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Women’s features and inter-/intra-rater agreement on mammographic density assessment in full-field digital mammograms (DDM-SPAIN)

  • Epidemiology
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

An Erratum to this article was published on 07 November 2012

Abstract

Measurement of mammographic density (MD), one of the leading risk factors for breast cancer, still relies on subjective assessment. However, the consistency of MD measurement in full-digital mammograms has yet to be evaluated. We studied inter- and intra-rater agreement with respect to estimation of breast density in full-digital mammograms, and tested whether any of the women’s characteristics might have some influence on them. After an initial training period, three experienced radiologists estimated MD using Boyd scale in a left breast cranio-caudal mammogram of 1,431 women, recruited at three Spanish screening centres. A subgroup of 50 randomly selected images was read twice to estimate short-term intra-rater agreement. In addition, a reading of 1,428 of the images, performed 2 years before by one rater, was used to estimate long-term intra-rater agreement. Pair-wise weighted kappas with 95% bootstrap confidence intervals were calculated. Dichotomous variables were defined to identify mammograms in which any rater disagreed with other raters or with his/her own assessment, respectively. The association between disagreement and women’s characteristics was tested using multivariate mixed logistic models, including centre as a random-effects term, and taking into account repeated measures when required. All quadratic-weighted kappa values for inter- and intra-rater agreement were excellent (higher than 0.80). None of the studied women’s features, i.e. body mass index, brassiere size, menopause, nulliparity, lactation or current hormonal therapy, was associated with higher risk of inter- or intra-rater disagreement. However, raters differed significantly more in images that were classified in the higher-density MD categories, and disagreement in intra-rater assessment was also lower in low-density mammograms. The reliability of MD assessment in full-field digital mammograms is comparable to that for original or digitised images. The reassuring lack of association between subjects’ MD-related characteristics and agreement suggests that bias from this source is unlikely.

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Abbreviations

MD:

Mammographic density

BMI:

Body mass index

References

  1. Boyd NF, Guo H, Martin LJ, Sun L, Stone J, Fishell E, Jong RA, Hislop G, Chiarelli A, Minkin S, Yaffe MJ (2007) Mammographic density and the risk and detection of breast cancer. N Engl J Med 356:227–236

    Article  CAS  PubMed  Google Scholar 

  2. Stone J, Dite GS, Gunasekara A, English DR, McCredie MR, Giles GG, Cawson JN, Hegele RA, Chiarelli AM, Yaffe MJ, Boyd NF, Hopper JL (2006) The heritability of mammographically dense and nondense breast tissue. Cancer Epidemiol Biomarkers Prev 15:612–617

    Article  PubMed  Google Scholar 

  3. Boyd NF, Dite GS, Stone J, Gunasekara A, English DR, McCredie MR, Giles GG, Tritchler D, Chiarelli A, Yaffe MJ, Hopper JL (2002) Heritability of mammographic density, a risk factor for breast cancer. N Engl J Med 347:886–894

    Article  PubMed  Google Scholar 

  4. El Bastawissi AY, White E, Mandelson MT, Taplin S (2001) Variation in mammographic breast density by race. Ann Epidemiol 11:257–263

    Article  CAS  PubMed  Google Scholar 

  5. El Bastawissi AY, White E, Mandelson MT, Taplin SH (2000) Reproductive and hormonal factors associated with mammographic breast density by age (United States). Cancer Causes Control 11:955–963

    Article  CAS  PubMed  Google Scholar 

  6. Vacek PM, Geller BM (2004) A prospective study of breast cancer risk using routine mammographic breast density measurements. Cancer Epidemiol Biomarkers Prev 13:715–722

    PubMed  Google Scholar 

  7. Kelemen LE, Pankratz VS, Sellers TA, Brandt KR, Wang A, Janney C, Fredericksen ZS, Cerhan JR, Vachon CM (2008) Age-specific trends in mammographic density: the Minnesota Breast Cancer Family Study. Am J Epidemiol 167:1027–1036

    Article  PubMed  Google Scholar 

  8. Cuzick J, Warwick J, Pinney E, Warren RM, Duffy SW (2004) Tamoxifen and breast density in women at increased risk of breast cancer. J Natl Cancer Inst 96:621–628

    Article  CAS  PubMed  Google Scholar 

  9. Boyd N, Martin L, Stone J, Little L, Minkin S, Yaffe M (2002) A longitudinal study of the effects of menopause on mammographic features. Cancer Epidemiol Biomarkers Prev 11:1048–1053

    PubMed  Google Scholar 

  10. Stone J, Gunasekara A, Martin LJ, Yaffe M, Minkin S, Boyd NF (2003) The detection of change in mammographic density. Cancer Epidemiol Biomarkers Prev 12:625–630

    CAS  PubMed  Google Scholar 

  11. McCormack VA, dos SS I, De Stavola BL, Perry N, Vinnicombe S, Swerdlow AJ, Hardy R, Kuh D (2003) Life-course body size and perimenopausal mammographic parenchymal patterns in the MRC 1946 British birth cohort. Br J Cancer 89:852–859

    Article  CAS  PubMed  Google Scholar 

  12. American College of Radiology (1993) Breast imaging reporting and data system (BIRADS). American College of Radiology, Reston, Va

    Google Scholar 

  13. Boyd NF, Byng JW, Jong RA, Fishell EK, Little LE, Miller AB, Lockwood GA, Tritchler DL, Yaffe MJ (1995) Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study. J Natl Cancer Inst 87:670–675

    Article  CAS  PubMed  Google Scholar 

  14. Byng JW, Boyd NF, Fishell E, Jong RA, Yaffe MJ (1994) The quantitative analysis of mammographic densities. Phys Med Biol 39:1629–1638

    Article  CAS  PubMed  Google Scholar 

  15. Ciatto S, Houssami N, Apruzzese A, Bassetti E, Brancato B, Carozzi F, Catarzi S, Lamberini MP, Marcelli G, Pellizzoni R, Pesce B, Risso G, Russo F, Scorsolini A (2005) Categorizing breast mammographic density: intra- and interobserver reproducibility of BI-RADS density categories. Breast 14:269–275

    Article  CAS  PubMed  Google Scholar 

  16. Gao J, Warren R, Warren-Forward H, Forbes JF (2008) Reproducibility of visual assessment on mammographic density. Breast Cancer Res Treat 108:121–127

    Article  PubMed  Google Scholar 

  17. Ooms EA, Zonderland HM, Eijkemans MJ, Kriege M, Mahdavian DB, Burger CW, Ansink AC (2007) Mammography: interobserver variability in breast density assessment. Breast 16:568–576

    Article  CAS  PubMed  Google Scholar 

  18. Tagliafico A, Tagliafico G, Tosto S, Chiesa F, Martinoli C, Derchi LE, Calabrese M (2009) Mammographic density estimation: comparison among BI-RADS categories, a semi-automated software and a fully automated one. Breast 18:35–40

    Article  PubMed  Google Scholar 

  19. Lee-Han H, Cooke G, Boyd NF (1995) Quantitative evaluation of mammographic densities: a comparison of methods of assessment. Eur J Cancer Prev 4:285–292

    Article  CAS  PubMed  Google Scholar 

  20. Nicholson BT, LoRusso AP, Smolkin M, Bovbjerg VE, Petroni GR, Harvey JA (2006) Accuracy of assigned BI-RADS breast density category definitions. Acad Radiol 13:1143–1149

    Article  PubMed  Google Scholar 

  21. Berg WA, Campassi C, Langenberg P, Sexton MJ (2000) Breast imaging reporting and data system: inter- and intraobserver variability in feature analysis and final assessment. AJR Am J Roentgenol 174:1769–1777

    CAS  PubMed  Google Scholar 

  22. Benichou J, Byrne C, Capece LA, Carroll LE, Hurt-Mullen K, Pee DY, Salane M, Schairer C, Gail MH (2003) Secular stability and reliability of measurements of the percentage of dense tissue on mammograms. Cancer Detect Prev 27:266–274

    Article  PubMed  Google Scholar 

  23. Jong R, Fishell E, Little L, Lockwood G, Boyd NF (1996) Mammographic signs of potential relevance to breast cancer risk: the agreement of radiologists’ classification. Eur J Cancer Prev 5:281–286

    Article  CAS  PubMed  Google Scholar 

  24. Kerlikowske K, Grady D, Barclay J, Frankel SD, Ominsky SH, Sickles EA, Ernster V (1998) Variability and accuracy in mammographic interpretation using the American College of Radiology Breast Imaging Reporting and Data System. J Natl Cancer Inst 90:1801–1809

    Article  CAS  PubMed  Google Scholar 

  25. Antonio AL, Crespi CM (2010) Predictors of interobserver agreement in breast imaging using the Breast Imaging Reporting and Data System. Breast Cancer Res Treat 120:539–546

    Article  PubMed  Google Scholar 

  26. Garrido-Estepa M, Ruiz-Perales F, Miranda J, Ascunce N, Gonzalez-Roman I, Sanchez-Contador C, Santamarina C, Moreo P, Vidal C, Peris M, Moreno MP, Vaquez-Carrete JA, Collado-Garcia F, Casanova F, Ederra M, Salas D, Pollan M (2010) Evaluation of mammographic density patterns: reproducibility and concordance among scales. BMC Cancer 10:485

    PubMed  Google Scholar 

  27. Cabanes A, Pastor-Barriuso R, Garcia-Lopez M, Pedraz-Pingarron C, Sanchez-Contador C, Vazquez Carrete JA, Moreno MP, Vidal C, Salas D, Miranda-Garcia J, Peris M, Moreo P, Santamarina MC, Collado-Garcia F, Gonzalez-Roman I, Ascunce N, Pollan M (2011) Alcohol, tobacco, and mammographic density: a population-based study. Breast Cancer Res Treat 129(1):135–147

    Article  PubMed  Google Scholar 

  28. Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Measur 20:37–46

    Article  Google Scholar 

  29. Cohen J (1968) Weighted kappa: nominal scale agreement with provision for scaled disagreement or partial credit. Psychol Bull 70:213–220

    Article  CAS  PubMed  Google Scholar 

  30. Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174

    Article  CAS  PubMed  Google Scholar 

  31. Gelman A, Hill J (2007) Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, Cambridge

    Google Scholar 

  32. Caldwell CB, Stapleton SJ, Holdsworth DW, Jong RA, Weiser WJ, Cooke G, Yaffe MJ (1990) Characterisation of mammographic parenchymal pattern by fractal dimension. Phys Med Biol 35:235–247

    Article  CAS  PubMed  Google Scholar 

  33. Jeffreys M, Warren R, Smith GD, Gunnell D (2003) Breast density: agreement of measures from film and digital image. Br J Radiol 76:561–563

    Article  CAS  PubMed  Google Scholar 

  34. Fischmann A, Siegmann KC, Wersebe A, Claussen CD, Muller-Schimpfle M (2005) Comparison of full-field digital mammography and film-screen mammography: image quality and lesion detection. Br J Radiol 78:312–315

    Article  CAS  PubMed  Google Scholar 

  35. Venta LA, Hendrick RE, Adler YT, DeLeon P, Mengoni PM, Scharl AM, Comstock CE, Hansen L, Kay N, Coveler A, Cutter G (2001) Rates and causes of disagreement in interpretation of full-field digital mammography and film-screen mammography in a diagnostic setting. AJR Am J Roentgenol 176:1241–1248

    CAS  PubMed  Google Scholar 

  36. Maclure M, Willett WC (1987) Misinterpretation and misuse of the kappa-statistic. Am J Epidemiol 126:161–169

    Article  CAS  PubMed  Google Scholar 

  37. Cicchetti DV, Allison T (1971) A new procedure for assessing reliability of scoring EEG sleep recordings. Am J EEG Technol 11:101–110

    Google Scholar 

  38. Fleiss JL, Cohen J (1973) Equivalence of weighted kappa and intraclass correlation coefficient as measures of reliability. Educ Psychol Measur 33:613–619

    Article  Google Scholar 

  39. Yaffe MJ, Mainprize JG, Jong RA (2008) Technical developments in mammography. Health Phys 95:599–611

    Article  CAS  PubMed  Google Scholar 

  40. Tice JA, Feldman MD (2008) Full-field digital mammography compared with screen-film mammography in the detection of breast cancer: rays of light through DMIST or more fog? Breast Cancer Res Treat 107:157–165

    Article  PubMed  Google Scholar 

  41. Vinnicombe S, Pinto Pereira SM, McCormack VA, Shiel S, Perry N, dos Santos Silva I (2009) Full-field digital versus screen-film mammography: comparison within the UK breast screening program and systematic review of published data. Radiology 251:347–358

    Article  PubMed  Google Scholar 

  42. Del Turco MR, Mantellini P, Ciatto S, Bonardi R, Martinelli F, Lazzari B, Houssami N (2007) Full-field digital versus screen-film mammography: comparative accuracy in concurrent screening cohorts. AJR Am J Roentgenol 189:860–866

    Article  PubMed  Google Scholar 

  43. Boyd NF (2011) Tamoxifen, mammographic density, and breast cancer prevention. J Natl Cancer Inst 103:704–705

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

This study was supported by research grants from Fundación Gent per Gent (EDEMAC Project); grants FIS PI09/1230 & PI060386 from Spain’s Health Research Fund (Fondo de Investigación Sanitaria); the EPY 1306/06 Collaboration Agreement between Astra-Zeneca and the Carlos III Institute of Health (Instituto de Salud Carlos III); and a grant from the Spanish Federation of Breast Cancer Patients (FECMA). We thank the participants of the study DDM-Spain for their contribution to breast cancer research. We wish also to acknowledge the collaboration from other DDM-Spain members: Pilar Moreo, Pilar Moreno and Soledad Abad (Aragón); Francisca Collado and Magdalena Moyá (Baleares); Isabel González, Carmen Pedraz and Francisco Casanova (Castilla-León); Mercé Peris (Cataluña); Carmen Santamariña, José Antonio Vázquez Carrete, Montserrat Corujo and Ana Belén Fernández (Galicia); Nieves Ascunce, María Ederra, Milagros García and Ana Barcos (Navarra); Manuela Alcaraz, Jesus Vioque (C. Valenciana); Virginia Lope, Nuria Aragonés, Anna Cabanes (Madrid).

Conflict of interest

The authors declare that they have no competing interests.

Author information

Authors and Affiliations

  1. Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Instituto de Salud Carlos III, Sinesio Delgado 6, 28029, Madrid, Spain

    Beatriz Pérez-Gómez & Marina Pollán

  2. Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Madrid, Spain

    Beatriz Pérez-Gómez & Marina Pollán

  3. Breast Cancer Screening Programme, General Directorate Public Health, Valencia, Spain

    Franciso Ruiz, Inmaculada Martínez, María Casals, Josefa Miranda & Dolores Salas

  4. Centro Superior de Investigación en Salud Pública (CSISP), Valencia, Spain

    Josefa Miranda & Dolores Salas

  5. Balearic Islands Breast Cancer Screening Programme, Health Promotion for Women and Childhood. General Directorate Public Health and Participation, Regional Authority of Health and Consumer Affairs, Balearic Islands, Spain

    Carmen Sánchez-Contador

  6. Cancer Prevention and Control Unit, Catalan Institute of Oncology (ICO), Barcelona, Spain

    Carmen Vidal

  7. Universidad Politécnica de Valencia, Valencia, Spain

    Rafael Llobet

Authors
  1. Beatriz Pérez-Gómez
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  2. Franciso Ruiz
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  3. Inmaculada Martínez
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  4. María Casals
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  6. Carmen Sánchez-Contador
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  7. Carmen Vidal
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  8. Rafael Llobet
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  9. Marina Pollán
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  10. Dolores Salas
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Correspondence to Beatriz Pérez-Gómez.

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Pérez-Gómez, B., Ruiz, F., Martínez, I. et al. Women’s features and inter-/intra-rater agreement on mammographic density assessment in full-field digital mammograms (DDM-SPAIN). Breast Cancer Res Treat 132, 287–295 (2012). https://doi.org/10.1007/s10549-011-1833-3

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