Literature DB >> 16990670

Single reading with computer-aided detection and double reading of screening mammograms in the United Kingdom National Breast Screening Program.

Fiona J Gilbert1, Susan M Astley, Magnus A McGee, Maureen G C Gillan, Caroline R M Boggis, Pamela M Griffiths, Stephen W Duffy.   

Abstract

PURPOSE: To retrospectively determine if the use of a computer-aided detection (CAD) system can improve the performance of single reading of screening mammograms to match that of double reading in the United Kingdom.
MATERIALS AND METHODS: Local research ethics committee approval was obtained; informed consent was not required. This study included a sample of 10 267 mammograms obtained in women aged 50 years or older who underwent routine screening at one of two breast screening centers in 1996. Mammograms that were double read in 1996 were randomly allocated to be re-read by eight different radiologists using CAD. The cancer detection and recall rates from double reading and single reading with CAD were compared. Statistical significance and confidence intervals were calculated with the McNemar test to account for the matched nature of the data.
RESULTS: Single reading with CAD led to a cancer detection rate that was significantly (P = .02) higher than that achieved with double reading: 6.5% more cancers were detected by means of single reading with CAD than by means of double reading. However, the recall rate was higher for single reading with CAD than for double reading (8.6% vs 6.5%, respectively; P < .001). This was equivalent to relative increases of 15% and 32% in the cancer detection and recall rates, respectively.
CONCLUSION: Single reading with CAD leads to an improved cancer detection rate and an increased recall rate. (c) RSNA, 2006.

Entities:  

Mesh:

Year:  2006        PMID: 16990670     DOI: 10.1148/radiol.2411051092

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  22 in total

Review 1.  Information technology conduit as a portal to circumvent the graveyard shift.

Authors:  Amar Gupta; Shawna Sando; Sairam Parthasarathy; Stuart F Quan
Journal:  J Clin Sleep Med       Date:  2010-04-15       Impact factor: 4.062

Review 2.  Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.

Authors:  Maryellen L Giger; Heang-Ping Chan; John Boone
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

3.  Novel computer-aided diagnosis algorithms on ultrasound image: effects on solid breast masses discrimination.

Authors:  Ying Wang; Hong Wang; Yanhui Guo; Chunping Ning; Bo Liu; H D Cheng; Jiawei Tian
Journal:  J Digit Imaging       Date:  2009-11-10       Impact factor: 4.056

4.  False positive marks on unsuspicious screening mammography with computer-aided detection.

Authors:  Mary C Mahoney; Karthikeyan Meganathan
Journal:  J Digit Imaging       Date:  2011-10       Impact factor: 4.056

Review 5.  Imaging-based screening: maximizing benefits and minimizing harms.

Authors:  Jessica C Germino; Joann G Elmore; Ruth C Carlos; Christoph I Lee
Journal:  Clin Imaging       Date:  2015-06-12       Impact factor: 1.605

6.  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

7.  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

8.  Improving the performance of computer-aided detection of subtle breast masses using an adaptive cueing method.

Authors:  Xingwei Wang; Lihua Li; Weidong Xu; Wei Liu; Dror Lederman; Bin Zheng
Journal:  Phys Med Biol       Date:  2012-01-21       Impact factor: 3.609

Review 9.  Microcalcification on mammography: approaches to interpretation and biopsy.

Authors:  Louise Wilkinson; Val Thomas; Nisha Sharma
Journal:  Br J Radiol       Date:  2016-10-17       Impact factor: 3.039

Review 10.  Needs assessment for next generation computer-aided mammography reference image databases and evaluation studies.

Authors:  Alexander Horsch; Alexander Hapfelmeier; Matthias Elter
Journal:  Int J Comput Assist Radiol Surg       Date:  2011-03-30       Impact factor: 2.924

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