Literature DB >> 3711253

Observer variation in the classification of mammographic parenchymal patterns.

N F Boyd, C Wolfson, M Moskowitz, T Carlile, C Petitclerc, H A Ferri, E Fishell, A Gregoire, M Kiernan, J D Longley.   

Abstract

Wolfe has described different cancer risks associated with a classification of four patterns of the breast parenchyma on mammography, but there is however little information available on the ability of radiologists to agree on the classification of the different patterns. We have assessed inter-rater agreement on the assignment of films to one of the four mammographic patterns described by Wolfe. One hundred xeromammograms were selected, copied and distributed to 10 radiologists who were experts in mammography. Films were classified according to the presence or absence of several radiological signs, according to diagnosis and recommendation, and according to mammographic pattern. Agreement was assessed after correction for agreement expected by chance, using the Kappa statistic. In general, high levels of agreement were found for the classification of mammographic pattern. Agreement on the classification of mammographic pattern was substantially greater than agreement for any other feature of mammographic interpretation, including diagnosis and recommendation.

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Year:  1986        PMID: 3711253     DOI: 10.1016/0021-9681(86)90113-x

Source DB:  PubMed          Journal:  J Chronic Dis        ISSN: 0021-9681


  8 in total

1.  Interobserver agreement in breast radiological density attribution according to BI-RADS quantitative classification.

Authors:  D Bernardi; M Pellegrini; S Di Michele; P Tuttobene; C Fantò; M Valentini; M Gentilini; S Ciatto
Journal:  Radiol Med       Date:  2012-01-07       Impact factor: 3.469

2.  Methods for assessing and representing mammographic density: an analysis of 4 case-control studies.

Authors:  Christy G Woolcott; Shannon M Conroy; Chisato Nagata; Giske Ursin; Celine M Vachon; Martin J Yaffe; Ian S Pagano; Celia Byrne; Gertraud Maskarinec
Journal:  Am J Epidemiol       Date:  2013-10-11       Impact factor: 4.897

3.  Association between mammographic density and age-related lobular involution of the breast.

Authors:  Karthik Ghosh; Lynn C Hartmann; Carol Reynolds; Daniel W Visscher; Kathleen R Brandt; Robert A Vierkant; Christopher G Scott; Derek C Radisky; Thomas A Sellers; V Shane Pankratz; Celine M Vachon
Journal:  J Clin Oncol       Date:  2010-03-29       Impact factor: 44.544

4.  Reproducibility of BI-RADS breast density measures among community radiologists: a prospective cohort study.

Authors:  Mary C Spayne; Charlotte C Gard; Joan Skelly; Diana L Miglioretti; Pamela M Vacek; Berta M Geller
Journal:  Breast J       Date:  2012-05-21       Impact factor: 2.431

5.  Independent association of lobular involution and mammographic breast density with breast cancer risk.

Authors:  Karthik Ghosh; Celine M Vachon; V Shane Pankratz; Robert A Vierkant; Stephanie S Anderson; Kathleen R Brandt; Daniel W Visscher; Carol Reynolds; Marlene H Frost; Lynn C Hartmann
Journal:  J Natl Cancer Inst       Date:  2010-10-29       Impact factor: 13.506

Review 6.  Review of imaging techniques for the diagnosis of breast cancer: a new role of prone scintimammography using technetium-99m sestamibi.

Authors:  I Khalkhali; I Mena; L Diggles
Journal:  Eur J Nucl Med       Date:  1994-04

7.  Textural classification of mammographic parenchymal patterns with the SONNET Selforganizing neural network.

Authors:  Daniel Howard; Simon C Roberts; Conor Ryan; Adrian Brezulianu
Journal:  J Biomed Biotechnol       Date:  2008

8.  Examining intra-rater and inter-rater response agreement: a medical chart abstraction study of a community-based asthma care program.

Authors:  Teresa To; Eileen Estrabillo; Chengning Wang; Lisa Cicutto
Journal:  BMC Med Res Methodol       Date:  2008-05-09       Impact factor: 4.615

  8 in total

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