Literature DB >> 14764891

Computer-aided detection output on 172 subtle findings on normal mammograms previously obtained in women with breast cancer detected at follow-up screening mammography.

Debra M Ikeda1, Robyn L Birdwell, Kathryn F O'Shaughnessy, Edward A Sickles, R James Brenner.   

Abstract

PURPOSE: To evaluate, by using a computer-aided detection (CAD) program, the nonspecific findings on normal screening mammograms obtained in women in whom breast cancer was later detected at follow-up screening mammography.
MATERIALS AND METHODS: Four hundred ninety-three mammogram pairs-an initial negative screening mammogram and a subsequently obtained screening mammogram showing cancer-were collected. The mean interval between examinations was 14.6 months. In 169 cases, in which 172 cancers were later depicted, findings on the initial mammogram were subtle enough that either none or only one or two of five blinded radiologists recommended screening recall. On the initial negative mammograms, of the 172 areas where cancer later developed, 137 (80%) had subtle nonspecific findings and were retrospectively judged as having a benign or normal appearance. The mammograms with these subtle findings were evaluated with a commercially available CAD program, and the numbers of CAD marks on these nonspecific findings were analyzed.
RESULTS: Of the 172 cancers, 129 (75%) were invasive and 43 (25%) were ductal carcinoma in situ. The CAD program marked 72 (42%) of the 172 findings that subsequently developed into cancer: 24 (29%) of 82 findings recalled by none, 25 (49%) of 51 findings recalled by one, and 23 (59%) of 39 findings recalled by two of the five radiologists. Among the 137 areas with nonspecific normal or benign findings, 41 (30%) areas where cancer subsequently developed were marked by the CAD program.
CONCLUSION: A subset of cancers have perceptible but nonspecific mammographic findings that may be marked by a CAD program, even when the findings do not warrant recall as judged at blinded and unblinded radiologist review. The authors believe failure to act on such nonspecific but CAD-marked findings prospectively does not constitute interpretation below a reasonable standard of care. Copyright RSNA, 2004

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Year:  2004        PMID: 14764891     DOI: 10.1148/radiol.2303030254

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


  8 in total

1.  Dual system approach to computer-aided detection of breast masses on mammograms.

Authors:  Jun Wei; Heang-Ping Chan; Berkman Sahiner; Lubomir M Hadjiiski; Mark A Helvie; Marilyn A Roubidoux; Chuan Zhou; Jun Ge
Journal:  Med Phys       Date:  2006-11       Impact factor: 4.071

2.  Computer-aided detection of architectural distortion in prior mammograms of interval cancer.

Authors:  Rangaraj M Rangayyan; Shantanu Banik; J E Leo Desautels
Journal:  J Digit Imaging       Date:  2010-02-02       Impact factor: 4.056

Review 3.  Mobile Mammography Services and Underserved Women.

Authors:  Usha Trivedi; Toma S Omofoye; Cindy Marquez; Callie R Sullivan; Diane M Benson; Gary J Whitman
Journal:  Diagnostics (Basel)       Date:  2022-04-05

Review 4.  Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives.

Authors:  Krzysztof J Geras; Ritse M Mann; Linda Moy
Journal:  Radiology       Date:  2019-09-24       Impact factor: 11.105

5.  True detection versus "accidental" detection of small lung cancer by a computer-aided detection (CAD) program on chest radiographs.

Authors:  Feng Li; Roger Engelmann; Kunio Doi; Heber Macmahon
Journal:  J Digit Imaging       Date:  2009-05-07       Impact factor: 4.056

Review 6.  [Applications of Artificial Intelligence in Mammography from a Development and Validation Perspective].

Authors:  Ki Hwan Kim; Sang Hyup Lee
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2021-01-31

7.  International evaluation of an AI system for breast cancer screening.

Authors:  Scott Mayer McKinney; Marcin Sieniek; Varun Godbole; Jonathan Godwin; Natasha Antropova; Hutan Ashrafian; Trevor Back; Mary Chesus; Greg S Corrado; Ara Darzi; Mozziyar Etemadi; Florencia Garcia-Vicente; Fiona J Gilbert; Mark Halling-Brown; Demis Hassabis; Sunny Jansen; Alan Karthikesalingam; Christopher J Kelly; Dominic King; Joseph R Ledsam; David Melnick; Hormuz Mostofi; Lily Peng; Joshua Jay Reicher; Bernardino Romera-Paredes; Richard Sidebottom; Mustafa Suleyman; Daniel Tse; Kenneth C Young; Jeffrey De Fauw; Shravya Shetty
Journal:  Nature       Date:  2020-01-01       Impact factor: 49.962

8.  Features of Undiagnosed Breast Cancers at Screening Breast MR Imaging and Potential Utility of Computer-Aided Evaluation.

Authors:  Mirinae Seo; Nariya Cho; Min Sun Bae; Hye Ryoung Koo; Won Hwa Kim; Su Hyun Lee; Ajung Chu
Journal:  Korean J Radiol       Date:  2016-01-06       Impact factor: 3.500

  8 in total

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