title: Role of multi-mode ultrasound in the diagnosis of level 4 BI-RADS breast lesions and Logistic regression model.
abstract: OBJECTIVE
  This study is to investigate the diagnostic role of multi-mode ultrasound in level 4 BI-RADS breast lesions and to establish a Logistic regression model.
  
  
  METHODS
  Totally 179 patients with 182 sites of breast lesions were enrolled in this study. Preoperatively, the examinations of routine ultrasonography, elastography, contrast-enhanced ultrasonography and three-dimensional color Doppler were performed. Postoperatively, the breast lesions were diagnosed as benign and malignant lesions according to pathological results. Diagnostic indicators of each ultrasound analysis were determined and compared. The relationship between these diagnostic indicators and the benign and malignant features of breast lesions was analyzed by single factor analysis. Logistic regression model was established.
  
  
  RESULTS
  The diagnostic indicators with high sensitivity and specificity were tumor edge, enhanced range and score of elastography. Four factors of tumor edge, enhanced order, contrast mode and score of elastography were related with the benign and malignant features of breast lesions. The prediction model was Logit (P) = 0.636 + 4.471X1 + 4.337X2 + 3.753X3 + 3.014X4 + 2.525X5 + 2.105X6. Likelihood ratio test showed that the model was statistically significant (χ(2) = 161.876, P < 0.0001). This model could effectively distinguish between benign and malignant tumors (R(2) = 0.813, prediction accuracy 92.3%). The differences in sensitivity and specificity between multi-mode ultrasound diagnosis and routine ultrasound diagnosis were statistically significant (P < 0.001). However, there was no significant difference between Logistic regression model and multi-mode ultrasound diagnosis.
  
  
  CONCLUSIONS
  Multi-mode ultrasound and Logistic regression model are more effective in diagnosing level 4 BI-RADS breast lesions.
authors.affiliation: Department of Ultrasonography, The First Affiliated Hospital of Xinjiang Medical University Urumqi 830054, Xinjiang, China ; Department of Ultrasonography, The Affiliated Tumor Hospital of Xinjiang Medical University Urumqi 830011, Xinjiang, China.
authors.forename: Xiaoling
authors.initials: X
authors.lastname: Leng
authors.affiliation: Department of Radio-Chemotherapy, The Fifth Affiliated Hospital of Xinjiang Medical University Urumqi 830011, Xinjiang, China.
authors.forename: Guofu
authors.initials: G
authors.lastname: Huang
authors.affiliation: Department of Ultrasonography, The First Affiliated Hospital of Xinjiang Medical University Urumqi 830054, Xinjiang, China.
authors.forename: Lanhui
authors.initials: L
authors.lastname: Yao
authors.affiliation: Department of Ultrasonography, The Affiliated Tumor Hospital of Xinjiang Medical University Urumqi 830011, Xinjiang, China.
authors.forename: Fucheng
authors.initials: F
authors.lastname: Ma
keywords: BI-RADS 4 level; Breast neoplasms; multi-mode ultrasound diagnosis