Literature DB >> 12933460

Improvement in sensitivity of screening mammography with computer-aided detection: a multiinstitutional trial.

Rachel F Brem1, Janet Baum, Mary Lechner, Stuart Kaplan, Stuart Souders, L Gill Naul, Jeff Hoffmeister.   

Abstract

OBJECTIVE: Our study evaluated radiologist detection of breast cancer using a computer-aided detection system.
MATERIALS AND METHODS: Three radiologists reviewed 377 screening mammograms interpreted as showing normal or benign findings 9-24 months before cancer diagnosis from 17 of the 18 participating centers. In 313 cases, study radiologists recommended additional mammographic evaluation. In 177 cases, the area warranting additional workup precisely correlated with the subsequently diagnosed cancer. These 177 missed cancers were evaluated with computer-aided detection. The proportion of radiologists identifying the missed cancers was used to determine radiologist sensitivity without computer-aided detection.
RESULTS: The study radiologists determined that 123 of the 377 missed cancer cases warranted workup. Therefore, 123 additional cancers cases could have been found. The calculated radiologist sensitivity without computer-aided detection was therefore 75.4% (377 / [377 + 123]). Similarly, using the performance of the system on the missed cancers, we estimated that 80 (65.0%) of these 123 missed cancer cases would have been identified with the use of computer-aided detection. Consequently, the estimated sensitivity of radiologists using computer-aided detection was 91.4% ([377 + 80] / [377 + 123])-resulting in a 21.2% ([91.4% / 75.4%] - 1) increase in radiologist sensitivity with computer-aided detection.
CONCLUSION: Use of the computer-aided detection system significantly improved the detection of breast cancer by increasing radiologist sensitivity by 21.2%. Therefore, for every 100,000 women with breast cancer identified without the use of computer-aided detection, an estimated additional 21,200 cancers would be found with the use of computer-aided detection.

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Year:  2003        PMID: 12933460     DOI: 10.2214/ajr.181.3.1810687

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  33 in total

1.  An interactive system for computer-aided diagnosis of breast masses.

Authors:  Xingwei Wang; Lihua Li; Wei Liu; Weidong Xu; Dror Lederman; Bin Zheng
Journal:  J Digit Imaging       Date:  2012-10       Impact factor: 4.056

2.  Computer-aided detection of breast masses on full field digital mammograms.

Authors:  Jun Wei; Berkman Sahiner; Lubomir M Hadjiiski; Heang-Ping Chan; Nicholas Petrick; Mark A Helvie; Marilyn A Roubidoux; Jun Ge; Chuan Zhou
Journal:  Med Phys       Date:  2005-09       Impact factor: 4.071

3.  Impact of breast density on computer-aided detection in full-field digital mammography.

Authors:  Silvia Obenauer; Christian Sohns; Carola Werner; Eckhardt Grabbe
Journal:  J Digit Imaging       Date:  2006-09       Impact factor: 4.056

4.  Computer-aided detection system for clustered microcalcifications: comparison of performance on full-field digital mammograms and digitized screen-film mammograms.

Authors:  Jun Ge; Lubomir M Hadjiiski; Berkman Sahiner; Jun Wei; Mark A Helvie; Chuan Zhou; Heang-Ping Chan
Journal:  Phys Med Biol       Date:  2007-01-23       Impact factor: 3.609

5.  Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis.

Authors:  Jonathan L Jesneck; Loren W Nolte; Jay A Baker; Carey E Floyd; Joseph Y Lo
Journal:  Med Phys       Date:  2006-08       Impact factor: 4.071

6.  Bilateral analysis based false positive reduction for computer-aided mass detection.

Authors:  Yi-Ta Wu; Jun Wei; Lubomir M Hadjiiski; Berkman Sahiner; Chuan Zhou; Jun Ge; Jiazheng Shi; Yiheng Zhang; Heang-Ping Chan
Journal:  Med Phys       Date:  2007-08       Impact factor: 4.071

7.  Interactive computer-aided diagnosis of breast masses: computerized selection of visually similar image sets from a reference library.

Authors:  Bin Zheng; Claudia Mello-Thoms; Xiao-Hui Wang; Gordon S Abrams; Jules H Sumkin; Denise M Chough; Marie A Ganott; Amy Lu; David Gur
Journal:  Acad Radiol       Date:  2007-08       Impact factor: 3.173

Review 8.  Incorporating new imaging models in breast cancer management.

Authors:  Denise H Reddy; Ellen B Mendelson
Journal:  Curr Treat Options Oncol       Date:  2005-03

9.  Evaluating the effect of image preprocessing on an information-theoretic CAD system in mammography.

Authors:  Georgia D Tourassi; Robert Ike; Swatee Singh; Brian Harrawood
Journal:  Acad Radiol       Date:  2008-05       Impact factor: 3.173

Review 10.  State of the art of current modalities for the diagnosis of breast lesions.

Authors:  Cosimo Di Maggio
Journal:  Eur J Nucl Med Mol Imaging       Date:  2004-04-15       Impact factor: 9.236

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