Ultrasound Utility for Predicting Biological Behavior of Invasive Ductal Breast Cancers

  • Zhang, Lei (Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University) ;
  • Liu, Yu-Jie (Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University) ;
  • Jiang, Shuang-Quan (Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University) ;
  • Cui, Hao (Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University) ;
  • Li, Zi-Yao (Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University) ;
  • Tian, Jia-Wei (Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University)
  • Published : 2014.10.23


Purpose: The aim of the study was to evaluate the correlation of ultrasound features with breast cancer molecular status. Materials and Methods: A retrospective review was performed of ultrasound findings in 263 patients diagnosed with breast invasive ductal carcinoma for comparison with immunohistochemistric results were obtained from each lesion. Relationships between ultrasound findings and molecular status were investigated by using multiple regression analysis by means of stepwise logistic regression. Differences in ultrasound criteria were assessed among women with different molecular status. Results: ER positivity was associated with small size, lobulate, angular or spiculated margin contours, absence of calcification, posterior tumor shadowing and low elasticity score; PR positivity was associated with small size, lobulate or angular or spiculated margin contours and absence of calcification; HER2 positivity was associated with presence of calcification and absence of any echogenic halo. The calculated models of predicted molecular status were accurate and discriminating with AUCs of 0.78, 0.74, and 0.74, respectively. Conclusions: Breast cnacer ultrasound features show some correlation with the molecular status. These models may help to expand the scope of ultrasound in predicting tumor biology.



Supported by : National Natural Science Foundations of China


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