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Clinical Article
MRI differentiation between breast mucinous carcinoma and fibroadenoma
ZHAO Jianxiu  SHENG Fugeng  ZHOU Juan  SHUANG Ping  YANG Xiaoyan  YIN Hui  WANG Tingting 

Cite this article as: Zhao JX, Sheng FG, Zhou J, et al. MRI differentiation between breast mucinous carcinoma and fibroadenoma. Chin J Magn Reson Imaging, 2019, 10(2): 136-139. DOI:10.12015/issn.1674-8034.2019.02.012.


[Abstract] Objective: To explore the MRI differentiation between breast mucinous carcinoma (MCs) and fibroadenoma (FAs) as to improve the diagnostic accuracy of MCs of the breast.Materials and Methods: 31 cases of breast MCs and 50 cases of FAs confirmed by pathology were collected.Results: Breast MCs and FAs T2WI all showed higher signal intensity on T2WI. ①Morphology: irregular margins were observed more frequently in MCs, but FAs showed more margin circumscribed. ②ADC value: the mean ADC value of pure-MCs was (1.8±0.5)×10-3 mm2/s, the mean ADC value of mixed-MCs was (1.0±0.6)×10-3 mm2/s, the mean ADC value of FAs was (1.4±0.30)×10-3 mm2/s. ③Internal enhancement characteristic: pure-MCs also showed delayed heterogeneous enhancement (45%, 9/20) and rim enhancement (45%, 9/20), mixed-MCs also showed heterogeneous enhancement (91%, 10/11), FAs showed homogeneous enhancement (44%, 22/50) and heterogeneous enhancement (40%, 20/50) and dark internal septation (14%, 7/50). ④Time signal intensity curve (TIC): pure-MCs and FAs also showed Ⅰ type, mixed-MCs also showed Ⅲ type. The difference of MCs and FAs was statistically significant (P<0.05).Conclusions: Breast MCs and FAs are relatively characteristic in MRI. Correctly understanding the characteristics of MRI can improve the diagnostic accuracy of MCs.
[Keywords] breast neoplasms;mucinous carcinoma;fibroadenoma;magnetic resonance imaging

ZHAO Jianxiu Department of Radiology, No.307 Hospital of PLA, Beijing 100071, China

SHENG Fugeng Department of Radiology, No.307 Hospital of PLA, Beijing 100071, China

ZHOU Juan* Department of Radiology, No.307 Hospital of PLA, Beijing 100071, China

SHUANG Ping Department of Radiology, No.307 Hospital of PLA, Beijing 100071, China

YANG Xiaoyan Department of Radiology, No.307 Hospital of PLA, Beijing 100071, China

YIN Hui Department of Radiology, No.307 Hospital of PLA, Beijing 100071, China

WANG Tingting Department of Radiology, No.307 Hospital of PLA, Beijing 100071, China

*Correspondence to: Zhou J, E-mail: zjuan122@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This work was part granted by the Natural Natural Science Foundation of China No.21575161
Received  2018-06-19
Accepted  2018-08-03
DOI: 10.12015/issn.1674-8034.2019.02.012
Cite this article as: Zhao JX, Sheng FG, Zhou J, et al. MRI differentiation between breast mucinous carcinoma and fibroadenoma. Chin J Magn Reson Imaging, 2019, 10(2): 136-139. DOI:10.12015/issn.1674-8034.2019.02.012.

[1]
钟琦,崔凤.乳腺MRI对不同类型黏液腺癌的诊断价值.中国临床医学影像杂志, 2016, 27(2): 94-97.
[2]
金纯,李权,郭贵龙,等. 35例乳腺粘液腺癌病理分型和临床分析.中国高等医学教育, 2013(9): 138-139.
[3]
Reeves GK, Pirie K, Green J, et al. Reproductive factors and specific histological types of breast cancer: prospective study and meta-analysis. Br J Cancer, 2009, 100(3): 538-544.
[4]
刘佩芳,尹璐,牛昀,等.乳腺黏液腺癌MRI表现特征及其与病理对照研究.中华放射学杂志, 2009, 43(5): 470-475.
[5]
郭媛,孔庆聪,朱叶青,等.乳腺单纯型黏液癌的磁共振征象与细胞密度及免疫组化的相关分析.中华医学杂志, 2017, 97(17): 1307-1311.
[6]
李莉,程流泉,李洪福,等.乳腺单纯型黏液腺癌与纤维腺瘤的MRI表现.中国医学影像学杂志, 2011, 19(7): 503-508.
[7]
刘佩芳,鲍润贤,牛昀,等.乳腺良恶性病变动态增强MRI表现特征与血管生成相关性的初步研究.中华放射学杂志, 2002, 36(11): 967-972.
[8]
薛志新.乳腺粘液腺癌的病理特征及临床预后分析.现代诊断与治疗, 2016, 27(23): 4413-4415.
[9]
华小兰,华佳,所世腾,等.乳腺黏液癌的MRI诊断.磁共振成像, 2017, 8(3): 182-188.
[10]
Igarashi T, Ashida H, Morikawa K, et al. Use of BI-RADS-MRI descriptors for differentiation between mucinous carcinoma and fibroadenoma. Eur J Radiol, 2016, 85(6): 1092-1098.

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