title: Changes in breast cancer detection and mammography recall rates after the introduction of a computer-aided detection system.
abstract: BACKGROUND
  Computer-aided mammography is rapidly gaining clinical acceptance, but few data demonstrate its actual benefit in the clinical environment. We assessed changes in mammography recall and cancer detection rates after the introduction of a computer-aided detection system into a clinical radiology practice in an academic setting.
  
  
  METHODS
  We used verified practice- and outcome-related databases to compute recall rates and cancer detection rates for 24 Mammography Quality Standards Act-certified academic radiologists in our practice who interpreted 115,571 screening mammograms with (n = 59,139) or without (n = 56,432) the use of a computer-aided detection system. All statistical tests were two-sided.
  
  
  RESULTS
  For the entire group of 24 radiologists, recall rates were similar for mammograms interpreted without and with computer-aided detection (11.39% versus 11.40%; percent difference = 0.09, 95% confidence interval [CI] = -11 to 11; P =.96) as were the breast cancer detection rates for mammograms interpreted without and with computer-aided detection (3.49% versus 3.55% per 1000 screening examinations; percent difference = 1.7, 95% CI = -11 to 19; P =.68). For the seven high-volume radiologists (i.e., those who interpreted more than 8000 screening mammograms each over a 3-year period), the recall rates were similar for mammograms interpreted without and with computer-aided detection (11.62% versus 11.05%; percent difference = -4.9, 95% CI = -21 to 4; P =.16), as were the breast cancer detection rates for mammograms interpreted without and with computer-aided detection (3.61% versus 3.49% per 1000 screening examinations; percent difference = -3.2, 95% CI = -15 to 9; P =.54).
  
  
  CONCLUSIONS
  The introduction of computer-aided detection into this practice was not associated with statistically significant changes in recall and breast cancer detection rates, both for the entire group of radiologists and for the subset of radiologists who interpreted high volumes of mammograms.
authors.affiliation: Department of Radiology, University of Pittsburgh, Magee-Womens Hospital of the University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA. gurd@upmc.edu
authors.forename: David
authors.initials: D
authors.lastname: Gur
authors.forename: Jules H
authors.initials: JH
authors.lastname: Sumkin
authors.forename: Howard E
authors.initials: HE
authors.lastname: Rockette
authors.forename: Marie
authors.initials: M
authors.lastname: Ganott
authors.forename: Christiane
authors.initials: C
authors.lastname: Hakim
authors.forename: Lara
authors.initials: L
authors.lastname: Hardesty
authors.forename: William R
authors.initials: WR
authors.lastname: Poller
authors.forename: Ratan
authors.initials: R
authors.lastname: Shah
authors.forename: Luisa
authors.initials: L
authors.lastname: Wallace
mesh_terms: D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D016208:Databases, Factual; D042241:Early Diagnosis; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D008403:Mass Screening / Q000379:methods*; D011446:Prospective Studies; D011857:Radiographic Image Interpretation, Computer-Assisted