title: Impact of computer-aided detection systems on radiologist accuracy with digital mammography.
abstract: OBJECTIVE
  The purpose of this study was to assess the impact of computer-aided detection (CAD) systems on the performance of radiologists with digital mammograms acquired during the Digital Mammographic Imaging Screening Trial (DMIST).
  
  
  METHODS
  Only those DMIST cases with proven cancer status by biopsy or 1-year follow-up that had available digital images were included in this multireader, multicase ROC study. Two commercially available CAD systems for digital mammography were used: iCAD SecondLook, version 1.4; and R2 ImageChecker Cenova, version 1.0. Fourteen radiologists interpreted, without and with CAD, a set of 300 cases (150 cancer, 150 benign or normal) on the iCAD SecondLook system, and 15 radiologists interpreted a different set of 300 cases (150 cancer, 150 benign or normal) on the R2 ImageChecker Cenova system.
  
  
  RESULTS
  The average AUC was 0.71 (95% CI, 0.66-0.76) without and 0.72 (95% CI, 0.67-0.77) with the iCAD system (p = 0.07). Similarly, the average AUC was 0.71 (95% CI, 0.66-0.76) without and 0.72 (95% CI 0.67-0.77) with the R2 system (p = 0.08). Sensitivity and specificity differences without and with CAD for both systems also were not significant.
  
  
  CONCLUSIONS
  Radiologists in our studies rarely changed their diagnostic decisions after the addition of CAD. The application of CAD had no statistically significant effect on radiologist AUC, sensitivity, or specificity performance with digital mammograms from DMIST.
authors.affiliation: 1 Department of Radiology and Radiological Science, Medical University of South Carolina, 96 Jonathan Lucas St, Ste 210, MSC 323, Charleston, SC 29425.
authors.forename: Elodia B
authors.initials: EB
authors.lastname: Cole
authors.forename: Zheng
authors.initials: Z
authors.lastname: Zhang
authors.forename: Helga S
authors.initials: HS
authors.lastname: Marques
authors.forename: R
authors.initials: R
authors.lastname: Edward Hendrick
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Yaffe
authors.forename: Etta D
authors.initials: ED
authors.lastname: Pisano
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000818:Animals; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology*; D002170:Canada / Q000453:epidemiology; D002415:Cats; D055088:Early Detection of Cancer / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008327:Mammography / Q000706:statistics & numerical data*; D008875:Middle Aged; D015588:Observer Variation; D015995:Prevalence; D011361:Professional Competence / Q000706:statistics & numerical data*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011871:Radiology / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D014481:United States / Q000453:epidemiology
keywords: AUC; computer-aided detection; mammography; sensitivity; specificity