Share:
Share this content in WeChat
X
Review
Research progress in MRI diagnosis of breast non-mass enhancement lesions
ZHAO Ying  ZHAO Nan  WANG Yinzhong  XU Yongsheng  ZHAO Wenhui  LEI Junqiang 

Cite this article as: ZHAO Y, ZHAO N, WANG Y Z, et al. Research progress in MRI diagnosis of breast non-mass enhancement lesions[J]. Chin J Magn Reson Imaging, 2025, 16(4): 186-191. DOI:10.12015/issn.1674-8034.2025.04.030.


[Abstract] Breast diseases pose a serious threat to women's health. Among them, non-mass enhancement (NME) lesions of the breast have always been difficult to diagnose and differentiate due to their complex and diverse pathological types and atypical imaging features. In recent years, functional imaging techniques represented by intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI), as well as artificial intelligence (AI) algorithms, have significantly improved the diagnostic efficiency of magnetic resonance imaging (MRI) for NME lesions. Based on this, this paper systematically reviews the research progress of MRI techniques in NME lesions, focuses on discussing the clinical application values of functional imaging, multimodal fusion, and AI models, and proposes future optimization directions in response to technical bottlenecks, aiming to provide references for the clinical practice and scientific research of NME lesions.
[Keywords] non-mass enhancement lesions of the breast;diagnosis and differentiation;magnetic resonance imaging;artificial intelligence;radiomics;multi-parameter and multimodal imaging

ZHAO Ying1, 2   ZHAO Nan1, 2   WANG Yinzhong2   XU Yongsheng2   ZHAO Wenhui1   LEI Junqiang2*  

1 The First Clinical Medical College of Lanzhou University, Lanzhou 730000, China

2 Department of Radiology, the First Hospital of Lanzhou University, Lanzhou 730000, China

Corresponding author: LEI J Q, E-mail: leijq2011@126.com

Conflicts of interest   None.

Received  2025-02-13
Accepted  2025-04-10
DOI: 10.12015/issn.1674-8034.2025.04.030
Cite this article as: ZHAO Y, ZHAO N, WANG Y Z, et al. Research progress in MRI diagnosis of breast non-mass enhancement lesions[J]. Chin J Magn Reson Imaging, 2025, 16(4): 186-191. DOI:10.12015/issn.1674-8034.2025.04.030.

[1]
ZHANG J X, CAI L S, PAN X Y, et al. Comparison and risk factors analysis of multiple breast cancer screening methods in the evaluation of breast non-mass-like lesions[J/OL]. BMC Med Imaging, 2022, 22(1): 202 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/36404330/. DOI: 10.1186/s12880-022-00921-3.
[2]
ARIAN A, DINAS K, PRATILAS G C, et al. The breast imaging-reporting and data system (BI-RADS) made easy[J/OL]. Iran J Radiol, 2022, 19(1): [2025-02-12]. https://brieflands.com/articles/ijradiology-121155. DOI: 10.5812/iranjradiol-121155.
[3]
GREENWOOD H I, WILMES L J, KELIL T, et al. Role of breast MRI in the evaluation and detection of DCIS: opportunities and challenges[J]. J Magn Reson Imaging, 2020, 52(3): 697-709. DOI: 10.1002/jmri.26985.
[4]
DURHAN G, POKER A, SETTARZADE E, et al. Magnetic resonance imaging findings of invasive breast cancer in different histological grades and different histopathological types[J/OL]. Clin Imaging, 2021, 76: 98-103 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/33582618/. DOI: 10.1016/j.clinimag.2021.01.039.
[5]
YAMAGUCHI R, WATANABE H, MIHARA Y, et al. Histopathology of non-mass-like breast lesions on ultrasound[J]. J Med Ultrason, 2023, 50(3): 375-380. DOI: 10.1007/s10396-023-01286-y.
[6]
LIU D D, BA Z G, GAO Y, et al. Subcategorization of suspicious non-mass-like enhancement lesions(BI-RADS-MRI Category4)[J/OL]. BMC Med Imaging, 2023, 23(1): 182 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/37950164/. DOI: 10.1186/s12880-023-01144-w.
[7]
KUBOTA K, MORI M, FUJIOKA T, et al. Magnetic resonance imaging diagnosis of non-mass enhancement of the breast[J]. J Med Ultrason, 2023, 50(3): 361-366. DOI: 10.1007/s10396-023-01290-2.
[8]
LIU G, LI Y, CHEN S L, et al. Non-mass enhancement breast lesions: MRI findings and associations with malignancy[J/OL]. Ann Transl Med, 2022, 10(6): 357 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/35433999/. DOI: 10.21037/atm-22-503.
[9]
AHMADINEJAD N, AZIZINIK F, KHOSRAVI P, et al. Evaluation of features in probably benign and malignant nonmass enhancement in breast MRI[J/OL]. Int J Breast Cancer, 2024, 2024: 6661849 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/38523651/. DOI: 10.1155/2024/6661849.
[10]
GARGIULO M, DIEN E, GAL J, et al. Predictive factors for non-mass enhancement occult in conventional breast imaging: The "PAMAS" study[J/OL]. Eur J Radiol, 2025, 184: 111962 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/39913974/. DOI: 10.1016/j.ejrad.2025.111962.
[11]
ZHOU J, LI M, LIU D Q, et al. Differential diagnosis of benign and malignant breast papillary neoplasms on MRI with non-mass enhancement[J/OL]. Acad Radiol, 2023, 30(Suppl 2): S127-S132 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/36906443/. DOI: 10.1016/j.acra.2023.02.010.
[12]
WANG B, ZHOU L H, WANG S, et al. Clinical application of MRI in differential diagnosis of benign and malignant breast lesions with non-mass enhancement[J]. J Clin Radiol, 2024, 43(5): 724-728. DOI: 10.13437/j.cnki.jcr.2024.05.017.
[13]
HE C Y, ZHANG X F, GAO Y F, et al. DCE-MRI features of non-mass enhanced breast lesions and their relationship with malignant tumors[J]. J Clin Radiol, 2022, 41(10): 1858-1862. DOI: 10.13437/j.cnki.jcr.2022.10.021.
[14]
LUNKIEWICZ M, FORTE S, FREIWALD B, et al. Interobserver variability and likelihood of malignancy for fifth edition BI-RADS MRI descriptors in non-mass breast lesions[J]. Eur Radiol, 2020, 30(1): 77-86. DOI: 10.1007/s00330-019-06312-7.
[15]
AYDIN H. The MRI characteristics of non-mass enhancement lesions of the breast: associations with malignancy[J/OL]. Br J Radiol, 2019, 92(1096): 20180464 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/30673299/. DOI: 10.1259/bjr.20180464.
[16]
MARINO M A, AVENDANO D, SEVILIMEDU V, et al. Limited value of multiparametric MRI with dynamic contrast-enhanced and diffusion-weighted imaging in non-mass enhancing breast tumors[J/OL]. Eur J Radiol, 2022, 156: 110523 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/36122521/. DOI: 10.1016/j.ejrad.2022.110523.
[17]
SONG C, ZHU W S, SHI S Y, et al. Differentiation between benign and malignant non-mass enhancement lesions using volumetric quantitative dynamic contrast-enhanced MR imaging[J]. Radiol Pract, 2020, 35(2): 190-196. DOI: 10.13609/j.cnki.1000-0313.2020.02.013.
[18]
LI H F, LIU G H. Clinical value of MRI dynamic enhancement quantitative parameters in differential diagnosis of benign and malignant breast lesions without mass enhancement[J]. J Imag Res Med Appl, 2021, 5(4): 241-242. DOI: 10.3969/j.issn.2096-3807.2021.04.120.
[19]
ZHAO X, LI B Y, SHI G X, et al. Value of DCE-MRI perfusion in distinguishing non-mass enhanced breast pathologies[J]. Diagn Imag Interv Radiol, 2022, 31(6): 440-445. DOI: 10.3969/j.issn.1005-8001.2022.06.007.
[20]
AVENDANO D, MARINO M A, LEITHNER D, et al. Limited role of DWI with apparent diffusion coefficient mapping in breast lesions presenting as non-mass enhancement on dynamic contrast-enhanced MRI[J/OL]. Breast Cancer Res, 2019, 21(1): 136 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/31801635/. DOI: 10.1186/s13058-019-1208-y.
[21]
PERIĆ I, BRKLJAČIĆ B, TADIĆ T D, et al. DWI in the differentiation of malignant and benign breast lesions presenting with non-mass enhancement on CE-MRI[J/OL]. Cancers, 2024, 17(1): 31 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/39796662/. DOI: 10.3390/cancers17010031.
[22]
LI X, WANG H, GAO J Y, et al. Quantitative apparent diffusion coefficient metrics for MRI-only suspicious breast lesions: any added clinical value?[J]. Quant Imaging Med Surg, 2023, 13(10): 7092-7104. DOI: 10.21037/qims-23-331.
[23]
LV W J, ZHENG D W, GUAN W B, et al. Contribution of diffusion-weighted imaging and ADC values to papillary breast lesions[J/OL]. Front Oncol, 2022, 12: 911790 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/35847891/. DOI: 10.3389/fonc.2022.911790.
[24]
KUNIMATSU N, KUNIMATSU A, UCHIDA Y, et al. Whole-lesion histogram analysis of apparent diffusion coefficient for the assessment of non-mass enhancement lesions on breast MRI[J/OL]. J Clin Imaging Sci, 2022, 12: 12 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/35414962/. DOI: 10.25259/JCIS_201_2021.
[25]
BICKEL H, POLANEC S H, WENGERT G, et al. Diffusion-weighted MRI of breast cancer: improved lesion visibility and image quality using synthetic b-values[J]. J Magn Reson Imaging, 2019, 50(6): 1754-1761. DOI: 10.1002/jmri.26809.
[26]
OKAZAWA A, IIMA M, KATAOKA M, et al. Diagnostic utility of an adjusted DWI lexicon using multiple b-values to evaluate breast lesions in combination with BI-RADS[J]. Magn Reson Med Sci, 2024, 23(4): 438-448. DOI: 10.2463/mrms.mp.2022-0056.
[27]
CHRISTNER S A, GRUNZ J P, SCHLAIß T, et al. Breast lesion morphology assessment with high and standard b values in diffusion-weighted imaging at 3 Tesla[J/OL]. Magn Reson Imaging, 2024, 107: 100-110 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/38246517/. DOI: 10.1016/j.mri.2024.01.005.
[28]
CHAN S W, HU W H, OUYANG Y C, et al. Quantitative measurement of breast tumors using intravoxel incoherent motion (IVIM) MR images[J/OL]. J Pers Med, 2021, 11(7): 656 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/34357123/. DOI: 10.3390/jpm11070656.
[29]
WU X Y, ZHAN S H, LU M Y, et al. Value of intravoxel incoherent motion(IVIM) model in differential diagnosis of idiopathic granulomatous mastitis and invasive ductal carcinoma[J]. Chin Imag J Integr Tradit West Med, 2022, 20(6): 558-562. DOI: 10.3969/j.issn.1672-0512.2022.06.012.
[30]
WU Q, WANG Z, NING N, et al. Differential diagnostic value of IVIM combining with dynamic enhanced MRI in non-mass enhancement adenosis and breast cancer[J]. Chin J Magn Reson Imag, 2023, 14(2): 37-43, 49. DOI: 10.12015/issn.1674-8034.2023.02.007.
[31]
SI L F, LIU X J, LI X Y, et al. Diffusion kurtosis imaging and intravoxel incoherent motion imaging parameters in breast lesions: Effect of radiologists' experience and region-of-interest selection[J/OL]. Eur J Radiol, 2023, 158: 110633 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/36470051/. DOI: 10.1016/j.ejrad.2022.110633.
[32]
ZHANG J, LI L C, ZHANG L, et al. Meta-analysis of dynamic contrast enhancement and diffusion-weighted MRI for differentiation of benign from malignant non-mass enhancement breast lesions[J/OL]. Front Oncol, 2024, 14: 1332783 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/38544833/. DOI: 10.3389/fonc.2024.1332783.
[33]
ZANG H, LIU H L, ZHU L Y, et al. Diagnostic performance of DCE-MRI, multiparametric MRI and multimodality imaging for discrimination of breast non-mass-like enhancement lesions[J/OL]. Br J Radiol, 2022, 95(1136): 20220211 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/35522775/. DOI: 10.1259/bjr.20220211.
[34]
ZANG H, ZHU L Y, WANG X, et al. Analysis of MRI features of non-mass enhancement breast lesions and building the diagnosis model[J]. J Clin Radiol, 2021, 40(3): 436-441. DOI: 10.13437/j.cnki.jcr.2021.03.007.
[35]
AN Y Y, MAO G Q, ZHENG S S, et al. External validation of multiparametric magnetic resonance imaging-based decision rules for characterizing breast lesions and comparison to Kaiser score and breast imaging reporting and data system (BI-RADS) category[J]. Quant Imaging Med Surg, 2025, 15(1): 648-661. DOI: 10.21037/qims-23-1783.
[36]
NIU R L, LI J K, WANG B, et al. Combination of breast ultrasound with magnetic resonance imaging in the diagnosis of non-mass-like breast lesions detected on ultrasound: a new integrated strategy to improve diagnostic performance[J]. Ultrasound Med Biol, 2024, 50(1): 105-111. DOI: 10.1016/j.ultrasmedbio.2023.09.009.
[37]
GOTO M, NAKANO S, SAITO M, et al. Evaluation of an MRI/US fusion technique for the detection of non-mass enhancement of breast lesions detected by MRI yet occult on conventional B-mode second-look US[J]. J Med Ultrason, 2022, 49(2): 269-278. DOI: 10.1007/s10396-021-01175-2.
[38]
XIE Y M, ZHANG X X. A risk prediction stratification for non-mass breast lesions, combining clinical characteristics and imaging features on ultrasound, mammography, and MRI[J/OL]. Front Oncol, 2024, 14: 1337265 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/39484042/. DOI: 10.3389/fonc.2024.1337265.
[39]
YAO Y, ZHANG H J, ZHANG W T, et al. Establishment and application evaluation of Logistic regression model for diagnosing malignant risk of breast non-mass-kike lesions based on MRI and mammography[J]. J China Clin Med Imag, 2024, 35(6): 401-405, 417. DOI: 10.12117/jccmi.2024.06.005.
[40]
WU L H, YANG W, ZHOU X P, et al. Clinical features, mammography and MRI manifestations for differentiating non-mass breast cancer and mastitis[J]. Chin J Med Imag Technol, 2023, 39(11): 1653-1658. DOI: 10.13929/j.issn.1003-3289.2023.11.013.
[41]
LI Y, YANG Z L, LV W Z, et al. Non-mass enhancements on DCE-MRI: development and validation of a radiomics-based signature for breast cancer diagnoses[J/OL]. Front Oncol, 2021, 11: 738330 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/34631572/. DOI: 10.3389/fonc.2021.738330.
[42]
LI Y, YANG Z L, LV W Z, et al. Role of combined clinical-radiomics model based on contrast-enhanced MRI in predicting the malignancy of breast non-mass enhancements without an additional diffusion-weighted imaging sequence[J]. Quant Imaging Med Surg, 2023, 13(9): 5974-5985. DOI: 10.21037/qims-22-1199.
[43]
LV S Y, ZHAO Q F, WANG X Y, et al. The value of radiomics in discriminating granulomatous lobular mastitis from invasive breast cancer in non-mass-like enhancing lesions[J]. J Clin Radiol, 2025, 44(2): 253-258. DOI: 10.13437/j.cnki.jcr.2025.02.003.
[44]
YANG W, YANG W, ZHOU X P, et al. Development and external validation of an XGBoost model for differentiating the benign and malignant nature of non-mass breast lesions[J]. Chin J Magn Reson Imag, 2025, 16(1): 118-126, 145. DOI: 10.12015/issn.1674-8034.2025.01.018.
[45]
GOTO M, SAKAI K, TOYAMA Y, et al. Use of a deep learning algorithm for non-mass enhancement on breast MRI: comparison with radiologists' interpretations at various levels[J]. Jpn J Radiol, 2023, 41(10): 1094-1103. DOI: 10.1007/s11604-023-01435-w.
[46]
WANG L J, CHANG L F, LUO R, et al. An artificial intelligence system using maximum intensity projection MR images facilitates classification of non-mass enhancement breast lesions[J]. Eur Radiol, 2022, 32(7): 4857-4867. DOI: 10.1007/s00330-022-08553-5.
[47]
ZHOU J J, LIU Y L, ZHANG Y, et al. BI-RADS reading of non-mass lesions on DCE-MRI and differential diagnosis performed by radiomics and deep learning[J/OL]. Front Oncol, 2021, 11: 728224 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/34790569/. DOI: 10.3389/fonc.2021.728224.
[48]
MACHIDA Y, SHIMAUCHI A, TOZAKI M, et al. Descriptors of malignant non-mass enhancement of breast MRI: their correlation to the presence of invasion[J]. Acad Radiol, 2016, 23(6): 687-695. DOI: 10.1016/j.acra.2016.01.014.
[49]
LEE S M, NAM K J, CHOO K S, et al. Patterns of malignant non-mass enhancement on 3-T breast MRI help predict invasiveness: using the BI-RADS lexicon fifth edition[J]. Acta Radiol, 2018, 59(11): 1292-1299. DOI: 10.1177/0284185118759139.
[50]
WANG M L, CHANG Y P, WU C H, et al. Prognostic molecular biomarkers in breast cancer lesions with non-mass enhancement on MR[J/OL]. Diagnostics, 2024, 14(7): 747 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/38611660/. DOI: 10.3390/diagnostics14070747.
[51]
YOON G Y, CHOI W J, CHA J H, et al. The role of MRI and clinicopathologic features in predicting the invasive component of biopsy-confirmed ductal carcinoma in situ[J/OL]. BMC Med Imaging, 2020, 20(1): 95 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/32787871/. DOI: 10.1186/s12880-020-00494-z.
[52]
NGUYEN V T, DUONG D H, NGUYEN Q T, et al. The association of magnetic resonance imaging features with five molecular subtypes of breast cancer[J/OL]. Eur J Radiol Open, 2024, 13: 100585 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/39041054/. DOI: 10.1016/j.ejro.2024.100585.
[53]
NIE T T, FENG M W, YANG K, et al. Correlation between dynamic contrast-enhanced MRI characteristics and apparent diffusion coefficient with Ki-67-positive expression in non-mass enhancement of breast cancer[J/OL]. Sci Rep, 2023, 13(1): 21451 [2025-02-12]. https://pubmed.ncbi.nlm.nih.gov/38052920/. DOI: 10.1038/s41598-023-48445-2.

PREV Cardiac magnetic resonance in evaluating cardioxicity induced by anthracycline chemotherapy in breast cancer
NEXT Advances in imaging research on congenital anorectal malformations
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn