Share:
Share this content in WeChat
X
Clinical Article
Value of multi-parameter diffusion weighted imaging in the differential diagnosis of benign and malignant TIC type Ⅱ breast lesions
WANG Hongjie  WANG Weiwei  LÜ Siqiang  CHU Yao  LIU Shangkuan  ZHU Laimin  CHEN Yueqin  SUN Zhanguo 

Cite this article as: Wang HJ, Wang WW, Lü SQ, et al. Value of multi-parameter diffusion weighted imaging in the differential diagnosis of benign and malignant TIC type Ⅱ breast lesions[J]. Chin J Magn Reson Imaging, 2022, 13(9): 18-24. DOI:10.12015/issn.1674-8034.2022.09.004.


[Abstract] Objective To explore the value of parameters obtained by mono-exponential diffusion-weighted imaging (DWI), intravoxel incoherent motion-DWI (IVIM-DWI) and diffusion kurtosis imaging (DKI) in the differential diagnosis of benign and malignant breast lesions with plateau time-signal-curve (TIC) type-Ⅱ in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).Materials and Methods A total of 103 cases with breast TIC type-Ⅱ lesions in the Affiliated Hospital of Jining Medical University from October 2019 to January 2021 were reviewed retrospectively. The patients were divided into benign group (25 patients, 25 lesions) and malignant group (78 patients, 78 lesions) according to the pathological results,the ADC value, true diffusion coefficient (D value), perfusion-related diffusion coefficient (D* value), perfusion fraction (f value), mean diffusion rate (MD value) and mean kurtosis value (MK value) were measured. Independent samples t-test was used to compare the differences of each parameter between the two groups, and univariate/multivariate logistic regression analyses were further performed. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to analyze the diagnostic efficacy of each parameter alone or combination diffusion models (DWI+IVIM, DWI+DKI and DWI+IVIM+DKI) in differentiating benign and malignant breast TIC type-Ⅱ lesions.Results The ADC, D, f, MD, and MK values of the two groups were significantly different (P<0.05), but the D* value of the two groups had no significant difference (P>0.05). Multiple logistic regression analysis showed that the D value and MK value were independent influencing factors in the differential diagnosis of the two groups, with the largest odds ratio for MK value (AUC 0.871, specificity 88.0%, sensitivity 80.8% and accuracy 78.6%). There was no significant difference in AUC among each combined diffusion model (P>0.05), but three-combination diffusion model achieved the greatest diagnostic efficiency (AUC 0.915, sensitivity 92.3%, specificity 84.0% and accuracy 86.4%), and the AUC of which was statistically higher than that of DWI (AUC 0.816, P<0.05).Conclusions DWI combined with IVIM and DKI have a good differential diagnostic value for benign and malignant breast TIC type-Ⅱ lesions.
[Keywords] breast neoplasms;magnetic resonance imaging;diffusion-weighted imaging;intravoxel incoherent motion;diffusion kurtosis imaging

WANG Hongjie1   WANG Weiwei2   LÜ Siqiang1   CHU Yao1   LIU Shangkuan1   ZHU Laimin2   CHEN Yueqin2   SUN Zhanguo2*  

1 Clinical Medical College of Jining Medical University, Jining 272013, China

2 Department of Medical Imaging, Affiliated Hospital of Jining Medical University, Jining 272029, China

*Sun ZG, E-mail: yingxiangszg@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Shandong Medical and Health Science and Technology Development Program (No. 202009011151); Shandong Province Traditional Chinese Medicine Science and Technology Program (No. Q-2022132).
Received  2021-11-08
Accepted  2022-08-30
DOI: 10.12015/issn.1674-8034.2022.09.004
Cite this article as: Wang HJ, Wang WW, Lü SQ, et al. Value of multi-parameter diffusion weighted imaging in the differential diagnosis of benign and malignant TIC type Ⅱ breast lesions[J]. Chin J Magn Reson Imaging, 2022, 13(9): 18-24. DOI:10.12015/issn.1674-8034.2022.09.004.

[1]
Ding YN, Chen XG, Zhang QJ, et al. Historical trends in breast Cancer among women in China from age-period-cohort modeling of the 1990-2015 breast Cancer mortality data[J]. BMC Public Health, 2020, 20(1): 1280. DOI: 10.1186/s12889-020-09375-0.
[2]
Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. DOI: 10.3322/caac.21660.
[3]
Lei SY, Zheng RS, Zhang SW, et al. Breast cancer incidence and mortality in women in China: temporal trends and projections to 2030[J]. Cancer Biol Med, 2021, 18(3): 900-909. DOI: 10.20892/j.issn.2095-3941.2020.0523.
[4]
Kuhl CK, Mielcareck P, Klaschik S, et al. Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions?[J]. Radiology, 1999, 211(1): 101-110. DOI: 10.1148/radiology.211.1.r99ap38101.
[5]
Chen YD, Long LL, Peng P, et al. Diagnosis value of ADC values combination with MRI signs on breast lump lesions with the type of TIC Ⅱ[J]. J Pract Radiol, 2018, 34(3): 370-373, 377. DOI: 10.3969/j.issn.1002-1671.2018.03.011.
[6]
Jiang L, Lu X, Hua B, et al. Intravoxel incoherent motion diffusion-weighted imaging versus dynamic contrast-enhanced magnetic resonance imaging: comparison of the diagnostic performance of perfusion-related parameters in breast[J]. J Comput Assist Tomogr, 2018, 42(1): 6-11. DOI: 10.1097/RCT.0000000000000661.
[7]
Li K, Machireddy A, Tudorica A, et al. Discrimination of malignant and benign breast lesions using quantitative multiparametric MRI: a preliminary study[J]. Tomography, 2020, 6(2): 148-159. DOI: 10.18383/j.tom.2019.00028.
[8]
Uslu H, Önal T, Tosun M, et al. Intravoxel incoherent motion magnetic resonance imaging for breast cancer: a comparison with molecular subtypes and histological grades[J]. Magn Reson Imaging, 2021, 78: 35-41. DOI: 10.1016/j.mri.2021.02.005.
[9]
He MZ, Ruan HP, Ma MP, et al. Application of diffusion weighted imaging techniques for differentiating benign and malignant breast lesions[J/OL]. Front Oncol, 2021, 11 [2021-6-21]. https://www.frontiersin.org/articles/10.3389/fonc.2021.694634/full. DOI: 10.3389/fonc.2021.694634.
[10]
Leithner D, Wengert GJ, Helbich TH, et al. Clinical role of breast MRI now and going forward[J]. Clin Radiol, 2018, 73(8): 700-714. DOI: 10.1016/j.crad.2017.10.021.
[11]
Ma D, Lu F, Zou X, et al. Intravoxel incoherent motion diffusion-weighted imaging as an adjunct to dynamic contrast-enhanced MRI to improve accuracy of the differential diagnosis of benign and malignant breast lesions [J]. Magn Reson Imaging, 2017, 36: 175-179. DOI: 10.1016/j.mri.2016.10.005.
[12]
Yang YW, Hu CH, Zhu M, et al. The differential diagnosis value of MRI apparent diffusion coefficient value combined with dynamic contrast enhanced MRI time-intensity curve type for mass plasma cell mastitis and breast cancer[J]. Chin J Magn Reson Imaging, 2019, 10(7): 530-534. DOI: 10.12015/issn.1674-8034.2019.07.010.
[13]
Zhao R, Ma WJ, Tang J, et al. Heterogeneity of enhancement kinetics in dynamic contrast-enhanced MRI and implication of distant metastasis in invasive breast cancer[J/OL]. Clin Radiol, 2020, 75(12) [2021-7-30]. https://www.clinicalradiologyonline.net/article/S0009-9260(20)30318-4/fulltext.
[14]
Long N, Ran C, Sun J, et al. Correlation study between the magnetic resonance imaging features of breast cancer and expression of immune molecular subtypes[J]. Eur Rev Med Pharmacol Sci, 2020, 24(22): 11518-11527. DOI: 10.26355/eurrev_202011_23793.
[15]
Thakran S, Gupta PK, Kabra V, et al. Characterization of breast lesion using T1-perfusion magnetic resonance imaging: qualitative vs. quantitative analysis[J]. Diagn Interv Imaging, 2018, 99(10): 633-642. DOI: 10.1016/j.diii.2018.05.006.
[16]
Mumin NA, Hamid M, Hamid SA, et al. MRI breast: current imaging trends, clinical applications, and future research directions[J/OL]. Curr Med Imaging, 2022 [2022-1-27]. https://www.eurekaselect.com/article/122604. DOI: 10.2174/1573405618666220415130131
[17]
Chou SS, Romanoff J, Lehman CD, et al. Preoperative breast MRI for newly diagnosed ductal carcinoma in situ: imaging features and performance in a multicenter setting (ECOG-ACRIN E4112 trial)[J/OL]. Radiology, 2021, 301(1) [2021-11-08]. https://pubs.rsna.org/doi/abs/10.1148/radiol.2021204743. DOI: 10.1148/radiol.2021219016.
[18]
Yang XP, Dong MS, Li S, et al. Diffusion-weighted imaging or dynamic contrast-enhanced curve: a retrospective analysis of contrast-enhanced magnetic resonance imaging-based differential diagnoses of benign and malignant breast lesions[J]. Eur Radiol, 2020, 30(9): 4795-4805. DOI: 10.1007/s00330-020-06883-w.
[19]
Thompson JL, Wright GP. The role of breast MRI in newly diagnosed breast cancer: an evidence-based review[J]. Am J Surg, 2021, 221(3): 525-528. DOI: 10.1016/j.amjsurg.2020.12.018.
[20]
Gilbert FJ, Hickman SE, Baxter GC, et al. Opportunities in cancer imaging: risk-adapted breast imaging in screening[J]. Clin Radiol, 2021, 76(10): 763-773. DOI: 10.1016/j.crad.2021.02.013.
[21]
Tang W, Chen L, Jin Z, et al. The diagnostic dilemma with the plateau pattern of the time-intensity curve: can the relative apparent diffusion coefficient (rADC) optimise the ADC parameter for differentiating breast lesions?[J]. Clin Radiol, 2021, 76(9): 688-695. DOI: 10.1016/j.crad.2021.04.015.
[22]
Zhang Q, Peng YS, Liu W, et al. Radiomics based on multimodal MRI for the differential diagnosis of benign and malignant breast lesions[J]. J Magn Reson Imaging, 2020, 52(2): 596-607. DOI: 10.1002/jmri.27098.
[23]
Ma WL, Mao JW, Wang T, et al. Distinguishing between benign and malignant breast lesions using diffusion weighted imaging and intravoxel incoherent motion: a systematic review and meta-analysis[J/OL]. Eur J Radiol, 2021, 141 [2021-6-3]. https://www.ejradiology.com/article/S0720-048X(21)00290-4/fulltext. DOI: 10.1016/j.ejrad.2021.109809.
[24]
Palm T, Wenkel E, Ohlmeyer S, et al. Diffusion kurtosis imaging does not improve differentiation performance of breast lesions in a short clinical protocol[J]. Magn Reson Imaging, 2019, 63: 205-216. DOI: 10.1016/j.mri.2019.08.007.
[25]
Liang JY, Zeng SH, Li ZP, et al. Intravoxel incoherent motion diffusion-weighted imaging for quantitative differentiation of breast tumors: a meta-analysis[J/OL]. Front Oncol, 2020 [2020-10-20]. https://www.frontiersin.org/articles/10.3389/fonc.2020.585486/full. DOI: 10.3389/fonc.2020.585486.
[26]
Lee YJ, Kim SH, Kang BJ, et al. Associations between angiogenic factors and intravoxel incoherent motion-derived parameters in diffusion-weighted magnetic resonance imaging of breast cancer[J/OL]. Medicine, 2021, 100(41) [2021-10-15]. https://journals.lww.com/md-journal/Fulltext/2021/10150/Associations_between_angiogenic_factors_and.30.aspx. DOI: 10.1097/MD.0000000000027495.
[27]
Li ZP, Li XM, Peng C, et al. The diagnostic performance of diffusion kurtosis imaging in the characterization of breast tumors: a meta-analysis[J/OL]. Front Oncol, 2020, 10 [2021-10-27]. https://www.frontiersin.org/articles/10.3389/fonc.2020.575272/full. DOI: 10.3389/fonc.2020.575272.
[28]
Ma Y, Shan D, Wei J, et al. Application of intravoxel incoherent motion diffusion-weighted imaging in differential diagnosis and molecular subtype analysis of breast cancer[J]. Am J Transl Res, 2021, 13(4): 3034-3043.
[29]
Song GJ, Shi JH, Li Q, et al. Comparative study of three diffusion imaging techniques in differential diagnosis of benign and malignant breast lesions[J]. J Clin Radiol, 2019, 38(6): 1010-1014. DOI: 10.13437/j.cnki.jcr.2019.06.016.

PREV Meta-analysis of local spontaneous brain activity changes in acute and subacute mild traumatic brain injury
NEXT Comparative assessment of MRI BI-RADS 4 breast lesions with Kaiser score and apparent diffusion coefficient value
  



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