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Published in: BMC Cancer 1/2010

Open Access 01-12-2010 | Research article

Evaluation of mammographic density patterns: reproducibility and concordance among scales

Authors: Macarena Garrido-Estepa, Francisco Ruiz-Perales, Josefa Miranda, Nieves Ascunce, Isabel González-Román, Carmen Sánchez-Contador, Carmen Santamariña, Pilar Moreo, Carmen Vidal, Mercé Peris, María P Moreno, Jose A Váquez-Carrete, Francisca Collado-García, Francisco Casanova, María Ederra, Dolores Salas, Marina Pollán, DDM-Spain

Published in: BMC Cancer | Issue 1/2010

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Abstract

Background

Increased mammographic breast density is a moderate risk factor for breast cancer. Different scales have been proposed for classifying mammographic density. This study sought to assess intra-rater agreement for the most widely used scales (Wolfe, Tabár, BI-RADS and Boyd) and compare them in terms of classifying mammograms as high- or low-density.

Methods

The study covered 3572 mammograms drawn from women included in the DDM-Spain study, carried-out in seven Spanish Autonomous Regions. Each mammogram was read by an expert radiologist and classified using the Wolfe, Tabár, BI-RADS and Boyd scales. In addition, 375 mammograms randomly selected were read a second time to estimate intra-rater agreement for each scale using the kappa statistic. Owing to the ordinal nature of the scales, weighted kappa was computed. The entire set of mammograms (3572) was used to calculate agreement among the different scales in classifying high/low-density patterns, with the kappa statistic being computed on a pair-wise basis. High density was defined as follows: percentage of dense tissue greater than 50% for the Boyd, "heterogeneously dense and extremely dense" categories for the BI-RADS, categories P2 and DY for the Wolfe, and categories IV and V for the Tabár scales.

Results

There was good agreement between the first and second reading, with weighted kappa values of 0.84 for Wolfe, 0.71 for Tabár, 0.90 for BI-RADS, and 0.92 for Boyd scale. Furthermore, there was substantial agreement among the different scales in classifying high- versus low-density patterns. Agreement was almost perfect between the quantitative scales, Boyd and BI-RADS, and good for those based on the observed pattern, i.e., Tabár and Wolfe (kappa 0.81). Agreement was lower when comparing a pattern-based (Wolfe or Tabár) versus a quantitative-based (BI-RADS or Boyd) scale. Moreover, the Wolfe and Tabár scales classified more mammograms in the high-risk group, 46.61 and 37.32% respectively, while this percentage was lower for the quantitative scales (21.89% for BI-RADS and 21.86% for Boyd).

Conclusions

Visual scales of mammographic density show a high reproducibility when appropriate training is provided. Their ability to distinguish between high and low risk render them useful for routine use by breast cancer screening programs. Quantitative-based scales are more specific than pattern-based scales in classifying populations in the high-risk group.
Appendix
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Literature
1.
go back to reference Cummings SR, Tice JA, Bauer S, Browner WS, Cuzick J, Ziv E, Vogel V, Shepherd J, Vachon C, Smith-Bindman R, Kerlikowske K: Prevention of Breast Cancer in Postmenopausal Women: Approaches to Estimating and Reducing Risk. J Natl Cancer Inst. 2009, 101: 384-398. 10.1093/jnci/djp018.CrossRefPubMedPubMedCentral Cummings SR, Tice JA, Bauer S, Browner WS, Cuzick J, Ziv E, Vogel V, Shepherd J, Vachon C, Smith-Bindman R, Kerlikowske K: Prevention of Breast Cancer in Postmenopausal Women: Approaches to Estimating and Reducing Risk. J Natl Cancer Inst. 2009, 101: 384-398. 10.1093/jnci/djp018.CrossRefPubMedPubMedCentral
2.
go back to reference Boyd NF, Rommens JM, Vogt K, Lee V, Hopper JL, Yaffe MJ, Paterson AD: Mammographic breast density as an intermediate phenotype for breast cancer. Lancet Oncol. 2005, 6: 798-808. 10.1016/S1470-2045(05)70390-9.CrossRefPubMed Boyd NF, Rommens JM, Vogt K, Lee V, Hopper JL, Yaffe MJ, Paterson AD: Mammographic breast density as an intermediate phenotype for breast cancer. Lancet Oncol. 2005, 6: 798-808. 10.1016/S1470-2045(05)70390-9.CrossRefPubMed
3.
go back to reference Byrne C, Schairer C, Wolfe J, Parekh N, Salane M, Brinton L, Hoover R, Haile R: Mammographic features and breast cancer risk: effects with time, age, and menopause status. J Natl Cancer Inst. 1995, 87 (21): 1622-1629. 10.1093/jnci/87.21.1622.CrossRefPubMed Byrne C, Schairer C, Wolfe J, Parekh N, Salane M, Brinton L, Hoover R, Haile R: Mammographic features and breast cancer risk: effects with time, age, and menopause status. J Natl Cancer Inst. 1995, 87 (21): 1622-1629. 10.1093/jnci/87.21.1622.CrossRefPubMed
4.
go back to reference Boyd NF, Byng JW, Jong RA, Fishell EK, Little LE, Miller AB, Lockwood GA, Tritchler DL, Yaffe MJ: Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study. J Natl Cancer Inst. 1995, 87: 670-675. 10.1093/jnci/87.9.670.CrossRefPubMed Boyd NF, Byng JW, Jong RA, Fishell EK, Little LE, Miller AB, Lockwood GA, Tritchler DL, Yaffe MJ: Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study. J Natl Cancer Inst. 1995, 87: 670-675. 10.1093/jnci/87.9.670.CrossRefPubMed
5.
go back to reference Harvey JA, Bovbjerg VE: Quantitative assessment of mammographic breast density: relationship with breast cancer risk. Radiology. 2004, 230: 29-41. 10.1148/radiol.2301020870.CrossRefPubMed Harvey JA, Bovbjerg VE: Quantitative assessment of mammographic breast density: relationship with breast cancer risk. Radiology. 2004, 230: 29-41. 10.1148/radiol.2301020870.CrossRefPubMed
6.
go back to reference Wolfe JN: Breast patterns as an index of risk for developing breast cancer. AJR Am J Roentgenol. 1976, 126: 1130-1137.CrossRefPubMed Wolfe JN: Breast patterns as an index of risk for developing breast cancer. AJR Am J Roentgenol. 1976, 126: 1130-1137.CrossRefPubMed
7.
go back to reference Gram IT, Funkhouser E, Tabar L: The Tabar classification of mammographic parenchymal patterns. Eur J Radiol. 1997, 24: 131-136. 10.1016/S0720-048X(96)01138-2.CrossRefPubMed Gram IT, Funkhouser E, Tabar L: The Tabar classification of mammographic parenchymal patterns. Eur J Radiol. 1997, 24: 131-136. 10.1016/S0720-048X(96)01138-2.CrossRefPubMed
8.
go back to reference American College of Radiology: ACR Breast imaging reporting and data system. 1993, Reston, VA: American College of Radiology American College of Radiology: ACR Breast imaging reporting and data system. 1993, Reston, VA: American College of Radiology
9.
go back to reference American College of Radiology: ACR breast imaging reporting and data system atlas. 2003, Reston, VA: American College of Radiology American College of Radiology: ACR breast imaging reporting and data system atlas. 2003, Reston, VA: American College of Radiology
10.
go back to reference Chang YH, Wang XH, Hardesty LA, Chang TS, Poller WR, Good WF, Gur D: Computerized assessment of tissue composition on digitized mammograms. Acad Radiol. 2002, 9: 899-905. 10.1016/S1076-6332(03)80459-2.CrossRefPubMed Chang YH, Wang XH, Hardesty LA, Chang TS, Poller WR, Good WF, Gur D: Computerized assessment of tissue composition on digitized mammograms. Acad Radiol. 2002, 9: 899-905. 10.1016/S1076-6332(03)80459-2.CrossRefPubMed
11.
go back to reference Byng JW, Yaffe MJ, Jong RA, Shumak RS, Lockwood GA, Tritchler DL, Boyd NF: Analysis of mammographic density and breast cancer risk from digitized mammograms. Radiographics. 1998, 18: 1587-1598.CrossRefPubMed Byng JW, Yaffe MJ, Jong RA, Shumak RS, Lockwood GA, Tritchler DL, Boyd NF: Analysis of mammographic density and breast cancer risk from digitized mammograms. Radiographics. 1998, 18: 1587-1598.CrossRefPubMed
12.
go back to reference Cohen J: A coefficient of agreement for nominal scales. Educ Psychol Meas. 1960, 20: 37-46. 10.1177/001316446002000104.CrossRef Cohen J: A coefficient of agreement for nominal scales. Educ Psychol Meas. 1960, 20: 37-46. 10.1177/001316446002000104.CrossRef
13.
go back to reference Reichenheim ME: Confidence intervals for the kappa statistic. The Stata Journal. 2004, 4: 421-428. Reichenheim ME: Confidence intervals for the kappa statistic. The Stata Journal. 2004, 4: 421-428.
14.
go back to reference Moskowitz M, Gartside P, McLaughlin C: Mammographic patterns as markers for high-risk benign breast disease and incident cancers. Radiology. 1980, 134: 293-295.CrossRefPubMed Moskowitz M, Gartside P, McLaughlin C: Mammographic patterns as markers for high-risk benign breast disease and incident cancers. Radiology. 1980, 134: 293-295.CrossRefPubMed
15.
go back to reference Boyd NF, O'Sullivan B, Campbell JE, Fishell E, Simor I, Cooke G, Germanson T: Bias and the association of mammographic parenchymal patterns with breast cancer. Br J Cancer. 1982, 45: 179-184.CrossRefPubMedPubMedCentral Boyd NF, O'Sullivan B, Campbell JE, Fishell E, Simor I, Cooke G, Germanson T: Bias and the association of mammographic parenchymal patterns with breast cancer. Br J Cancer. 1982, 45: 179-184.CrossRefPubMedPubMedCentral
16.
go back to reference Carlile T, Thompson DJ, Kopecky KJ, Gilbert FI, Krook PM, Present AJ, Russell HW, Threatt BA: Reproducibility and consistency in classification of breast parenchymal patterns. AJR Am J Roentgenol. 1983, 140: 1-7.CrossRefPubMed Carlile T, Thompson DJ, Kopecky KJ, Gilbert FI, Krook PM, Present AJ, Russell HW, Threatt BA: Reproducibility and consistency in classification of breast parenchymal patterns. AJR Am J Roentgenol. 1983, 140: 1-7.CrossRefPubMed
17.
go back to reference Toniolo P, Bleich AR, Beinart C, Koenig KL: Reproducibility of Wolfe's classification of mammographic parenchymal patterns. Prev Med. 1992, 21: 1-7. 10.1016/0091-7435(92)90001-X.CrossRefPubMed Toniolo P, Bleich AR, Beinart C, Koenig KL: Reproducibility of Wolfe's classification of mammographic parenchymal patterns. Prev Med. 1992, 21: 1-7. 10.1016/0091-7435(92)90001-X.CrossRefPubMed
18.
go back to reference Gao J, Warren R, Warren-Forward H, Forbes JF: Reproducibility of visual assessment on mammographic density. Breast Cancer Res Treat. 2008, 108: 121-127. 10.1007/s10549-007-9581-0.CrossRefPubMed Gao J, Warren R, Warren-Forward H, Forbes JF: Reproducibility of visual assessment on mammographic density. Breast Cancer Res Treat. 2008, 108: 121-127. 10.1007/s10549-007-9581-0.CrossRefPubMed
19.
go back to reference Jamal N, Ng KH, Looi LM, McLean D, Zulfiqar A, Tan SP, Liew WF, Shantini A, Ranganathan S: Quantitative assessment of breast density from digitized mammograms into Tabar's patterns. Phys Med Biol. 2006, 51: 5843-5857. 10.1088/0031-9155/51/22/008.CrossRefPubMed Jamal N, Ng KH, Looi LM, McLean D, Zulfiqar A, Tan SP, Liew WF, Shantini A, Ranganathan S: Quantitative assessment of breast density from digitized mammograms into Tabar's patterns. Phys Med Biol. 2006, 51: 5843-5857. 10.1088/0031-9155/51/22/008.CrossRefPubMed
20.
go back to reference Berg WA, Campassi C, Langenberg P, Sexton MJ: Breast Imaging Reporting and Data System: inter- and intraobserver variability in feature analysis and final assessment. AJR Am J Roentgenol. 2000, 174: 1769-1777.CrossRefPubMed Berg WA, Campassi C, Langenberg P, Sexton MJ: Breast Imaging Reporting and Data System: inter- and intraobserver variability in feature analysis and final assessment. AJR Am J Roentgenol. 2000, 174: 1769-1777.CrossRefPubMed
21.
go back to reference Kerlikowske K, Grady D, Barclay J, Frankel SD, Ominsky SH, Sickles EA, Ernster V: Variability and accuracy in mammographic interpretation using the American College of Radiology Breast Imaging Reporting and Data System. J Natl Cancer Inst. 1998, 90: 1801-1809. 10.1093/jnci/90.23.1801.CrossRefPubMed Kerlikowske K, Grady D, Barclay J, Frankel SD, Ominsky SH, Sickles EA, Ernster V: Variability and accuracy in mammographic interpretation using the American College of Radiology Breast Imaging Reporting and Data System. J Natl Cancer Inst. 1998, 90: 1801-1809. 10.1093/jnci/90.23.1801.CrossRefPubMed
22.
go back to reference Jong R, Fishell E, Little L, Lockwood G, Boyd NF: Mammographic signs of potential relevance to breast cancer risk: the agreement of radiologists' classification. Eur J Cancer Prev. 1996, 5: 281-286. 10.1097/00008469-199608000-00008.CrossRefPubMed Jong R, Fishell E, Little L, Lockwood G, Boyd NF: Mammographic signs of potential relevance to breast cancer risk: the agreement of radiologists' classification. Eur J Cancer Prev. 1996, 5: 281-286. 10.1097/00008469-199608000-00008.CrossRefPubMed
23.
go back to reference Lee-Han H, Cooke G, Boyd NF: Quantitative evaluation of mammographic densities: a comparison of methods of assessment. Eur J Cancer Prev. 1995, 4: 285-292. 10.1097/00008469-199508000-00003.CrossRefPubMed Lee-Han H, Cooke G, Boyd NF: Quantitative evaluation of mammographic densities: a comparison of methods of assessment. Eur J Cancer Prev. 1995, 4: 285-292. 10.1097/00008469-199508000-00003.CrossRefPubMed
Metadata
Title
Evaluation of mammographic density patterns: reproducibility and concordance among scales
Authors
Macarena Garrido-Estepa
Francisco Ruiz-Perales
Josefa Miranda
Nieves Ascunce
Isabel González-Román
Carmen Sánchez-Contador
Carmen Santamariña
Pilar Moreo
Carmen Vidal
Mercé Peris
María P Moreno
Jose A Váquez-Carrete
Francisca Collado-García
Francisco Casanova
María Ederra
Dolores Salas
Marina Pollán
DDM-Spain
Publication date
01-12-2010
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2010
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/1471-2407-10-485

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