Literature DB >> 12888373

Use of previous screening mammograms to identify features indicating cases that would have a possible gain in prognosis following earlier detection.

M J M Broeders1, N C Onland-Moret, H J T M Rijken, J H C L Hendriks, A L M Verbeek, R Holland.   

Abstract

False-negative screening mammograms generally refer to breast cancers that were overlooked or misinterpreted at screening. An important question is whether earlier detection could have made a difference in the prognosis of the women concerned. We reviewed screening and diagnostic mammograms of 234 screen-detected and interval cancer cases (aged 44-84 years) diagnosed between 1991 and 1996 in the Nijmegen breast cancer screening programme. A lesion was visible on 117 (50%) of the screening mammograms prior to the diagnosis of breast cancer. Fifty-one out of the 117 cancers had poor prognostic characteristics at diagnosis (i.e. N+ and/or T2+) and could potentially have benefited from an earlier diagnosis ('possible gain'). The 'possible gain' cases were more often characterised by architectural distortion (29 vs. 10%; P=0.01) or a high-density mass (25 vs. 13%; P=0.06) on the mammogram prior to diagnosis than the 58 'no gain' cases. Our study shows that architectural distortion and non-spiculated high-density masses on the mammogram prior to diagnosis are associated with a possible gain in prognosis. Earlier detection of the carcinomas preceded by these signs may well have an impact on breast cancer mortality and thus warrant extra attention in radiological practice.

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Mesh:

Year:  2003        PMID: 12888373     DOI: 10.1016/s0959-8049(03)00311-3

Source DB:  PubMed          Journal:  Eur J Cancer        ISSN: 0959-8049            Impact factor:   9.162


  17 in total

1.  Measures of angular spread and entropy for the detection of architectural distortion in prior mammograms.

Authors:  Shantanu Banik; Rangaraj M Rangayyan; J E Leo Desautels
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-03-30       Impact factor: 2.924

2.  Detection of architectural distortion in prior mammograms via analysis of oriented patterns.

Authors:  Rangaraj M Rangayyan; Shantanu Banik; J E Leo Desautels
Journal:  J Vis Exp       Date:  2013-08-30       Impact factor: 1.355

3.  Gabor filters and phase portraits for the detection of architectural distortion in mammograms.

Authors:  Rangaraj M Rangayyan; Fábio J Ayres
Journal:  Med Biol Eng Comput       Date:  2006-08-11       Impact factor: 2.602

4.  Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms.

Authors:  Qi Guo; Jiaqing Shao; Virginie F Ruiz
Journal:  Int J Comput Assist Radiol Surg       Date:  2008-10-28       Impact factor: 2.924

5.  Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists.

Authors:  Alejandro Rodriguez-Ruiz; Kristina Lång; Albert Gubern-Merida; Mireille Broeders; Gisella Gennaro; Paola Clauser; Thomas H Helbich; Margarita Chevalier; Tao Tan; Thomas Mertelmeier; Matthew G Wallis; Ingvar Andersson; Sophia Zackrisson; Ritse M Mann; Ioannis Sechopoulos
Journal:  J Natl Cancer Inst       Date:  2019-09-01       Impact factor: 13.506

6.  Measures of divergence of oriented patterns for the detection of architectural distortion in prior mammograms.

Authors:  Rangaraj M Rangayyan; Shantanu Banik; Jayasree Chakraborty; Sudipta Mukhopadhyay; J E Leo Desautels
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-09-30       Impact factor: 2.924

Review 7.  Inositol phosphates in the environment.

Authors:  Benjamin L Turner; Michael J Papházy; Philip M Haygarth; Ian D McKelvie
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2002-04-29       Impact factor: 6.237

8.  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

9.  Differences in Breast Cancer Characteristics by Mammography Screening Participation or Non-Participation.

Authors:  Bettina Braun; Laura Khil; Joke Tio; Barbara Krause-Bergmann; Andrea Fuhs; Oliver Heidinger; Hans-Werner Hense
Journal:  Dtsch Arztebl Int       Date:  2018-08-06       Impact factor: 5.594

10.  Mammographic features and histopathological findings of interval breast cancers.

Authors:  S Hofvind; B Geller; P Skaane
Journal:  Acta Radiol       Date:  2008-11       Impact factor: 1.990

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