Mammographic density. Measurement of mammographic density

Abstract

Mammographic density has been strongly associated with increased risk of breast cancer. Furthermore, density is inversely correlated with the accuracy of mammography and, therefore, a measurement of density conveys information about the difficulty of detecting cancer in a mammogram. Initial methods for assessing mammographic density were entirely subjective and qualitative; however, in the past few years methods have been developed to provide more objective and quantitative density measurements. Research is now underway to create and validate techniques for volumetric measurement of density. It is also possible to measure breast density with other imaging modalities, such as ultrasound and MRI, which do not require the use of ionizing radiation and may, therefore, be more suitable for use in young women or where it is desirable to perform measurements more frequently. In this article, the techniques for measurement of density are reviewed and some consideration is given to their strengths and limitations.

Figure 1

A six-category system for classifying mammographic density. The categories describe the fraction of fibroglandular tissue in the breast as judged by an observer and are: (a) 0, (b) <10%, (c) 10–25%, (d) 26–50%, (e) 51–75%, (f) >75%. Reproduced from [1] with permission from American Association for Cancer Research.

Figure 2

Linear X-ray attenuation coefficients of fat and fibroglandular tissue in the breast plotted versus X-ray energy. Values for samples of breast tumors are also shown. Reproduced from [51] with permission from IOP Publishing Ltd.

Figure 3

The user interface for the interactive thresholding method for determination of mammographic density. (a) The digitized mammogram is displayed on the computer screen and a threshold is selected by the operator to segment the breast from the surrounding background. (b) A second threshold is set to identify the regions of density. The algorithm indicates these pixels by a white overlay.

Figure 4

Illustrates the limitations of setting a single threshold value to segment a mammogram for measurement of density. (a) Aerial view of mountains in the South Island of New Zealand. The altitude of the snow line varies so that a single value is not adequate to separate the snow-covered (dense) from bare (fatty) regions. (b) A schematic illustration of this problem. The edge and density brightness thresholds are denoted by the horizontal dashed lines Because of the reduction in thickness of the breast near the periphery, the brightness of a region of dense tissue in the mammogram (between the two vertical dashed lines) falls below the density threshold and so is excluded from the measurement. Similarly, fatty tissue in an area of the breast that is thicker than average can be inappropriately registered as dense tissue.

Figure 5

Schematic representation of image acquisition in breast tomosynthesis.

Figure 6

An empirical approach to calibration of a mammography system for volumetric measurement of density. (a) "Staircase" calibration tool. It is composed of a range of thicknesses of breast tissue equivalent plastics. On each step, the composition mimics fat, fibroglandular tissue and 30:70, 50:50, and 70:30 combinations of the two. (b) Radiograph of the calibration tool. (c) Calibration surface created from the radiograph in (b).

Figure 7

Characteristic curve of a screen-film mammography image receptor. There is an approximately linear relationship between optical density of the processed film and the logarithm of relative X-ray exposure, but only over a limited region of exposure.