The relationship between anatomic noise and volumetric breast density for digital mammography

Purpose: The appearance of parenchymal/stromal patterns in mammography have been characterized as having a Wiener power spectrum with an inverse power-law shape described by the exponential parameter, beta. The amount of fibroglandular tissue, which can be quantified in terms of volumetric breast density (VBD), influences the texture and appearance of the patterns formed in a mammogram. Here, a large study is performed to investigate the variations in beta in a clinical population and to indicate the relationship between beta and breast density. Methods: From a set of 2686 cranio-caudal normal screening mammograms, the parameter beta was extracted from log-log fits to the Wiener spectrum over the range 0.15-1 min(-1). The Wiener spectrum was calculated from regions of interest in the compression paddle contact region of the breast. An in-house computer program, Cumulus V, was used to extract the volumetric breast density and identify the compression paddle contact regions of the breast. The Wiener spectra were calculated with and without modulation transfer function (MTF) correction to determine the impact of VBD on the intrinsic anatomic noise. Results: The mean volumetric breast density was 25.5% (+/- 12.6%) over all images. The mean beta following a MTF correction which decreased the beta slightly (approximate to-0.08) was found to be 2.87. Varying the maximum of the spatial frequency range of the fits from 0.7 to 1.0, 1.25 or 1.5 mm(-1) showing small decreases in the result, although the effect of the quantum noise power component on reducing beta was clearly observed at 1.5 mm(-1). Conclusions: The texture parameter, beta, was found to increase with VBD at low volumetric breast densities with an apparent leveling off at higher densities. The relationship between beta and VBD measured here can be used to create probabilistic models for computer simulations of detectability. As breast density is a known risk predictor for breast cancer, the correlation between beta and VBD suggests that beta may provide predictive information and this will be investigated in the future. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4736422]