Statistical analysis of mammographic breast composition measurements: towards a quantitative measure of relative breast cancer risk

Abstract

Objective: A number of studies have identified the relationship between the visual appearance of high breast density at mammography and an increased risk of breast cancer. With the advent of digital mammography and the promise of routine measurements of parameters associated with breast composition, the possibility arises of using breast composition in a quantitative manner to predict relative breast cancer risk. Previous measurements have shown that the average proportion of glandular and adipose tissue within the breast varies with both age and breast size. In order to be able to identify individual women with an unusually high volume of glandular tissue, it will therefore be necessary to make comparisons with a disease-free population matched for age and breast size. Methods: A large number of breast glandular thickness measurements were analysed to investigate the statistics of breast composition across a disease-free population as a test of a suitable methodology for relative risk estimation. The large data set is also used to revisit the trends in breast composition used in the current UK method of breast radiation dosimetry. Results: It is demonstrated that a non-linear transformation can be used to produce normal statistical distributions, suitable for producing a standardised ''Z-score'' for breast composition. Conclusion: A standard ''Z-score'' approach to identify women with unusually glandular breasts is recommended and so provide a basis for cancer risk estimations. It is generally accepted that a link exists between socalled ''breast density'', i.e. the proportion and pattern of bright areas in a mammographic image denoting glandular tissue, and the relative risk of breast cancer. The field has been reviewed by Harvey and Bovbjerg [1], who identified 12 studies in which quantitative methods of measuring breast density showed a moderate to strong positive association with breast cancer risk. The risk of breast cancer for women with increased breast density in most of these studies is four to six times that for women with primarily adipose breasts; a relative risk greater than most traditional risk factors such as nulliparity and early menarche. With the advent of digital mammography and the promise of replacing visual assessment of breast density with quantitative measurements of parameters associated with breast composition, the possibility arises of using breast composition to predict relative breast cancer risk. In this article, a large number of breast glandular thickness measurements are analysed to investigate the statistics of breast composition across a diseasefree population as a test of a suitable methodology for relative risk estimation.Despite the structural and functional complexity of the female breast, in terms of its mammographic appearance, and for the purposes of constructing a simple cancer risk model, it is convenient to regard the breast as being composed of two tissue components, adipose and glandular. These two components can be defined in terms of their X-ray attenuation prop...

Assessment of breast density in women from different regions of Brazil

“…2016 ). The glandular tissue proportion varies according to the breast size and patient age ( Kotre 2011 ). Moreover, some works have shown that the ethnicity of the women and their geographical location are also factors relevant to breast density, which are associated with socio-economic conditions and lifestyle ( Aitken et al.…”

“…Some authors have suggested that alternative imaging tests should be used for dense breasts, such as ultrasound or digital breast tomosynthesis (DBT), since these are not as affected by the amount of glandular tissue (Boyd et al 2007; Ko et al 2014;Vilaverde et al 2016). The glandular tissue proportion varies according to the breast size and patient age (Kotre 2011). Moreover, some works have shown that the ethnicity of the women and their geographical location are also factors relevant to breast density, which are associated with socio-economic conditions and lifestyle (Aitken et al 2010;Moore et al 2020;Perry et al 2008;Van der Waal et al 2015;Viel and Rymzhanova 2012;Zulfiqar et al 2011).…”

Study Review on the Role of Image Analysis on Improving Diagnostic and Therapeutic Breast Cancer Outcomes

“…Figure 1 below. Kotre CJ [5] consents that "It is demonstrated that a nonlinear transformation can be used to produce normal statistical distributions, suitable for producing a standardized "Z-score" for breast composition. A standard "Z-score" approach to identify women with unusually glandular breasts is recommended and so provide a basis for cancer risk estimations".…”