磁共振新技术在肺结节诊断中的研究进展

江叶海; 蒲豆豆; 于楠

doi:10.12122/j.issn.1674-4500.2023.04.35

磁共振新技术在肺结节诊断中的研究进展

doi: 10.12122/j.issn.1674-4500.2023.04.35

江叶海^1,,
蒲豆豆^1,,
于楠^{1, 2, ,}

1.
陕西中医药大学医学技术学院，陕西咸阳 712046
2.
陕西中医药大学附属医院医学影像科，陕西咸阳 712000

基金项目:

陕西省科技厅重点产业创新链 2021ZDLSF04-10

陕西科技厅基础研究项目 2022JM-453

国家级大学生创新创业训练计划 202210716013

详细信息

作者简介:
江叶海，在读硕士研究生，E-mail: jiangyehai@126.com

蒲豆豆，在读硕士研究生，E-mail: 872970953@qq.com

通讯作者:
于楠，博士，副教授，副主任医师，E-mail: yunan0512@sina.com

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- 被引次数: 0
出版历程
- 收稿日期: 2023-02-20
- 网络出版日期: 2023-07-18
- 刊出日期: 2023-07-20

Research progress of new magnetic resonance technology in pulmonary nodules

JIANG Yehai^1
,,
PU Doudou^1
,,
YU Nan^{1, 2
, ,}

1.
School of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang 712046, China
2.
Department of Medical Imaging, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712000, China

摘要

摘要: MRI具有无辐射、软组织分辨率高、多参数、多序列成像的优势，广泛应用于全身各系统。以往由于肺内氢质子含量低、呼吸运动伪影以及磁化率伪影等原因，MRI被认为不能用于肺部扫描。随着MRI技术的飞速发展，如并行采集技术、呼吸门控技术、新序列的研发以及人工智能的发展，肺部MRI成像逐渐完善。随着人们对辐射剂量和肺结节关注度的增加，肺部MRI的临床需求也逐渐增加。本文将从MRI新技术在结节检出和良恶性鉴别两方面展开综述，包括放射状容积内插式屏气序列、超短回波时间、零回波时间、压缩感知容积内插式屏气序列、纵向弛豫时间定量成像和化学交换饱和转移等MRI新技术。
- 肺结节 /
- 磁共振成像 /
- 超短回波时间成像 /
- 零回波时间成像 /
- T1 mapping
Abstract: MRI has the advantages of radiation-free, high soft tissue resolution, multi-parameter and multi-sequence imaging, and is widely used in all systems of the whole body.In the past, due to the low content of hydrogen protons in the lung, respiratory motion artifacts and magnetic susceptibility artifacts, MRI was considered not to be used in lung scanning. With the rapid development of MRI technology, such as parallel acquisition technology, respiratory gating technology, and development of new sequences and artificial intelligence, lung MRI technology is gradually improved. With the increase of people's attention to radiation dose and pulmonary nodules, the clinical demand of pulmonary MRI is also increasing. This article will review the new technology of MRI from two aspects: nodule detection and benign and malignant differentiation, including star volume interpolated breath-hold examination sequence, ultrashort echo time, zero echo time, compression sensing volume interpolated breath-hold examination sequence, longitudinal relaxation time quantitative imaging, chemical exchange saturation transfer and other new MRI techniques.
- pulmonary nodules /
- magnetic resonance imaging /
- ultrashort echo time imaging /
- zero echo time imaging /
- T1 mapping

HTML全文

表 1 MRI新序列肺结节检出率比较

Table 1. Comparison of detection rates of lung nodules by MRI new sequence

Sequence	Equipment	Breath-hold	Acquisition time (s)	Detection rate (%)*	Author
StarVIBE	3.0T Siemens	No	330	94.0	Ren Zhanli^[4]
StarVIBE	3.0T Siemens	No	330	94.0	Yu^[3]
StarVIBE	3.0T Siemens	No	420	73.0	Vermersch^[7]
StarVIBE	PET-MRI Siemens	No	220	47.7	Bruckmann^[36]
CS-VIBE	1.5T Siemens	Yes	13	83.0	Huang^[9]
UTE	1.5T Siemens	No	210-300	78.0	Huang^[18]
UTE	1.5T Siemens	No	380	76.4	Renz^[20]
UTE	3.0T Siemens	No	200-310	90.8	Cha^[19]
ZTE	3.0T GE	No	125-141	89.5	Bae^[16]
ZTE	PET-MRI GE	No	330	70.0	chang^[33]
ZTE	3.0T GE	No	127-148	80.0	Bae^[35]
StarVIBE: Star volume interpolated breath- hold examination: CS- VIBE: Compressed sensing volume interpolated breath-hold examination; UTE: Ultrashort time echo; ZTE: Zero time echo. *The detection rate of nodules is the total detection rate, including ground glass nodules, some solid nodules, and solid nodules.

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参考文献(51)

[1]	Yang F, Pan X, Zhu K, et al. Accelerated 3D high-resolution T2-weighted breast MRI with deep learning constrained compressed sensing, comparison with conventional T2-weighted sequence on 3.0 T[J]. Eur J Radiol, 2022, 156: 110562. doi: 10.1016/j.ejrad.2022.110562
[2]	Cha MJ, Park HJ, Paek MY, et al. Free-breathing ultrashort echo time lung magnetic resonance imaging using stack-of-spirals acquisition: a feasibility study in oncology patients[J]. J Magn Reson Imaging, 2018, 51: 137-43. doi: 10.1016/j.mri.2018.05.002
[3]	Yu N, Yang CB, Ma GM, et al. Feasibility of pulmonary MRI for nodule detection in comparison to computed tomography[J]. BMC Med Imaging, 2020, 20(1): 53. doi: 10.1186/s12880-020-00451-w
[4]	任占丽, 贺太平, 杨创勃, 等. 磁共振3D-VIBE序列和STAR-VIBE序列对肺结节显示能力的比较研究[J]. 磁共振成像, 2019, 10(1): 14-7. https://www.cnki.com.cn/Article/CJFDTOTAL-CGZC201901006.htm
[5]	任占丽, 张敏, 雷雨欣, 等. T1加权STAR VIBE序列与CT成像在评估肺实质疾病中的对比研究[J]. 磁共振成像, 2019, 10(6): 440-4. https://www.cnki.com.cn/Article/CJFDTOTAL-CGZC201906012.htm
[6]	Yu N, Duan H, Yang C, et al. Free-breathing radial 3D fat-suppressed 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
[7]	Vermersch M, Emsen B, Monnet A, et al. Chest PET/MRI in solid cancers: comparing the diagnostic performance of a free-breathing 3D-T1-GRE stack-of-stars volume interpolated breath-hold examination (StarVIBE) acquisition with that of a 3D-T1-GRE volume interpolated breath-hold examination (VIBE) for chest staging during whole-body PET/MRI[J]. J Magnc Reson Imaging, 2022, 55(6): 1683-93. doi: 10.1002/jmri.27981
[8]	Li H, Hu C, Yang Y, et al. Single-breath-hold T2WI MRI with artificial intelligence-assisted technique in liver imaging: As compared with conventional respiratory-triggered T2WI[J]. Magn Reson Imaging, 2022, 93: 175-80. doi: 10.1016/j.mri.2022.08.012
[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]	郑裕, 李仕红, 林光武, 等. 磁共振自由呼吸CS-VIBE在肺部肿瘤动态增强成像中的应用研究[J]. 中国医学计算机成像杂志, 2019, 25(3): 246-51. doi: 10.3969/j.issn.1006-5741.2019.03.007
[11]	张旭阳, 于楠, 张喜荣, 等. 磁共振超短回波时间序列的应用研究进展[J]. 磁共振成像, 2022, 13(2): 163-6. https://www.cnki.com.cn/Article/CJFDTOTAL-CGZC202202040.htm
[12]	Jiang WW, Ong F, Johnson KM, et al. Motion robust high resolution 3D free-breathing pulmonary MRI using dynamic 3D image self-navigator[J]. Magn Reson Med, 2018, 79(6): 2954-67. doi: 10.1002/mrm.26958
[13]	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
[14]	Ohno Y, Koyama H, Yoshikawa T, et al. Standard-, reduced-, and No-dose thin-section radiologic examinations: comparison of capability for nodule detection and nodule type assessment in patients suspected of having pulmonary nodules[J]. Radiology, 2017, 284(2): 562-73. doi: 10.1148/radiol.2017161037
[15]	Wielpütz MO, Triphan SMF, Ohno Y, et al. Outracing lung signal decay-potential of ultrashort echo time MRI[J]. Rofo, 2019, 191(5): 415-23. doi: 10.1055/a-0715-2246
[16]	Bae K, Jeon KN, Hwang MJ, et al. Comparison of lung imaging using three-dimensional ultrashort echo time and zero echo time sequences: preliminary study[J]. Eur Radiol, 2019, 29(5): 2253-62. doi: 10.1007/s00330-018-5889-x
[17]	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): 1208-21. doi: 10.1002/mrm.27998
[18]	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 Phy, 2021, 34(3): 399-409. doi: 10.1007/s10334-020-00885-x
[19]	Cha MJ, Ahn HS, Choi H, et al. Accelerated stack-of-spirals free-breathing three-dimensional ultrashort echo time lung magnetic resonance imaging: A feasibility study in patients with breast cancer[J]. Front Oncol, 2021, 11: 746059. doi: 10.3389/fonc.2021.746059
[20]	Renz D, Herrmann K, Kraemer M, et al. Ultrashort echo time MRI of the lung in children and adolescents: comparison with non-enhanced computed tomography and standard post-contrast T1w MRI sequences[J]. Eur Radiol, 2021, 32: 1833-42.
[21]	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).
[22]	范丽, 夏艺, 刘士远. 肺部磁共振成像机遇与挑战: 中国十年来发展成果及展望[J]. 磁共振成像, 2022, 13(10): 61-5. https://www.cnki.com.cn/Article/CJFDTOTAL-CGZC202210008.htm
[23]	Ohno Y, Takenaka D, Yoshikawa T, et al. Efficacy of ultrashort echo time pulmonary MRI for lung nodule detection and lung-RADS classification[J]. Radiology, 2022, 302(3): 697-706. doi: 10.1148/radiol.211254
[24]	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
[25]	Olthof SC, Reinert C, Nikolaou K, et al. Detection of lung lesions in breath-hold VIBE and free-breathing Spiral VIBE MRI compared to CT[J]. Insights Imaging, 2021, 12(1): 175. doi: 10.1186/s13244-021-01124-0
[26]	Ohno Y, Kauczor HU, 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
[27]	Darçot E, Delacoste J, Dunet V, et al. Lung MRI assessment with high-frequency noninvasive ventilation at 3 T[J]. J Magn Reson Imaging, 2020, 74: 64-73. doi: 10.1016/j.mri.2020.09.006
[28]	窦晗, 王晓明. 磁共振零回波成像应用进展[J]. 磁共振成像, 2022, 13(2): 167-70. https://www.cnki.com.cn/Article/CJFDTOTAL-CGZC202202041.htm
[29]	Gibiino F, Sacolick L, Menini A, et al. Free-breathing, zero-TE MR lung imaging[J]. Magn Reson Mater Phy, 2015, 28(3): 207-15. doi: 10.1007/s10334-014-0459-y
[30]	Liu QY, Feng ZC, Liu WV, et al. Assessment of solid pulmonary nodules or masses using zero echo time MR lung imaging: a prospective head-to-head comparison with CT[J]. Front Oncol, 2022, 12: 812014. doi: 10.3389/fonc.2022.812014
[31]	Zeng F, Nogami M, Ueno YR, et al. Diagnostic performance of zero-TE lung MR imaging in FDG PET/MRI for pulmonary malignancies[J]. Eur Radiol, 2020, 30(9): 4995-5003. doi: 10.1007/s00330-020-06848-z
[32]	Zeimpekis KG, Kellenberger C J, Geiger J. Assessment of lung density in pediatric patients using three-dimensional ultrashort echo-time and four-dimensional zero echo-time sequences[J]. Jpn J Radiol, 2022, 40(7): 722-9. doi: 10.1007/s11604-022-01258-1
[33]	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]. Sci Rep, 2021, 11: 17636. doi: 10.1038/s41598-021-94702-7
[34]	Bae K, Jeon KN, Hwang MJ, et al. Respiratory motion-resolved four-dimensional zero echo time (4D ZTE) lung MRI using retrospective soft gating: feasibility and image quality compared with 3D ZTE[J]. Eur Radiol, 2020, 30(9): 5130-8. doi: 10.1007/s00330-020-06890-x
[35]	Bae K, Jeon KN, Hwang MJ, et al. Application of highly flexible adaptive image receive coil for lung MR imaging using zero TE sequence: comparison with conventional anterior array coil[J]. Diagnostics (Basel), 2022, 12(1): 148. doi: 10.3390/diagnostics12010148
[36]	Bruckmann NM, Kirchner J, Morawitz J, et al. Free-breathing 3D Stack of Stars GRE (StarVIBE) sequence for detecting pulmonary nodules in ¹⁸F-FDG PET/MRI[J]. EJNMMI Phys, 2022, 9(1): 11. doi: 10.1186/s40658-022-00439-1
[37]	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): 443-54. doi: 10.21037/jtd-22-77
[38]	Alamidi DF, Morgan AR, Hubbard Cristinacce PL, et al. COPD patients have short lung magnetic ResonanceT₁Relaxation time[J]. J Chronic Obstr Pulm Dis, 2016, 13(2): 153-9. doi: 10.3109/15412555.2015.1048851
[39]	Neemuchwala F, Ghadimi Mahani M, Pang YX, et al. Lung T1 mapping magnetic resonance imaging in the assessment of pulmonary disease in children with cystic fibrosis: a pilot study[J]. Pediatr Radiol, 2020, 50(7): 923-34. doi: 10.1007/s00247-020-04638-9
[40]	Mirsadraee S, Tse M, Kershaw L, et al. T1 characteristics of interstitial pulmonary fibrosis on 3T MRI-a predictor of early interstitial change?[J]. Quant Imaging Med Surg, 2016, 6(1): 42-9.
[41]	Renne J, Hinrichs J, Schönfeld C, et al. Noninvasive quantification of airway inflammation following segmental allergen challenge with functional MR imaging: a proof of concept study[J]. Radiology, 2015, 274(1): 267-75. doi: 10.1148/radiol.14132607
[42]	Jiang JQ, Cui L, Xiao Y, et al. B₁-CorrectedT1 mapping in lung cancer: repeatability, reproducibility, and identification of histological types[J]. J Magn Reson Imaging, 2021, 54(5): 1529-40. doi: 10.1002/jmri.27844
[43]	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
[44]	Fang T, Meng N, Feng PY, et al. A comparative study of amide proton transfer weighted imaging and intravoxel incoherent MotionMRI techniques versus (18)F-FDG PET to distinguish solitary pulmonary lesions and their subtypes[J]. J Magnetic Resonance Imaging, 2022, 55(5): 1376-90. doi: 10.1002/jmri.27977
[45]	冯鹏洋, 孟楠, 方婷, 等. 酰胺质子转移加权成像与体素内不相干运动成像评估肺腺癌病理分级及其与SUVmax的相关性[J]. 磁共振成像, 2022, 13(8): 24-9. https://www.cnki.com.cn/Article/CJFDTOTAL-CGZC202208005.htm
[46]	Meng N, Fu FF, Feng PY, et al. Evaluation of amide proton transfer-weighted imaging for lung cancer subtype and epidermal growth factor receptor: a comparative study with diffusion and metabolic parameters[J]. Magnetic Resonance Imaging, 2022, 56(4): 1118-29. doi: 10.1002/jmri.28135
[47]	Yang S, Wang Y, Shi Y, et al. Radiomics nomogram analysis of T2-fBLADE-TSE in pulmonary nodules evaluation[J]. J Magn Reson Imaging, 2022, 85: 80-6. doi: 10.1016/j.mri.2021.10.010
[48]	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.
[49]	Tang X, Xu X, Han Z, et al. Elaboration of a multimodal MRI-based radiomics signature for the preoperative prediction of the histological subtype in patients with non-small-cell lung cancer[J]. Biomed Eng Online, 2020, 19(1): 5.
[50]	Tang X, Bai GY, Wang H, et al. Elaboration of Multiparametric MRI-based radiomics signature for the preoperative quantitative identification of the histological grade in patients with non-small-cell lung cancer[J]. Magn Reson Imaging, 2022, 56(2): 579-89.
[51]	Wang YZ, Wan Q, Xia XY, et al. Value of radiomics model based on multi-parametric magnetic resonance imaging in predicting epidermal growth factor receptor mutation status in patients with lung adenocarcinoma[J]. J Thorac Dis, 2021, 13(6): 3497-508.