Literature DB >> 20889111

How widely is computer-aided detection used in screening and diagnostic mammography?

Vijay M Rao1, David C Levin, Laurence Parker, Barbara Cavanaugh, Andrea J Frangos, Jonathan H Sunshine.   

Abstract

PURPOSE: The aim of this study was to determine how widely computer-aided detection (CAD) is used in screening and diagnostic mammography and to see if there are differences between hospital facilities and private offices.
METHODS: The nationwide Medicare Part B fee-for-service databases for 2004 to 2008 were used. The Current Procedural Terminology(®) codes for screening and diagnostic mammography (both digital and screen film) and the CAD add-on codes were selected. Procedure volume was compared for screening vs diagnostic mammography and for hospital facilities vs private offices.
RESULTS: From 2004 to 2008, Medicare screening mammography volume increased slightly from 5,728,419 to 5,827,326 (+2%), but the use of screening CAD increased from 2,257,434 to 4,305,595 (+91%). By 2008, CAD was used in 74% of all screening mammographic studies. During this same time period, the Medicare volume of diagnostic mammography declined slightly from 1,835,700 to 1,682,026 (-8%), but the use of diagnostic CAD increased from 360,483 to 845,461 (+135%). By 2008, CAD was used in 50% of all diagnostic mammographic studies. In hospital facilities in 2008, CAD was used in 70% of all screening mammographic studies, compared with 81% in private offices. For diagnostic mammography in 2008, CAD was used in 48% in hospitals, compared with 55% in private offices.
CONCLUSION: Despite some operational drawbacks to using CAD, radiologists have embraced it in an effort to improve cancer detection. Its use has grown rapidly, and in 2008, it was used in three-quarters of all screening mammographic studies and half of all diagnostic mammographic studies. Women undergoing either screening or diagnostic mammography are more likely to receive CAD if they go to a private office than if they go to a hospital facility, although the differences are not great.
Copyright © 2010 American College of Radiology. Published by Elsevier Inc. All rights reserved.

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Mesh:

Year:  2010        PMID: 20889111     DOI: 10.1016/j.jacr.2010.05.019

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  30 in total

1.  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

2.  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

3.  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

4.  Radiological technologists' performance for the detection of malignant microcalcifications in digital mammograms without and with a computer-aided detection system.

Authors:  Rie Tanaka; Miho Takamori; Yoshikazu Uchiyama; Junji Shiraishi
Journal:  J Med Imaging (Bellingham)       Date:  2015-05-27

5.  Utilization and Cost of Mammography Screening Among Commercially Insured Women 50 to 64 Years of Age in the United States, 2012-2016.

Authors:  Jaya S Khushalani; Donatus U Ekwueme; Thomas B Richards; Susan A Sabatino; Gery P Guy; Yuanhui Zhang; Florence Tangka
Journal:  J Womens Health (Larchmt)       Date:  2019-10-15       Impact factor: 2.681

Review 6.  Breast cancer screening: an evidence-based update.

Authors:  Mackenzie S Fuller; Christoph I Lee; Joann G Elmore
Journal:  Med Clin North Am       Date:  2015-03-05       Impact factor: 5.456

7.  Using breast radiographers' reports as a second opinion for radiologists' readings of microcalcifications in digital mammography.

Authors:  R Tanaka; M Takamori; Y Uchiyama; R M Nishikawa; J Shiraishi
Journal:  Br J Radiol       Date:  2014-12-23       Impact factor: 3.039

8.  Analog Computer-Aided Detection (CAD) information can be more effective than binary marks.

Authors:  Corbin A Cunningham; Trafton Drew; Jeremy M Wolfe
Journal:  Atten Percept Psychophys       Date:  2017-02       Impact factor: 2.199

9.  The Rebirth of CAD: How Is Modern AI Different from the CAD We Know?

Authors:  Luke Oakden-Rayner
Journal:  Radiol Artif Intell       Date:  2019-05-29

10.  Short-term outcomes of screening mammography using computer-aided detection: a population-based study of medicare enrollees.

Authors:  Joshua J Fenton; Guibo Xing; Joann G Elmore; Heejung Bang; Steven L Chen; Karen K Lindfors; Laura-Mae Baldwin
Journal:  Ann Intern Med       Date:  2013-04-16       Impact factor: 25.391

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