title: Analysis of 107 breast lesions with automated 3D ultrasound and comparison with mammography and manual ultrasound.
abstract: OBJECTIVE
  Our aim was to investigate the diagnostic potential of an automated ultrasound (US) breast scanner prototype and compare it with manual US and mammography.
  
  
  METHODS
  Ninety-seven patients with a total of 107 breast lesions had mammograms, manual US and an automated breast US scan. Multiplanar reconstructions in coronal, axial and the sagittal view were reconstructed from the automated dataset and visualized. After biopsy, all lesions were confirmed histologically. The data were evaluated according to the BIRADS (Breast Imaging Reporting and Data System) classification. The sensitivity and specificity were analyzed.
  
  
  RESULTS
  The BIRADS criterion "margin" was significantly related to the overall BIRADS classification, independently of the US method being used. The sensitivity of mammography was significantly lower than of each US method (Fisher's exact test with p<0.05). There were no significant differences between the US methods.
  
  
  CONCLUSIONS
  The reconstructed third (axial) image plane of the whole breast, which corresponds to a craniocaudal mammogram, can give additional information about both, site and differential diagnosis of a lesion. Although image quality was sufficient, automated US is not good enough to replace manual US at this time.
authors.affiliation: Department of Clinical Radiology, University of Munich, Maistr. 11, Munich 80337, Germany. dorothea.hermle@med.uni-muenchen.de
authors.forename: D
authors.initials: D
authors.lastname: Kotsianos-Hermle
authors.forename: K M
authors.initials: KM
authors.lastname: Hiltawsky
authors.forename: S
authors.initials: S
authors.lastname: Wirth
authors.forename: T
authors.initials: T
authors.lastname: Fischer
authors.forename: K
authors.initials: K
authors.lastname: Friese
authors.forename: M
authors.initials: M
authors.lastname: Reiser
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001185:Artificial Intelligence; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005260:Female; D005858:Germany; D006801:Humans; D007089:Image Enhancement / Q000295:instrumentation / Q000592:standards; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation* / Q000592:standards; D021621:Imaging, Three-Dimensional / Q000295:instrumentation* / Q000592:standards; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D010865:Pilot Projects; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016217:Ultrasonography, Mammary / Q000295:instrumentation* / Q000379:methods / Q000592:standards; D055815:Young Adult