Literature DB >> 17409321

Influence of computer-aided detection on performance of screening mammography.

Joshua J Fenton1, Stephen H Taplin, Patricia A Carney, Linn Abraham, Edward A Sickles, Carl D'Orsi, Eric A Berns, Gary Cutter, R Edward Hendrick, William E Barlow, Joann G Elmore.   

Abstract

BACKGROUND: Computer-aided detection identifies suspicious findings on mammograms to assist radiologists. Since the Food and Drug Administration approved the technology in 1998, it has been disseminated into practice, but its effect on the accuracy of interpretation is unclear.
METHODS: We determined the association between the use of computer-aided detection at mammography facilities and the performance of screening mammography from 1998 through 2002 at 43 facilities in three states. We had complete data for 222,135 women (a total of 429,345 mammograms), including 2351 women who received a diagnosis of breast cancer within 1 year after screening. We calculated the specificity, sensitivity, and positive predictive value of screening mammography with and without computer-aided detection, as well as the rates of biopsy and breast-cancer detection and the overall accuracy, measured as the area under the receiver-operating-characteristic (ROC) curve.
RESULTS: Seven facilities (16%) implemented computer-aided detection during the study period. Diagnostic specificity decreased from 90.2% before implementation to 87.2% after implementation (P<0.001), the positive predictive value decreased from 4.1% to 3.2% (P=0.01), and the rate of biopsy increased by 19.7% (P<0.001). The increase in sensitivity from 80.4% before implementation of computer-aided detection to 84.0% after implementation was not significant (P=0.32). The change in the cancer-detection rate (including invasive breast cancers and ductal carcinomas in situ) was not significant (4.15 cases per 1000 screening mammograms before implementation and 4.20 cases after implementation, P=0.90). Analyses of data from all 43 facilities showed that the use of computer-aided detection was associated with significantly lower overall accuracy than was nonuse (area under the ROC curve, 0.871 vs. 0.919; P=0.005).
CONCLUSIONS: The use of computer-aided detection is associated with reduced accuracy of interpretation of screening mammograms. The increased rate of biopsy with the use of computer-aided detection is not clearly associated with improved detection of invasive breast cancer. Copyright 2007 Massachusetts Medical Society.

Entities:  

Mesh:

Year:  2007        PMID: 17409321      PMCID: PMC3182841          DOI: 10.1056/NEJMoa066099

Source DB:  PubMed          Journal:  N Engl J Med        ISSN: 0028-4793            Impact factor:   91.245


  34 in total

1.  Radiologist detection of microcalcifications with and without computer-aided detection: a comparative study.

Authors:  R F Brem; J M Schoonjans
Journal:  Clin Radiol       Date:  2001-02       Impact factor: 2.350

2.  Mammographic characteristics of 115 missed cancers later detected with screening mammography and the potential utility of computer-aided detection.

Authors:  R L Birdwell; D M Ikeda; K F O'Shaughnessy; E A Sickles
Journal:  Radiology       Date:  2001-04       Impact factor: 11.105

3.  Computer-Aided Diagnosis of Breast Cancer on Mammograms.

Authors: 
Journal:  Breast Cancer       Date:  1997-12-25       Impact factor: 4.239

4.  Continuing screening mammography in women aged 70 to 79 years: impact on life expectancy and cost-effectiveness.

Authors:  K Kerlikowske; P Salzmann; K A Phillips; J A Cauley; S R Cummings
Journal:  JAMA       Date:  1999-12-08       Impact factor: 56.272

5.  Testing the effect of computer-assisted detection on interpretive performance in screening mammography.

Authors:  Stephen H Taplin; Carolyn M Rutter; Constance D Lehman
Journal:  AJR Am J Roentgenol       Date:  2006-12       Impact factor: 3.959

6.  Association between mammography timing and measures of screening performance in the United States.

Authors:  Bonnie C Yankaskas; Stephen H Taplin; Laura Ichikawa; Berta M Geller; Robert D Rosenberg; Patricia A Carney; Karla Kerlikowske; Rachel Ballard-Barbash; Gary R Cutter; William E Barlow
Journal:  Radiology       Date:  2005-02       Impact factor: 11.105

7.  Current realities of delivering mammography services in the community: do challenges with staffing and scheduling exist?

Authors:  Carl D'Orsi; Shin-Ping Tu; Connie Nakano; Patricia A Carney; Linn A Abraham; Stephen H Taplin; R Edward Hendrick; Gary R Cutter; Eric Berns; William E Barlow; Joann G Elmore
Journal:  Radiology       Date:  2005-03-29       Impact factor: 11.105

8.  Impact of computer-aided detection in a regional screening mammography program.

Authors:  Tommy E Cupples; Joan E Cunningham; James C Reynolds
Journal:  AJR Am J Roentgenol       Date:  2005-10       Impact factor: 3.959

9.  The natural history of low-grade ductal carcinoma in situ of the breast in women treated by biopsy only revealed over 30 years of long-term follow-up.

Authors:  Melinda E Sanders; Peggy A Schuyler; William D Dupont; David L Page
Journal:  Cancer       Date:  2005-06-15       Impact factor: 6.860

10.  Physician predictors of mammographic accuracy.

Authors:  Rebecca Smith-Bindman; Philip Chu; Diana L Miglioretti; Chris Quale; Robert D Rosenberg; Gary Cutter; Berta Geller; Peter Bacchetti; Edward A Sickles; Karla Kerlikowske
Journal:  J Natl Cancer Inst       Date:  2005-03-02       Impact factor: 13.506

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  140 in total

1.  Automatic detection of follicular regions in H&E images using iterative shape index.

Authors:  K Belkacem-Boussaid; S Samsi; G Lozanski; M N Gurcan
Journal:  Comput Med Imaging Graph       Date:  2011-04-20       Impact factor: 4.790

2.  Computer-aided detection of clustered microcalcifications in digital breast tomosynthesis: a 3D approach.

Authors:  Berkman Sahiner; Heang-Ping Chan; Lubomir M Hadjiiski; Mark A Helvie; Jun Wei; Chuan Zhou; Yao Lu
Journal:  Med Phys       Date:  2012-01       Impact factor: 4.071

3.  Standalone computer-aided detection compared to radiologists' performance for the detection of mammographic masses.

Authors:  Rianne Hupse; Maurice Samulski; Marc Lobbes; Ard den Heeten; Mechli W Imhof-Tas; David Beijerinck; Ruud Pijnappel; Carla Boetes; Nico Karssemeijer
Journal:  Eur Radiol       Date:  2012-07-08       Impact factor: 5.315

4.  Assessing operating characteristics of CAD algorithms in the absence of a gold standard.

Authors:  Kingshuk Roy Choudhury; David S Paik; Chin A Yi; Sandy Napel; Justus Roos; Geoffrey D Rubin
Journal:  Med Phys       Date:  2010-04       Impact factor: 4.071

5.  BI-RADS data should not be used to estimate ROC curves.

Authors:  Yulei Jiang; Charles E Metz
Journal:  Radiology       Date:  2010-07       Impact factor: 11.105

6.  Exploring the potential of context-sensitive CADe in screening mammography.

Authors:  Georgia D Tourassi; Maciej A Mazurowski; Brian P Harrawood; Elizabeth A Krupinski
Journal:  Med Phys       Date:  2010-11       Impact factor: 4.071

7.  Time trends in radiologists' interpretive performance at screening mammography from the community-based Breast Cancer Surveillance Consortium, 1996-2004.

Authors:  Laura E Ichikawa; William E Barlow; Melissa L Anderson; Stephen H Taplin; Berta M Geller; R James Brenner
Journal:  Radiology       Date:  2010-05-26       Impact factor: 11.105

8.  External validation of a publicly available computer assisted diagnostic tool for mammographic mass lesions with two high prevalence research datasets.

Authors:  Matthias Benndorf; Elizabeth S Burnside; Christoph Herda; Mathias Langer; Elmar Kotter
Journal:  Med Phys       Date:  2015-08       Impact factor: 4.071

9.  Image toggling saves time in mammography.

Authors:  Trafton Drew; Avi M Aizenman; Matthew B Thompson; Mark D Kovacs; Michael Trambert; Murray A Reicher; Jeremy M Wolfe
Journal:  J Med Imaging (Bellingham)       Date:  2015-10-12

10.  Differentiation of malignant and benign breast lesions using magnetization transfer imaging and dynamic contrast-enhanced MRI.

Authors:  Samantha L Heller; Linda Moy; Sherlin Lavianlivi; Melanie Moccaldi; Sungheon Kim
Journal:  J Magn Reson Imaging       Date:  2012-10-23       Impact factor: 4.813

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