title: Digital breast tomosynthesis within a symptomatic "one-stop breast clinic" for characterization of subtle findings.
abstract: OBJECTIVE
  The aim of the study was to evaluate the diagnostic accuracy of combination of full-field digital mammography [two dimension (2D)] and digital breast tomosynthesis [DBT, three dimension (3D)] by comparing the combination with 2D imaging in a symptomatic setting.
  
  
  METHODS
  A retrospective analysis was conducted involving 103 patients who attended symptomatic breast clinics between March 2012 and September 2012. All had subtle signs on 2D images or ultrasound. Mammographic score distribution was compared between 2D imaging and 2D + 3D imaging, followed by comparison with the gold-standard histopathology. Receiver operative characteristic curves and area under curve (AUC) were calculated for 2D imaging and the combination imaging (2D + 3D). SPSS(®) v. 21 (IBM Corp., New York, NY; formerly SPSS Inc., Chicago, IL) was used for data analysis with p < 0.05 as statistically significant.
  
  
  RESULTS
  M3 lesions were reduced from 91 (85.8%) to 18 (16.9%) with the combination imaging. The mean AUC ± 95% confidence interval for 2D images alone was 0.721 (0.662-0.905) and for combined 2D and 3D images was 0.901 (0.765-1.00). The difference in AUCs between the two modalities was 0.180.
  
  
  CONCLUSIONS
  DBT (3D imaging) increases diagnostic accuracy in a symptomatic breast clinic setting and reduces the number of M3 mammograms, when used as an adjuvant to 2D images. Therefore, DBT has the potential to increase workflow efficiency in a symptomatic setting by reducing benign biopsies.
  
  
  CONCLUSIONS
  DBT reduces the number of M3 mammograms when used in the symptomatic breast setting and has the potential to reduce benign biopsies.
authors.affiliation: The Breast Centre, Llandough University Hospital, Cardiff and Vale University Health Board, Penarth, UK.
authors.forename: G J
authors.initials: GJ
authors.lastname: Bansal
authors.affiliation: The Breast Centre, Llandough University Hospital, Cardiff and Vale University Health Board, Penarth, UK.
authors.forename: P
authors.initials: P
authors.lastname: Young
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D055088:Early Detection of Cancer / Q000379:methods*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008327:Mammography / Q000379:methods*; D008875:Middle Aged; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*