Literature DB >> 11522419

Computed assisted detection of interval breast cancers.

K Moberg1, N Bjurstam, B Wilczek, L Rostgård, E Egge, C Muren.   

Abstract

OBJECTIVES: To examine interval cancer detection rate for a system of computer assisted detection (CAD) and its influence on radiologists' sensitivity/specificity in a screen-like retrospective review situation.
MATERIALS AND METHODS: Three screening radiologists reviewed previous screen images of 59 interval cancers mixed with other screening mammograms (ratio 1:5) and non-mixed. Mixed interval cases were interpreted both without and with aid of CAD.
RESULTS: CAD detected a number of 14 interval cancers while the three radiologists detected 17, 12 and 11 without and 16, 10 and 13 with CAD. Although CAD specificity was low (38%) no reduction in radiologists' specificity occurred using CAD (73%, 82% and 89% without and 78%, 90% and 92% with CAD). Non-mixed reading increased radiologists' detection rate to 21, 17 and 19 interval cancers respectively.
CONCLUSION: Despite sufficiently high sensitivity for CAD alone no increase in radiologist sensitivity (or decrease in specificity) occurred with CAD. Improving CAD specificity, with unaffectedly high sensitivity, should make radiologists more inclined to revise interpretations according to CAD. The potential sensitivity increase, noted when using CAD as a double reader, could be realised in this way.

Entities:  

Mesh:

Year:  2001        PMID: 11522419     DOI: 10.1016/s0720-048x(01)00291-1

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  6 in total

Review 1.  CAD for mammography: the technique, results, current role and further developments.

Authors:  Ansgar Malich; Dorothee R Fischer; Joachim Böttcher
Journal:  Eur Radiol       Date:  2006-01-17       Impact factor: 5.315

Review 2.  Computer-aided diagnosis in medical imaging: historical review, current status and future potential.

Authors:  Kunio Doi
Journal:  Comput Med Imaging Graph       Date:  2007-03-08       Impact factor: 4.790

Review 3.  Automation bias: a systematic review of frequency, effect mediators, and mitigators.

Authors:  Kate Goddard; Abdul Roudsari; Jeremy C Wyatt
Journal:  J Am Med Inform Assoc       Date:  2011-06-16       Impact factor: 4.497

4.  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 5.  Is single reading with computer-aided detection (CAD) as good as double reading in mammography screening? A systematic review.

Authors:  Edward Azavedo; Sophia Zackrisson; Ingegerd Mejàre; Marianne Heibert Arnlind
Journal:  BMC Med Imaging       Date:  2012-07-24       Impact factor: 1.930

6.  Variable size computer-aided detection prompts and mammography film reader decisions.

Authors:  Fiona J Gilbert; Susan M Astley; Caroline Rm Boggis; Magnus A McGee; Pamela M Griffiths; Stephen W Duffy; Olorunsola F Agbaje; Maureen Gc Gillan; Mary Wilson; Anil K Jain; Nicola Barr; Ursula M Beetles; Miriam A Griffiths; Jill Johnson; Rita M Roberts; Heather E Deans; Karen A Duncan; Geeta Iyengar
Journal:  Breast Cancer Res       Date:  2008-08-25       Impact factor: 6.466

  6 in total

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