title: Acoustic radiation force impulse elastography of breast imaging reporting and data system category 4 breast lesions.
abstract: BACKGROUND
  This population-based study on early breast cancer detection in women aimed to evaluate acoustic radiation force impulse elastography to differentiate BI-RADS (Breast Imaging Reporting and Data System) category 4 lesions.
  
  
  METHODS
  Acoustic radiation force impulse was performed on 95 patients with 122 BI-RADS 4 breast lesions diagnosed by conventional ultrasound. We calculated the area ratio of lesions by using virtual touch tissue imaging and gray-scale imaging. By using virtual touch tissue quantification, we calculated the ratio of shear wave velocity (SWV) in lesions and in surrounding glandular tissue at the same depth (SWV ratio).
  
  
  RESULTS
  The mean area ratio of benign lesions (1.09 ± 0.17) differed from that of the malignant lesions (1.96 ± 0.64; P < .001). The mean SWV ratio of benign lesions (2.44 ± 1.27) was lower than that of malignant lesions (5.74 ± 1.68; P < .001). The cutoff for the area and SWV ratios for malignancy were estimated to be 1.37 and 3.65, respectively.
  
  
  CONCLUSIONS
  Acoustic radiation force impulse provides quantitative elasticity measurements, which, combined with conventional ultrasound, can potentially improve the diagnostic accuracy of BI-RADS 4 breast lesions, and it is helpful to regulate the BI-RADS classification and avoid the need for unnecessary biopsies.
authors.affiliation: Department of Ultrasound, Affiliated Hospital of Guangdong Medical College, Zhanjiang, Guangdong, China.
authors.forename: Zhan-Qiang
authors.initials: ZQ
authors.lastname: Jin
authors.forename: Xiu-Ru
authors.initials: XR
authors.lastname: Li
authors.forename: Hong-Lian
authors.initials: HL
authors.lastname: Zhou
authors.forename: Jie-Xin
authors.initials: JX
authors.lastname: Chen
authors.forename: Xing
authors.initials: X
authors.lastname: Huang
authors.forename: Hai-Xia
authors.initials: HX
authors.lastname: Dai
authors.forename: Jian-Wen
authors.initials: JW
authors.lastname: Li
authors.forename: Xiao-Dong
authors.initials: XD
authors.lastname: Chen
authors.forename: Xiao-Hong
authors.initials: XH
authors.lastname: Xu
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001706:Biopsy; D001943:Breast Neoplasms / Q000145:classification* / Q000000981:diagnostic imaging* / Q000473:pathology; D002277:Carcinoma / Q000145:classification* / Q000000981:diagnostic imaging* / Q000473:pathology; D055088:Early Detection of Cancer / Q000379:methods / Q000706:statistics & numerical data; D054459:Elasticity Imaging Techniques / Q000379:methods*; D005260:Female; D006801:Humans; D007256:Information Systems / Q000706:statistics & numerical data; D008875:Middle Aged; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D016217:Ultrasonography, Mammary / Q000379:methods*; D055815:Young Adult