title: Imaging features of automated breast volume scanner: Correlation with molecular subtypes of breast cancer.
abstract: OBJECTIVE
  To investigate the correlation between the imaging features obtained by an automated breast volume scanner (ABVS) and molecular subtypes of breast cancer.
  
  
  METHODS
  We examined 303 malignant breast tumours by ABVS for specific imaging features and by immunohistochemical analysis to determine the molecular subtype. ABVS imaging features, including retraction phenomenon, shape, margins, echogenicity, post-acoustic features, echogenic halo, and calcifications were analysed by univariate and multivariate logistic regression analyses to determine the significant predictive factors of the molecular subtypes.
  
  
  RESULTS
  By univariate logistic regression analysis, the predictive factors of the Luminal-A subtype (n=128) were retraction phenomenon (odds ratio [OR]=10.188), post-acoustic shadowing (OR=5.112), and echogenic halo (OR=3.263, P<0.001). The predictive factors of the Human-epidermal-growth-factor-receptor-2-amplified subtype (n=39) were calcifications (OR=6.210), absence of retraction phenomenon (OR=4.375), non-mass lesions (OR=4.286, P<0.001), absence of echogenic halo (OR=3.851, P=0.035), and post-acoustic enhancement (OR=3.641, P=0.008). The predictors for the Triple-Negative subtype (n=47) were absence of retraction phenomenon (OR=5.884), post-acoustic enhancement (OR=5.255, P<0.001), absence of echogenic halo (OR=4.138, P=0.002), and absence of calcifications (OR=3.363, P=0.001). Predictors for the Luminal-B subtype (n=89) had a relatively lower association (OR≤2.328). By multivariate logistic regression analysis, retraction phenomenon was the strongest independent predictor for the Luminal-A subtype (OR=9.063, P<0.001) when present and for the Triple-Negative subtype (OR=4.875, P<0.001) when absent.
  
  
  CONCLUSIONS
  ABVS imaging features, especially retraction phenomenon, have a strong correlation with the molecular subtypes, expanding the scope of ultrasound in identifying breast cancer subtypes with confidence.
authors.affiliation: Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Shanghai Institute of Medical Imaging, Shanghai 200032, China. Electronic address: fyzheng16@fudan.edu.cn.
authors.forename: Feng-Yang
authors.initials: FY
authors.lastname: Zheng
authors.affiliation: Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China. Electronic address: lu.qing@zs-hospital.sh.cn.
authors.forename: Qing
authors.initials: Q
authors.lastname: Lu
authors.affiliation: Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Shanghai Institute of Medical Imaging, Shanghai 200032, China. Electronic address: huang.beijian@zs-hospital.sh.cn.
authors.forename: Bei-Jian
authors.initials: BJ
authors.lastname: Huang
authors.affiliation: Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China. Electronic address: zs12036@126.com.
authors.forename: Han-Sheng
authors.initials: HS
authors.lastname: Xia
authors.affiliation: Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China. Electronic address: dndyanlixia@163.com.
authors.forename: Li-Xia
authors.initials: LX
authors.lastname: Yan
authors.affiliation: Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Shanghai Institute of Medical Imaging, Shanghai 200032, China. Electronic address: wang.xi@zs-hospital.sh.cn.
authors.forename: Xi
authors.initials: X
authors.lastname: Wang
authors.affiliation: Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai 200032, China. Electronic address: yuan.wei@zs-hospital.sh.cn.
authors.forename: Wei
authors.initials: W
authors.lastname: Yuan
authors.affiliation: Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Shanghai Institute of Medical Imaging, Shanghai 200032, China. Electronic address: wang.wenping@zs-hospital.sh.cn.
authors.forename: Wen-Ping
authors.initials: WP
authors.lastname: Wang
mesh_terms: D000328:Adult; D000368:Aged; D001940:Breast / Q000000981:diagnostic imaging / Q000473:pathology; D001943:Breast Neoplasms / Q000145:classification / Q000000981:diagnostic imaging / Q000473:pathology*; D005260:Female; D006801:Humans; D008875:Middle Aged; D015588:Observer Variation; D009929:Organ Size; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism; D014463:Ultrasonography; D016217:Ultrasonography, Mammary
chemical_list: D018719:Erb-b2 Receptor Tyrosine Kinases; C508053:ERBB2 protein, human
keywords: Automated breast volume scanner; Breast cancer; Molecular subtype; Retraction phenomenon; Ultrasonography