Comparison of retraction phenomenon and BI-RADS-US descriptors in differentiating benign and malignant breast masses using an automated breast volume scanner.
OBJECTIVE
To compare the diagnostic values of retraction phenomenon in the coronal planes and descriptors in the Breast Imaging Reporting and Data System-Ultrasound (BI-RADS-US) lexicon in differentiating benign and malignant breast masses using an automated breast volume scanner (ABVS).


METHODS
Two hundred and eight female patients with 237 pathologically proven breast masses (120 benign and 117 malignant) were included in this study. ABVS was performed for each mass after preoperative localization by conventional ultrasonography (US). Multivariate logistic regression analysis was performed to assess independent variables for malignancy prediction. Diagnostic performance was evaluated through the receiver operating characteristic (ROC) curve analysis.


RESULTS
Retraction phenomenon (odds ratio [OR]: 76.70; 95% confidence interval [CI]: 12.55, 468.70; P<0.001) was the strongest independent predictor for malignant masses, followed by microlobulated margins (OR: 55.87; 95% CI: 12.56, 248.44; P<0.001), angular margins (OR: 36.44; 95% CI: 4.55, 292.06; P=0.001), calcifications (OR: 5.53; 95% CI: 1.34, 22.88; P=0.018,) and patient age (OR: 1.10; 95% CI: 1.03, 1.17; P=0.004). Mass shape, orientation, echo pattern, indistinct margins, spiculated margins, and mass size were not significantly associated with breast malignancy. Area under the ROC curve (Az) for microlobulated margins and retraction phenomenon was higher than that for other significant independent predictors. Az, sensitivity, and specificity were 0.877 (95% CI: 0.829, 0.926) and 0.838 (95% CI: 0.783, 0.892), 82.9% and 70.1%, and 92.5% and 98.3%, respectively, for microlobulated margins and retraction phenomenon.


CONCLUSIONS
Retraction phenomenon and microlobulated margins have high diagnostic values in the differentiation of benign and malignant breast masses using an ABVS.
Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China. Electronic address: 13211210063@fudan.edu.cn.
Feng-Yang
FY
Zheng
Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China. Electronic address: dndyanlixia@163.com.
Li-Xia
LX
Yan
Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Fu Dan University Institute of Medical Ultrasound and Engineering, Shanghai 200032, China. Electronic address: huang.beijian@zs-hospital.sh.cn.
Bei-Jian
BJ
Huang
Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China. Electronic address: zs12036@126.com.
Han-Sheng
HS
Xia
Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China. Electronic address: wang.xi@zs-hospital.sh.cn.
Xi
X
Wang
Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China. Electronic address: lu.qing@zs-hospital.sh.cn.
Qing
Q
Lu
Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China. Electronic address: wo123ziji@163.com.
Cui-Xian
CX
Li
Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Fu Dan University Institute of Medical Ultrasound and Engineering, Shanghai 200032, China. Electronic address: wang.wenping@zs-hospital.sh.cn.
Wen-Ping
WP
Wang
D000328:Adult; D000368:Aged; D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology*; D002681:China / Q000453:epidemiology; D005260:Female; D006801:Humans; D007089:Image Enhancement; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods; D008875:Middle Aged; D010363:Pattern Recognition, Automated; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016217:Ultrasonography, Mammary / Q000295:instrumentation* / Q000379:methods
Automated breast volume scanner; BI-RADS; Breast mass; Diagnosis; Retraction phenomenon; Ultrasound