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• Clinical Article •
Differentiation of breast benign and borderline phyllodes tumors from fibroadenomas on MRI
PENG Teng-fei  HUNG Bo  LUO Ya-hong  ZHANG Yi  NIU Wei  MA Xiao-wen  LI Pu-chen 

DOI:10.12015/issn.1674-8034.2018.11.003.


[Abstract] Objective: To analyze the MRI characteristics of benign and borderline phyllodes tumors (PT) and fibroadenomas of the breast, and to improve the differential diagnosis.Materials and Methods: We analyzed MRI features statistically of 52 cases of benign and borderline lobulated tumors and 68 cases of fibrous adenoma, which were confirmed by postoperative pathology and had complete magnetic resonance data in our hospital.Results: The phyllodes tumors were more common in lobulated or multi-nodular fusion shapes. Fibroadenomas were more common in round or round-like shape, and there were no multi-nodular fusion. Both phyllodes tumors and fibroadenomas were commonly smooth. Eighteen phyllodes tumors showed a flaky high signal in the lesion on T1WI, and the pathology showed bleeding. Only 5 cases of fibroadenomas showed high signal. On T2WI, phyllodes tumors showed high signal and fibroadenomas showed low or equal-low signal. After dynamic enhanced scanning, phyllodes tumors showed obvious and uneven enhancement, cystic changes were seen in part. Fibroadenomas showed uniform enhancement, only 1 case showed cystic change, both showed no reinforcement separation. Time-signal intensity curve (TIC) classification, phyllodes tumors was more common in type Ⅱ, fibroadenomas was more common in type Ⅰ. On DWI performance, phyllodes tumors all showed high signal, and 8 cases of fibroadenomas showed low or equal-low signal.Conclusions: The benign and borderline phyllodes tumors and fibroadenomas of the breast have some differences in shape, signal, enhancement mode and TIC curve, which are helpful for the differential diagnosis of fibroadenomas.
[Keywords] Breast neoplasms；Phyllodes tumor；Fibroadenoma；Magnetic resonance imaging

PENG Teng-fei Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang 110042, China

HUNG Bo Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang 110042, China

LUO Ya-hong* Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang 110042, China

ZHANG Yi Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang 110042, China

NIU Wei Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang 110042, China

MA Xiao-wen Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang 110042, China

LI Pu-chen Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang 110042, China

*Correspondence to: Luo YH E-mail: luoyahong8888@hotmail.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  National public welfare industry special fund No. 201402020
Received  2018-06-27
DOI: 10.12015/issn.1674-8034.2018.11.003
DOI:10.12015/issn.1674-8034.2018.11.003.

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