnostic accuracy of diffusion-weighted magnetic resonance imaging and positron emission tomography/computed tomography in pulmonary nodules: a prospective study[J]. Pol J Radiol, 2019, 84: 498-503. doi: 10.5114/pjr.2019.91200 [29] Schiebler ML. Can solitary pulmonary nodules be accurately characterized with diffusion- weighted MRI?[J]. Radiology, 2019, 290(2): 535-6. doi: 10.1148/radiol.2018182442 [30] Hatabu H, Ohno Y, Gefter WB, et al. Expanding applications of pulmonary MRI in the clinical evaluation of lung disorders: fleischner society position paper[J]. Radiology, 2020, 297(2): 286-301. doi: 10.1148/radiol.2020201138 [31] Usuda K, Ishikawa M, Iwai S, et al. Combination assessment of diffusion-weighted imaging and T2-weighted imaging is acceptable for the differential diagnosis of lung cancer from benign pulmonary nodules and masses[J]. Cancers, 2021, 13(7): 1551. doi: 10.3390/cancers13071551 [32] Scialpi M, Malaspina C, Rondoni V, et al. Solitary pulmonary nodule: increasing diagnosis and accuracy of biopsy by biparametric MR imaging[J]. Lung India, 2018, 35(2): 182. doi: 10.4103/lungindia.lungindia_424_17 [33] 陆杰, 徐海, 沈杰, 等. 小视野DWI联合T2WI压脂鉴别肺实性结节的价值[J]. 影像诊断与介入放射学, 2022, 31(6): 416-21. https://www.cnki.com.cn/Article/CJFDTOTAL-YXZD202206003.htm [34] Usuda K, Ishikawa M, Iwai S, et al. Pulmonary nodule and mass: superiority of MRI of diffusion-weighted imaging and T2-weighted imaging to FDG-PET/CT[J]. Cancers, 2021, 13(20): 5166. doi: 10.3390/cancers13205166 [35] El-Nenaey MA, Alashwah MM, Al-Shafey BI, et al. Determining the dynamic contrast-enhanced magnetic resonance imaging (DCEMRI) in diagnosis of pulmonary nodules[J]. J Adv Med Med Res, 2021: 115-29. [36] Kumar N, Sharma M, Aggarwal N, et al. Role of various DW MRI and DCE MRI parameters as predictors of malignancy in solid pulmonary lesions[J]. Can Assoc Radiol J, 2021, 72(3): 525-32. doi: 10.1177/0846537120914894 [37] 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: Distinguishing Lung Cancer from Benign SPLs[J]. J Magn Reson Imaging, 2016, 43(3): 669-79. doi: 10.1002/jmri.25018 [38] Feng F, Qiang FL, Shen AJ, et al. Dynamic contrast-enhanced MRI versus 18F- FDG PET/CT: which is better in differentiation between malignant and benign solitary pulmonary nodules?[J]. Chin J Cancer Res, 2018, 30(1): 21-30. doi: 10.21147/j.issn.1000-9604.2018.01.03 [39] Hekimoglu A, Ergun O, Turan A, et al. Role of magnetic resonance spectroscopy in differential diagnosis of solitary pulmonary lesions [J]. Diagn Interv Radiol, 2021, 27(6): 710-5. doi: 10.5152/dir.2021.20419 [40] Ohno Y, Kishida Y, Seki S, et al. Amide proton transfer-weighted imaging to differentiate malignant from benign pulmonary lesions: Comparison with diffusion-weighted imaging and FDG-PET/CT [J]. J Magn Reson Imaging, 2018, 47(4): 1013-21. doi: 10.1002/jmri.25832 [41] Yang S, Wang Y, Shi Y, et al. Radiomics nomogram analysis of T2-fBLADE- TSE in pulmonary nodules evaluation[J]. Magn Reson Imaging, 2022, 85: 80-6. doi: 10.1016/j.mri.2021.10.010 [42] Wang XH, Wan Q, Chen HJ, et al. Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods[J]. Eur Radiol, 2020, 30 (8): 4595-605. doi: 10.1007/s00330-020-06768-y [43] Feng B, Zhang MH, Zhu HL, et al. MRI image segmentation model with support vector machine algorithm in diagnosis of solitary pulmonary nodule[J]. Contrast Media Mol Imaging, 2021, 2021: 1-10. [44] Wan KC, Kline Timothy L, Hee YJ, et al. Magnetic resonance radiomic feature performance in pulmonary nodule classification and impact of segmentation variability on radiomics[J]. Br J Radiol, 2022, 95(1140): 20220230. doi: 10.1259/bjr.20220230 [45] Wan Q, Zhou JX, Xia X, et al. Diagnostic performance of 2D and 3D T2WI-based radiomics features with machine learning algorithms to distinguish solid solitary pulmonary lesion[J]. Front Oncol, 2021, 11: 683587. doi: 10.3389/fonc.2021.683587 [46] Madeleine B, Moritz S, Olga S, et al. Diagnostic accuracy of magnetic resonance imaging for the detection of pulmonary nodules simulated in a dedicated porcine chest phantom[J]. PLoS One, 2020, 15(12): e0244382.
点击查看大图
计量
- 文章访问数: 157
- HTML全文浏览量: 70
- PDF下载量: 19
- 被引次数: 0