Share this content in WeChat
Research status and potential of multi-parameter breast MRI
LIU Miaomiao  ZHANG Fengxiang  LU Dongxia  YANG Jinhua 

Cite this article as: Liu MM, Zhang FX, Lu DX, et al. Research status and potential of multi-parameter breast MRI[J]. Chin J Magn Reson Imaging, 2022, 13(2): 145-147, 151. DOI:10.12015/issn.1674-8034.2022.02.036.

[Abstract] Magnetic resonance imaging (MRI) is an indispensable tool in breast imaging, especially functional breast imaging plays an important role in the identification of benign and malignant breast masses. Dynamic contrast enhancement MRI can provide breast tumor tissue perfusion and other related functional information, which improves the sensitivity of breast cancer diagnosis. Diffusion weighted imaging can reflect the movement of water molecules. Studies have shown that diffusion function maps such as apparent diffusion coefficient, intravoxel incoherent motion, and diffusion kurtosis imaging can effectively improve the diagnostic specificity. There are also new MRI technical parameters sodium imaging, phosphorus spectroscopic imaging, chemical exchange saturation transfer imaging, blood oxygen level-dependent MRI and positron emission tomography/MRI provides information on the content of specific elements. Existing data indicate that multi-parameter imaging using different functional MRI can provide detailed information about cancer development and progression and provide added value for the specific diagnosis of breast cancer. This article will review the diagnostic value of current and emerging functional parameters of breast MRI technology.
[Keywords] breast cancer;magnetic resonance imaging;dynamic contrast enhancement magnetic resonance imaging;diffusion weighted imaging;intravoxel incoherent motion imaging;chemical exchange saturation transfer imaging;magnetic resonance spectroscopy

LIU Miaomiao1   ZHANG Fengxiang2*   LU Dongxia2   YANG Jinhua2  

1 Inner Mongolia Medical University, Huhhot 010100, China

2 Department of Radiology, Ordos Central Hospital, Ordos 017000, China

Zhang FX, E-mail:

Conflicts of interest   None.

Received  2021-10-07
Accepted  2021-12-28
DOI: 10.12015/issn.1674-8034.2022.02.036
Cite this article as: Liu MM, Zhang FX, Lu DX, et al. Research status and potential of multi-parameter breast MRI[J]. Chin J Magn Reson Imaging, 2022, 13(2): 145-147, 151. DOI:10.12015/issn.1674-8034.2022.02.036.

Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2018, 68(6): 394-424. DOI: 10.3322/caac.21492.
Liu DQ, Zhang W, Wang HY, et al. The features of breast cancer in young women and the diagnostic efficacy of imaging means[J]. J China Clin Med Imaging, 2017, 28(5): 331-336. DOI: 10.3969/j.issn.1008-1062.2017.05.008.
El Khouli RH, Macura KJ, Kamel IR, et al. 3-T dynamic contrast-enhanced MRI of the breast: pharmacokinetic parameters versus conventional kinetic curve analysis[J]. AJR Am J Roentgenol, 2011, 197(6): 1498-1505. DOI: 10.2214/AJR.10.4665.
Li WX, Zhan HH, Cheng JL. The differential diagnosis of breast cancer and breast fibroadenoma by DCE-MRI[J]. Chin J CT MRI, 2011, 9(2): 29-31, 48. DOI: 10.3969/j.issn.1672-5131.2011.02.008.
Zhang X, Min ZQ, Lei XY, et al. The application of dynamic contrast enhanced MR with MIP in differentiating benign and malignant breast diseases[J]. J Pract Radiol, 2018, 34(1): 35-38. DOI: 10.3969/j.issn.1002-1671.2018.01.010.
Li L, Wang K, Sun XL, et al. Parameters of dynamic contrast-enhanced MRI as imaging markers for angiogenesis in human breast cancer[J]. Prog Mod Biomed, 2016, 16(14): 2687-2691. DOI: 10.13241/j.cnki.pmb.2016.14.021.
Huang W, Tudorica LA, Li X, et al. Discrimination of benign and malignant breast lesions by using shutter-speed dynamic contrast-enhanced MR imaging[J]. Radiology, 2011, 261(2): 394-403. DOI: 10.1148/radiol.11102413.
Marinovich ML, Sardanelli F, Ciatto S, et al. Early prediction of pathologic response to neoadjuvant therapy in breast cancer: systematic review of the accuracy of MRI[J]. Breast, 2012, 21(5): 669-677. DOI: 10.1016/j.breast.2012.07.006.
Pinker K, Helbich TH, Morris EA. The potential of multiparametric MRI of the breast[J]. Br J Radiol, 2017, 90(1069): 20160715. DOI: 10.1259/bjr.20160715.
Partridge SC, DeMartini WB, Kurland BF, et al. Quantitative diffusion-weighted imaging as an adjunct to conventional breast MRI for improved positive predictive value[J]. AJR Am J Roentgenol, 2009, 193(6): 1716-1722. DOI: 10.2214/AJR.08.2139.
Zhang M, Horvat JV, Bernard-Davila B, et al. Multiparametric MRI model with dynamic contrast-enhanced and diffusion-weighted imaging enables breast cancer diagnosis with high accuracy[J]. J Magn Reson Imaging, 2019, 49(3): 864-874. DOI: 10.1002/jmri.26285.
Razek AAKA, Lattif MA, Denewer A, et al. Assessment of axillary lymph nodes in patients with breast cancer with diffusion-weighted MR imaging in combination with routine and dynamic contrast MR imaging[J]. Breast Cancer, 2016, 23(3): 525-532. DOI: 10.1007/s12282-015-0598-7.
Mao XJ, Zou XX, Yu N, et al. Quantitative evaluation of intravoxel incoherent motion diffusion-weighted imaging (IVIM) for differential diagnosis and grading prediction of benign and malignant breast lesions[J]. Medicine, 2018, 97(26): e11109. DOI: 10.1097/MD.0000000000011109.
le Bihan D, Breton E, Lallemand D, et al. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders[J]. Radiology, 1986, 161(2): 401-407. DOI: 10.1148/radiology.161.2.3763909.
Qu JJ, Wang SW, Liu YF, et al. Magnetic resonance within the voxel irrelevant movement for the value of the differential diagnosis of benign and malignant breast lesions preliminary study[J]. ZheJiang Clinical Medical Journal, 2019, 21(2): 187-189.
Tamura T, Usui S, Murakami S, et al. Biexponential signal attenuation analysis of diffusion-weighted imaging of breast[J]. Magn Reson Med Sci, 2010, 9(4): 195-207. DOI: 10.2463/mrms.9.195.
Liu CL, Liang CH, Liu ZY, et al. Intravoxel incoherent motion (IVIM) in evaluation of breast lesions: comparison with conventional DWI[J]. Eur J Radiol, 2013, 82(12): e782-e789. DOI: 10.1016/j.ejrad.2013.08.006.
Yu ZX, Liu JK, Zhou H, et al. Prediction of immunohistochemical markers of breast cancer based on intravoxel incoherent motion diffusion weighted imaging and dynamic contrast enhancement[J]. Chin J Med Imaging, 2019, 27(7): 522-526, 528. DOI: 10.3969/j.issn.1005-5185.2019.07.010.
Che SN, Zhao XM, Ou YH, et al. Role of the intravoxel incoherent motion diffusion weighted imaging in the pre-treatment prediction and early response monitoring to neoadjuvant chemotherapy in locally advanced breast cancer[J]. Medicine, 2016, 95(4): e2420. DOI: 10.1097/MD.0000000000002420.
Wen L, Hou J, Zhou JM, et al. Intravoxel incoherent motion diffusion-weighted imaging for discriminating the pathological response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer[J]. Sci Rep, 2017, 7(1): 8496. DOI: 10.1038/s41598-017-09227-9.
Zhu HB, Zhang XY, Zhou XH, et al. Assessment of pathological complete response to preoperative chemoradiotherapy by means of multiple mathematical models of diffusion-weighted MRI in locally advanced rectal cancer: a prospective single-center study[J]. J Magn Reson Imaging, 2017, 46(1): 175-183. DOI: 10.1002/jmri.25567.
Jensen JH, Helpern JA, Ramani A, et al. Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging[J]. Magn Reson Med, 2005, 53(6): 1432-1440. DOI: 10.1002/mrm.20508.
Li T, Hong Y, Kong DX, et al. Histogram analysis of diffusion kurtosis imaging based on whole-volume images of breast lesions[J]. J Magn Reson Imaging, 2020, 51(2): 627-634. DOI: 10.1002/jmri.26884.
Partridge SC, Nissan N, Rahbar H, et al. Diffusion-weighted breast MRI: clinical applications and emerging techniques[J]. J Magn Reson Imaging, 2017, 45(2): 337-355. DOI: 10.1002/jmri.25479.
Zhang Q, Chen X, Gu XW, et al. The value of 3.0 T MR IVIM and DKI in evaluating benign and malignant breast lesions[J]. Chin J Magn Reson Imaging, 2020, 11(12): 1115-1118, 1128. DOI: 10.12015/issn.1674-8034.2020.12.007.
Nogueira L, Brandão S, Matos E, et al. Application of the diffusion kurtosis model for the study of breast lesions[J]. Eur Radiol, 2014, 24(6): 1197-1203. DOI: 10.1007/s00330-014-3146-5.
Wu DM, Li GW, Zhang JX, et al. Characterization of breast tumors using diffusion kurtosis imaging (DKI)[J]. PLoS One, 2014, 9(11): e113240. DOI: 10.1371/journal.pone.0113240.
Jagannathan NR, Kumar M, Seenu V, et al. Evaluation of total choline from in-vivo volume localized proton MR spectroscopy and its response to neoadjuvant chemotherapy in locally advanced breast cancer[J]. Br J Cancer, 2001, 84(8): 1016-1022. DOI: 10.1054/bjoc.2000.1711.
Bilal Ahmadani MA, Bhatty S, Abideen ZU, et al. Imaging in breast cancer: use of magnetic resonance spectroscopy[J]. Cureus, 2020, 12(8): e9734. DOI: 10.7759/cureus.9734.
Leslie TK, James AD, Zaccagna F, et al. Sodium homeostasis in the tumour microenvironment[J]. Biochim Biophys Acta Rev Cancer, 2019, 1872(2): 188304. DOI: 10.1016/j.bbcan.2019.07.001.
Ianniello C, Madelin G, Moy L, et al. A dual-tuned multichannel bilateral RF coil for 1H/23Na breast MRI at 7 T[J]. Magn Reson Med, 2019, 82(4): 1566-1575. DOI: 10.1002/mrm.27829.
Jacobs MA, Ouwerkerk R, Wolff AC, et al. Monitoring of neoadjuvant chemotherapy using multiparametric, ²³Na sodium MR, and multimodality (PET/CT/MRI) imaging in locally advanced breast cancer[J]. Breast Cancer Res Treat, 2011, 128(1): 119-126. DOI: 10.1007/s10549-011-1442-1.
van der Kemp WJM, Stehouwer BL, Boer VO, et al. Proton and phosphorus magnetic resonance spectroscopy of the healthy human breast at 7 T[J]. NMR Biomed, 2017, 30(2): e3684. DOI: 10.1002/nbm.3684.
van der Kemp WJM, van der Velden TA, Schmitz AM, et al. Shortening of apparent transverse relaxation time of inorganic phosphate as a breast cancer biomarker[J]. NMR Biomed, 2019, 32(10): e4011. DOI: 10.1002/nbm.4011.
Wijnen JP, van der Kemp WJM, Luttje MP, et al. Quantitative 31P magnetic resonance spectroscopy of the human breast at 7 T[J]. Magn Reson Med, 2012, 68(2): 339-348. DOI: 10.1002/mrm.23249.
Schmitt B, Trattnig S, Schlemmer HP. CEST-imaging: a new contrast in MR-mammography by means of chemical exchange saturation transfer[J]. Eur J Radiol, 2012, 81: S144-S146. DOI: 10.1016/S0720-048X(12)70060-8.
Zhang S, Seiler S, Wang XZ, et al. CEST-Dixon for human breast lesion characterization at 3 T: a preliminary study[J]. Magn Reson Med, 2018, 80(3): 895-903. DOI: 10.1002/mrm.27079.
Zaric O, Farr A, Poblador Rodriguez E, et al. 7T CEST MRI: a potential imaging tool for the assessment of tumor grade and cell proliferation in breast cancer[J]. Magn Reson Imaging, 2019, 59: 77-87. DOI: 10.1016/j.mri.2019.03.004.
Ruan K, Song G, Ouyang GL. Role of hypoxia in the hallmarks of human cancer[J]. J Cell Biochem, 2009, 107(6): 1053-1062. DOI: 10.1002/jcb.22214.
Stadlbauer A, Zimmermann M, Bennani-Baiti B, et al. Development of a non-invasive assessment of hypoxia and neovascularization with magnetic resonance imaging in benign and malignant breast tumors: initial results[J]. Mol Imaging Biol, 2019, 21(4): 758-770. DOI: 10.1007/s11307-018-1298-4.
Pujara AC, Kim E, Axelrod D, et al. PET/MRI in breast cancer[J]. J Magn Reson Imaging, 2019, 49(2): 328-342. DOI: 10.1002/jmri.26298.
Ming Y, Wu N, Qian TY, et al. Progress and future trends in PET/CT and PET/MRI molecular imaging approaches for breast cancer[J]. Front Oncol, 2020, 10: 1301. DOI: 10.3389/fonc.2020.01301.
Li YC, Feng CL, Meng ZG, et al. Diagnostic value of combining MR diffusion weighted imaging and different sequences combinations in breast benign and malignant lesions[J]. J China Clin Med Imaging, 2017, 28(2): 95-98. DOI: 10.3969/j.issn.1008-1062.2017.02.005.

PREV Application progress of intravoxel incoherent motion diffusion weighted imaging in lungs
NEXT Research progress and prospect of DCE-MRI in breast lesions with rim enhancement

Tel & Fax: +8610-67113815    E-mail: