Literature DB >> 11895300

A pilot evaluation of the R2 image checker system and users' response in the detection of interval breast cancers on previous screening films.

L Garvican1, S Field.   

Abstract

AIM: Breast screening radiologists are under considerable pressure to maximize cancer detection and minimize the number of interval cancers. This study used screening films, previously reported as normal, taken before the development of an interval cancer. The aim was to determine the sensitivity and specificity of the R2 Image Checker System and the responses of users in detecting abnormalities in these previous films.
MATERIALS AND METHODS: The first R2 Image Checker System in the U.K. was installed in the Canterbury Assessment Centre for evaluation purposes. System performance was compared with the standard protocol for assessing interval cancers used in the NHS Breast Screening Programme (NHSBSP) Three readers examined the previous films blind before switching on R2 and compared the prompts generated with the location of the subsequent interval cancer.
RESULTS: The previous screening films for 104 cases generated 134 R2 prompts on the subsequent cancer side and 109 on the non-cancer side. Readers classified 29 cancers as false-negative or minimal signs and R2 correctly prompted in 15 of these cases (52%). At least one reader rejected the correct prompt in five cases.
CONCLUSION: From this preliminary study it appears that R2 overprompts normal areas and underprompts some cancers in these difficult cases. A full multi-centre evaluation is needed to assess the possible contribution of R2 to the NHSBSP.

Entities:  

Mesh:

Year:  2001        PMID: 11895300     DOI: 10.1053/crad.2001.0776

Source DB:  PubMed          Journal:  Clin Radiol        ISSN: 0009-9260            Impact factor:   2.350


  3 in total

1.  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

2.  Using computer-aided detection in mammography as a decision support.

Authors:  Maurice Samulski; Rianne Hupse; Carla Boetes; Roel D M Mus; Gerard J den Heeten; Nico Karssemeijer
Journal:  Eur Radiol       Date:  2010-06-09       Impact factor: 5.315

3.  Visually assessed breast density, breast cancer risk and the importance of the craniocaudal view.

Authors:  Stephen W Duffy; Iris D Nagtegaal; Susan M Astley; Maureen G C Gillan; Magnus A McGee; Caroline R M Boggis; Mary Wilson; Ursula M Beetles; Miriam A Griffiths; Anil K Jain; Jill Johnson; Rita Roberts; Heather Deans; Karen A Duncan; Geeta Iyengar; Pam M Griffiths; Jane Warwick; Jack Cuzick; Fiona J Gilbert
Journal:  Breast Cancer Res       Date:  2008-07-23       Impact factor: 6.466

  3 in total

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