Literature DB >> 10572847

Observer variability in cancer detection during routine repeat (incident) mammographic screening in a study of two versus one view mammography.

R G Blanks1, M G Wallis, R M Given-Wilson.   

Abstract

OBJECTIVE: To examine the reasons for observer variability of cancer detection using one and two view mammography at incident (subsequent) screening and determine whether false negative results (non-recall of a cancer) are due to failure to detect the associated features(s) of the cancer on the mammogram, or misinterpretation of the observed feature(s) as not indicative of malignancy.
SETTING: A random selection of cancers (invasive and in situ) seen as incident cases during the second screening round (January 1994-January 1997) in the South West London Breast Screening Service were used. This service uses two view mammography and double reading with arbitration by a third or further readers for all screens.
METHODS: Mammograms of cases were mixed with those of controls in a 1:2 ratio in two test sets. Eleven experienced film readers, each reading both test sets, took part in the study. Initially the oblique view only was read, then, additionally, the craniocaudal view. Previous films were available to the readers. Data on abnormalities noted on the films and probability of recall were recorded and analysed.
RESULTS: 387 valid readings of 36 cancers (30 invasive and six ductal carcinoma in situ) were made by 11 readers. The overall sensitivity increased from 79% with one view to 85% with two views. For invasive cancers < 10 mm the sensitivity was 71% with one view, but increased to 85% with two views. Recall of individual cancers by the readers varied substantially. With one view 15 (50%) of the 30 invasive cancers were recalled by all 11 readers, increasing to 18 (60%) with two views. Of the invasive cancers not recalled by all 11 readers, there was considerable disagreement, particularly for the smaller cancers. With one view 69% of invasive cancers < 10 mm were correctly marked on the proforma compared with 87% with two views. Invasive cancers > 10 mm were almost all marked on the proforma with one or two views. For invasive cancers, the misinterpreted feature that did not lead to recall was most commonly an asymmetry (42%), whereas for in situ cancers it was calcifications (67%). The finding of an irregular mass was the least misinterpreted feature.
CONCLUSION: The study showed that of those invasive cancers detected at routine repeat screening by a programme using two view mammography and double reading with arbitration, at least 50% could be described as "difficult" (for example, "minimal" signs) to recall using the single reading of one view, even under "favourable" study conditions with two normal subjects per case. The finding that at least 87% of invasive cancers < 10 mm are detected (marked on the proforma) with two views, but only 69% with the one view, suggests that for single reading of mammograms with one view the detection of small invasive cancers is a major problem. This problem is helped by the second view. For invasive cancers > or = 10 mm, interpretation (benign or malignant) rather than detection (under these study conditions) was the major cause of recall failure. The most common signs to be misinterpreted were calcifications and asymmetries; once visualised an irregular mass was least likely to be misinterpreted. This study provides evidence that detection and interpretation of most invasive cancers is improved by increasing the number of views, and by increasing the number of readers.

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Mesh:

Year:  1999        PMID: 10572847     DOI: 10.1136/jms.6.3.152

Source DB:  PubMed          Journal:  J Med Screen        ISSN: 0969-1413            Impact factor:   2.136


  11 in total

1.  Standalone computer-aided detection compared to radiologists' performance for the detection of mammographic masses.

Authors:  Rianne Hupse; Maurice Samulski; Marc Lobbes; Ard den Heeten; Mechli W Imhof-Tas; David Beijerinck; Ruud Pijnappel; Carla Boetes; Nico Karssemeijer
Journal:  Eur Radiol       Date:  2012-07-08       Impact factor: 5.315

Review 2.  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 3.  Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.

Authors:  Maryellen L Giger; Heang-Ping Chan; John Boone
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

4.  Computerized analysis of coronary artery disease: performance evaluation of segmentation and tracking of coronary arteries in CT angiograms.

Authors:  Chuan Zhou; Heang-Ping Chan; Aamer Chughtai; Jean Kuriakose; Prachi Agarwal; Ella A Kazerooni; Lubomir M Hadjiiski; Smita Patel; Jun Wei
Journal:  Med Phys       Date:  2014-08       Impact factor: 4.071

5.  Applying a new bilateral mammographic density segmentation method to improve accuracy of breast cancer risk prediction.

Authors:  Shiju Yan; Yunzhi Wang; Faranak Aghaei; Yuchen Qiu; Bin Zheng
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-07-19       Impact factor: 2.924

6.  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

7.  Bilateral mammographic density asymmetry and breast cancer risk: a preliminary assessment.

Authors:  Bin Zheng; Jules H Sumkin; Margarita L Zuley; Xingwei Wang; Amy H Klym; David Gur
Journal:  Eur J Radiol       Date:  2012-05-12       Impact factor: 3.528

8.  Automated coronary artery tree extraction in coronary CT angiography using a multiscale enhancement and dynamic balloon tracking (MSCAR-DBT) method.

Authors:  Chuan Zhou; Heang-Ping Chan; Aamer Chughtai; Smita Patel; Lubomir M Hadjiiski; Jun Wei; Ella A Kazerooni
Journal:  Comput Med Imaging Graph       Date:  2011-05-20       Impact factor: 4.790

9.  Automatic multiscale enhancement and segmentation of pulmonary vessels in CT pulmonary angiography images for CAD applications.

Authors:  Chuan Zhou; Heang-Ping Chan; Berkman Sahiner; Lubomir M Hadjiiski; Aamer Chughtai; Smita Patel; Jun Wei; Jun Ge; Philip N Cascade; Ella A Kazerooni
Journal:  Med Phys       Date:  2007-12       Impact factor: 4.071

10.  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

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