The relationship between anatomic noise and volumetric breast density for digital mammography.
OBJECTIVE
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, β. 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 β in a clinical population and to indicate the relationship between β and breast density.


METHODS
From a set of 2686 cranio-caudal normal screening mammograms, the parameter β was extracted from log-log fits to the Wiener spectrum over the range 0.15-1 mm(-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 β following a MTF correction which decreased the β slightly (≈-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 β was clearly observed at 1.5 mm(-1).


CONCLUSIONS
The texture parameter, β, was found to increase with VBD at low volumetric breast densities with an apparent leveling off at higher densities. The relationship between β 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 β and VBD suggests that β may provide predictive information and this will be investigated in the future.
Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada. james.mainprize@sunnybrook.ca
James G
JG
Mainprize
Albert H
AH
Tyson
Martin J
MJ
Yaffe
D000273:Adipose Tissue / Q000473:pathology; D000465:Algorithms; D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000175:diagnosis; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D015233:Models, Statistical; D009132:Muscles / Q000473:pathology; D011336:Probability; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results