Garrido-Estepa et al. BMC Cancer 2010, 10:485 http://www.biomedcentral.com/1471-2407/10/485 to 6.0, with most studies yielding an odds ratio of 4.0 or greater [5]. Recently, measurement of breast density has been proposed as an intermediate phenotype for breast cancer, useful in epidemiologic, clinical and genetic stu- dies [2]. The first classification was introduced by Wolfe in 1976 [6], based on qualitative and quantitative criteria of breast parenchyma to describe four different patterns. Attempts to increase reproducibility entailed the crea- tion of quantitative methods, the most widely used being that proposed by Boyd, which uses a semi-quanti- tative score of six categories [4]. In 1997, Tabár pro- posed a modification of Wolfe’s classification, with five categories based on anatomic-mammographic correla- tions [7]. Another classification, Breast Imaging Report- ing and Data System (BI-RADS), was developed in the USA to standardize mammography reports, reduce con- fusion in the interpretation of breast images, and facili- tate the monitoring of results. First edition of BI-RADS classification described four categories of density patterns, but later 2003 edition define them based on quantitative criteria as a quartiles of density percentages [8,9]. At the end of the nineties computer-assisted measurements of breast density have been developed to calculate percentages of mammo- graphic density but there are some limitations to the technique, such as the digitization of the images, time consumed, need for specific training, difficulty in mixing analog and digital mammograms, and the fact that such techniques continue to be non-volumetric [10,11]. At present, this computer-assisted method is not routinely used in radiology units, and has not been validated for digital mammograms. This present study sought to: assess the intra-rater reproducibility of the different visual scales of classifica- tion; and compare agreement among the Wolfe, Tabár, BI-RADS and Boyd scales in terms of classification into high- versus low-density groups. Lastly, we explored the variability of the Wolfe and Tabár qualitative pattern- based classifications with respect to the six categories of the Boyd semiquantitative scale. Methods Subjects and mammograms We used data drawn from the “Determinants of Density in Mammography in Spain” (DDM-Spain) study. This was a cross-sectional study which aimed to identify genetic, reproductive and lifestyle characteristics asso- ciated with mammographic patterns/densities that might enhance the risk of developing breast cancer. Briefly, women aged 45 and over who attended the regional Breast Cancer Screening Programs at the recruiting cen- ters established in Barcelona, Burgos, Corunna (Coruña), Palma de Mallorca, Pamplona, Valencia and Zaragoza from September 2006 through June 2007 were invited to Page 2 of 8 participate in the study. Exclusion criteria of DDM- Spain included the following: women not born in Spain; evidence of previous breast or ovarian cancer; inability to answer the questionnaire; physical impairment to per- form the mammogram; and previous breast surgery or implants. The study was reviewed and approved by the Bioethics Committee of the Instituto de Salud Carlos III (Madrid) and all subjects provided written consent. The intended sample size was 500 women per center, imply- ing a total of 3500 women. The final sample consisted of 3572 women (range 496 to 534 per center). The aver- age participation rate was 74.5%, ranging from 64.7% in Corunna to 84.0% in Zaragoza. Mammogram quality at each of these centers had been explored by a pilot study using 25 mammograms per center. As the cranio-caudal (CC) projection posed fewer technical problems, we decided to evaluate mammographic density using the CC projection from the left breast. Of the total included in the study, 2040 mammograms were in analog format (those from Burgos, Corunna, Pamplona and Zaragoza) and the remaining 1532 were in digital format (those from Barcelona, Palma de Mal- lorca and Valencia). Measurements Mammographic density was evaluated by a single experienced radiologist (Dr. Francisco Ruíz-Perales). All mammograms were classified using the Wolfe, Tabár, BI-RADS and Boyd scales: analog mammograms were read in negatoscope (view box), and digital mammo- grams on a computer screen. Every mammogram (in total 3572) was read randomly in four different stages to prevent recall bias until every scale was completed to study comparability among scales. To obtain a subsample of twice-read mammograms to explore intra-observer agreement each of the participant centers chose a set of 50-60 consecutive images using a random number between the first and last mammo- grams as initial. If the random number proposed was too near the last, the reading continued from the first. The second reading of a total of 375 mammograms was performed with the same procedure than first beginning within 1 to 66 days after the end of the previous reading to prevent recall bias. Statistical methods Intra-observer agreement was evaluated using the kappa coefficient, since it requires no assumption about cor- rect categorization and includes correction for the degree of agreement that would be expected by chance alone [12]. Due to the ordinal nature of the scales, weighted kappa was also calculated. Wolfe scale is compound of four categories defined as N1, P1, P2 and DY while Tabár proposed five different