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The value and the construction of the evaluation system of BI-RADS#br#
combined with CDFI together with UE |
LIU Shun-lan, LYU Guo-rong, XU Wan-hong, GUO Hai-xin, XU Dan-feng, XU Zhi-rong |
Department of Ultrasound, the Second Affiliated Hospital of Fujian Medical University, Quanzhou Fujian 362000, China |
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Abstract Objective: To investigate the value of breast imaging reporting and data system(BI-RADS) combined with color Doppler flow imaging(CDFI) together with ultrasound elastography(UE) in the diagnosis of breast lesions. Methods: One hundred and ninety-nine patients with 215 breast lesions were analyzed and classified by BI-RADS, to correct classification based on the score of UE and Adler grading of blood flow. Then draw ROC curve to compare the diagnostic efficiency in breast lesions by using BI-RADS and using BI-RADS combined with UE(BI-RADS+UE), and also by using BI-RADS combined with UE and CDFI(BI-RADS+UE+CDFI). Results: In the 215 lesions, 126 lesions were benign and 89 lesions were malignant. The sensitivity of BI-RADS, BI-RADS+UE and BI-RADS+UE+CDFI in the diagnosis of breast cancer were 77.5%, 88.8% and 91%, respectively. The specificity of them was 78.6%, 84.9%, 88.9%, respectively. The accuracy of them were 78.9%, 85.1%, 87.9%, respectively. The positive predictive value of them was 71.9%, 79.4%, 81.8%, respectively. The negative predictive value of them were 83.2%, 89.8%, 93.1%, respectively. AUC of them were 0.780, 0.868, 0.900, respectively. In the diagnosis of breast cancer, the sensitivity and accuracy of BI-RADS+UE and BI-RADS+UE+CDFI were significantly higher than those of BI-RADS classification(P<0.05). The sensitivity of BI-RADS+UE+CDFI in the diagnosis of breast cancer is higher than that of BI-RADS+UE(P<0.05). Conclusions: The methods of BI-RADS+UE and BI-RADS+UE+CDFI can significantly improve the value of ultrasound in the diagnosis of breast lesions. The sensitivity of BI-RADS+UE+CDFI in the diagnosis of breast cancer is higher than that of BI-RADS+UE. So it can effectively improve the detection rate of malignant lesions.
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Received: 24 January 2017
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