Diagnosis of BI-RADS 4 lesions by using the breast ultrasound types combined with ultrasound elastography

WANG Bo-juan; YANG Xiao-huan; WANG Xing-hua

doi:10.12117/jccmi.2018.08.011

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Journal of China Clinic Medical Imaging ›› 2018, Vol. 29 ›› Issue (8) : 571-574. DOI: 10.12117/jccmi.2018.08.011

Diagnosis of BI-RADS 4 lesions by using the breast ultrasound types combined with ultrasound elastography

WANG Bo-juan, YANG Xiao-huan, WANG Xing-hua

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Abstract

Objective: To investigate the value of breast imaging reporting and data system(BI-RADS) combined with the breast ultrasound types together with ultrasound elastography(UE) in the diagnosis of BI-RADS 4 breast lesions. Methods: Eighty-six patients with 103 breast lesions were analyzed and classified by BI-RADS for BI-RADS 4, to correct classification based on the breast ultrasound types and the score of UE. Then draw ROC curve to compare the diagnostic efficiency in breast lesions by using BI-RADS and using BI-RADS combined with the breast ultrasound types and UE. Results: Of 103 lesions, 66 lesions were benign and 37 lesions were malignant. The sensitivity of BI-RADS and BI-RADS+the breast ultrasound types+UE in the diagnosis of breast cancer was 75.7% and 91.9%. The specificity of them was 62.1% and 90.9%. The accuracy of them was 67.0% and 91.3%. The positive predictive value of them was 52.8% and 85.0%. The negative predictive value of them was 82.0% and 95.2%. AUC of them was 0.689 and 0.914. In the diagnosis of breast cancer, the specificity and accuracy of BI-RADS+the breast ultrasound types+UE were significantly higher than those of BI-RADS classification(P<0.001, P=0.028 7). Conclusions: The methods of BI-RADS+the breast ultrasound types+UE can significantly improve the value of ultrasound in the diagnosis of BI-RADS 4 breast lesions.

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Breast neoplasms / Ultrasonography, mammary

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WANG Bo-juan, YANG Xiao-huan, WANG Xing-hua. Diagnosis of BI-RADS 4 lesions by using the breast ultrasound types combined with ultrasound elastography[J]. Journal of China Clinic Medical Imaging. 2018, 29(8): 571-574 https://doi.org/10.12117/jccmi.2018.08.011

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