Share:
Share this content in WeChat
X
Clinical Article
Apparent diffusion coefficient value study in different molecular subtypes of non-specific type invasive breast carcinomas
NAN Shuaiming  HUANG Bo  LUO Yahong 

Cite this article as: Nan SM, Huang B, Luo YH. Apparent diffusion coefficient value study in different molecular subtypes of non-specific type invasive breast carcinomas. Chin J Magn Reson Imaging, 2019, 10(2): 130-135. DOI:10.12015/issn.1674-8034.2019.02.011.


[Abstract] Objective: To investigate the characteristic of apparent diffusion coefficient (ADC) value in the four molecular subtypes of non-specific type invasive breast carcinomas (Luminal A, Luminal B, HER-2-enriched, Basal-like subtype) and its biological prognostic factors estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 (HER-2) to provide the theory basis for identifying the different molecular subtypes and evaluating prognosis of breast cancer.Materials and Methods: One hundred and fifty-eight patients diagnosed as non-specific type invasive breast carcinomas with complete pathologic and preoperative MR data were retrospectively analyzed, preoperative diffusion weighted imaging were acquired (b=0, 800 s/mm2), the average ADC was measured; ER, PR, HER-2 and Ki-67 were obtained by immunohistochemistry, and the subtype of each case was decided. To investigate the characteristic of the ADC values in molecular subtypes and its biological prognostic factor.Results: ADC value of ER-negative, PR negative group and Ki-67 negative group was higher than that in ER-positive and PR-positive group and Ki-67 positive group (1.013±0.099, 1.002±0.094, 1.003±0.087 VS 0.932±0.066, 0.940±0.079, 0.952±0.089), the difference was statistically significant (P<0.01, P<0.01); ADC value of HER-2 positive group is significantly higher than that in HER-2 group negative (1.004±0.088 VS 0.948±0.088), the difference was statistically significant (P<0.05); while only the ADC values of HER-2-enriched subtype was higher than Luminal B and Basal-like subtype (1.048±0.073 VS 0.923±0.074, 0.960±0.095, P<0.01, P<0.01).Conclusions: The four molecular subtypes and its biological prognostic factors present characteristic ADC value in non-specific type invasive breast carcinomas.
[Keywords] breast neoplasms;magnetic resonance imaging;apparent diffusion coefficient;molecular subtypes;prognostic factors

NAN Shuaiming# Department of Radiology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang 110042, China

HUANG Bo# Department of Pathology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang 110042, China

LUO Yahong* Department of Radiology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang 110042, China

#: Co-first author

*Correspondence to: Luo YH, E-mail: cjr.luoyahong@vip.163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This work was part of National Public Industry Special Funds of China No.201402020
Received  2018-07-02
Accepted  2018-09-03
DOI: 10.12015/issn.1674-8034.2019.02.011
Cite this article as: Nan SM, Huang B, Luo YH. Apparent diffusion coefficient value study in different molecular subtypes of non-specific type invasive breast carcinomas. Chin J Magn Reson Imaging, 2019, 10(2): 130-135. DOI:10.12015/issn.1674-8034.2019.02.011.

[1]
孟凡凡,杨壹羚,付丽.乳腺癌异质性的遗传基础.中华病理学杂志, 2016, 45(11): 810-813.
[2]
Guiu S, Michiels S, André F, et al. Molecular subclasses of breast cancer: how do we define them? The IMPAKT 2012 Working Group Statement. Annals of Oncology, 2012, 23(12): 2997-3006.
[3]
Chu W, Jin W, Liu D, et al. Diffusion-weighted imaging in identifying breast cancer pathological response to neoadjuvant chemotherapy: A meta-analysis. Oncotarget, 2018, 9(6): 7088-7100.
[4]
Carey LA, Perou CM, Livasy CA, et al. Race, breast cancer subtypes, and survival in the carolina breast cancer study. JAMA, 2006, 295(21): 2492-2502.
[5]
Cheang MC, Chia SK, Voduc D, et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst, 2009, 101(10): 736-750.
[6]
Goldhirsch A, Winer EP, Coates AS, et al. Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol, 2013, 24(9): 2206-2223.
[7]
Cancello G, Maisonneuve P, Rotmensz N, et al. Progesterone receptor loss identifies Luminal B breast cancer subgroups at higher risk of relapse. Ann Oncol, 2013, 24(3): 661-668.
[8]
Akın Y, Uğurlu MÜ, Kaya H, et al. Diagnostic value of diffusion-weighted imaging and apparent diffusion coefficient values in the differentiation of breast lesions, histpathologic subgroups and correlatıon with prognostic factors using 3.0 Tesla MR. J Breast Health, 2016, 12(3): 123.
[9]
Kamitani T, Matsuo Y, Yabuuchi H, et al. Correlations between apparent diffusion coefficient values and prognostic factors of breast cancer. Magnetic Reson in Med Sci Mrms, 2013, 12(3): 193-199.
[10]
Ludovini V, Sidoni A, Pistola L, et al. Evaluation of the prognostic role of vascular endothelial growth factor and microvessel density in stages I and II breast cancer patients. Breast Cancer Res Treat, 2003, 81(2): 159-168.
[11]
Shin HJ, Kim SH, Lee HJ, et al. Tumor apparent diffusion coefficient as an imaging biomarker to predict tumor aggressiveness in patients with estrogen-receptor-positive breast cancer. Nmr in Biomedicine, 2016, 29(8): 1070-1078.
[12]
Kumar R, Yarmandbagheri R. The role of HER2 in angiogenesis. Seminars in Oncol, 2001, 28(5Suppl): 27-32.
[13]
Kim EJ, Kim SH, Park GE, et al. Histogram analysis of apparent diffusion coefficient at 3.0 T: Correlation with prognostic factors and subtypes of invasive ductal carcinoma. J Magn Reson Imaging, 2015, 42(6): 1666-1678.
[14]
Soliman NA, Yussif SM. Ki-67 as a prognostic marker according to breast cancer molecular subtype. Cancer Biology & Med, 2016, 13(4):496-504.
[15]
Bogner W, Gruber S, Pinker K, et al. Diffusion-weighted MR for differentiation of breast lesions at 3.0 T: how does selection of diffusion protocols affect diagnosis?. Radiology, 2009, 253(2): 341-351.
[16]
Kim SH, Cha ES, Kim HS, et al. Diffusion-weighted imaging of breast cancer: correlation of the apparent diffusion coefficient value with prognostic factors. J Magn Reson Imaging, 2009, 30(3): 615-620.
[17]
Molinari C, Clauser P, Girometti R, et al. MR mammography using diffusion-weighted imaging in evaluating breast cancer: a correlation with proliferation index. La Radiologia Medica, 2015, 120(10): 911-918.
[18]
Aydin H, Guner B, Esen IB, et al. Is there any relationship between adc values of diffusion weighted imaging and the histopathologic prognostic factors of invasive ductal carcinoma?. Br J Radiol, 2018(3): 20170705.
[19]
Martincich L, Deantoni V, Bertotto I, et al. Correlations between diffusion-weighted imaging and breast cancer biomarkers. Eur Radiol, 2012, 22(7): 1519-1528.
[20]
Youk JH, Son EJ, Chung J, et al. Triple-negative invasive breast cancer on dynamic contrast-enhanced and diffusion-weighted MR imaging: comparison with other breast cancer subtypes. Eur Radiol, 2012, 22(8): 1724-1734.

PREV The relationship between right ventricular myocardial strain and age gender by cardiac magnetic resonance tissue tracking
NEXT MRI differentiation between breast mucinous carcinoma and fibroadenoma
  



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