Literature DB >> 25261646

Three-dimensional ultrasonography for the prediction of breast cancer prognosis.

Guang Xu1, Ting Han, Ming-Hua Yao, Juan Xie, Hui-Xiong Xu, Rong Wu.   

Abstract

PURPOSE: To determine the value of three-dimensional (3D) ultrasonography findings in the prediction of breast cancer prognosis.
METHODS: The findings of 3D ultrasonography of 221 breast tumors were compared with pathologic prognostic factors, including tumor diameter, axillary lymph node status, histologic grade, estrogen receptor (ER) and progesterone receptor (PR) status, human epidermal growth factor receptor 2 (C-erb-B2), Ki-67 (cell proliferation marker) and p53 expression.
RESULTS: The convergence sign was correlated to the tumor diameter, axillary lymph node status, histologic grade, ER and PR status. The convergence sign was found significantly more frequently in the small tumor group (diameter ≤ 2 cm; p=0.001), in breast tumors associated with axillary lymph node metastases (p=0.034), in lower histologic grade (grade I and II) (p=0.011) and in positive ER and PR expression group (p=0.049; p=0.023, respectively). The appearance of tumor margins was correlated to axillary lymph node status and C-erb-B2 expression, with most breast tumors associated with axillary lymph node metastases and negative C-erb-B2 expression exhibiting irregular margins on 3D ultrasonography (p=0.000; p=0.039). The homogeneity of the tumor boundary was detected significantly more frequently in breast tumors without axillary lymph node metastases (p=0.037).
CONCLUSION: The 3D ultrasonographic characteristics of breast tumors, especially the convergence sign, may be used to predict breast cancer prognosis and provide a basis for making more accurate therapeutic decisions.

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Year:  2014        PMID: 25261646

Source DB:  PubMed          Journal:  J BUON        ISSN: 1107-0625            Impact factor:   2.533


  1 in total

1.  Identification of breast cancer recurrence risk factors based on functional pathways in tumor and normal tissues.

Authors:  Xiujie Chen; Lei Liu; YunFeng Wang; Bo Liu; Diheng Zeng; Qing Jin; MengJian Li; DeNan Zhang; Qiuqi Liu; Hongbo Xie
Journal:  Oncotarget       Date:  2017-03-28
  1 in total

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