Design and validation of a mathematical breast phantom for contrast-enhanced digital mammography

Abstract

In contrast-enhanced digital mammography (CEDM) an iodinated contrast agent is employed to increase lesion contrast and to provide tissue functional information. Here, we present the details of a software phantom that can be used as a tool for the simulation of CEDM images, and compare the degree of anatomic noise present in images simulated using the phantom to that associated with breast parenchyma in clinical CEDM images. Such a phantom could be useful for multiparametric investigations including characterization of CEDM imaging performance and system optimization. The phantom has a realistic mammographic appearance based on a clustered lumpy background and models contrast agent uptake according to breast tissue physiology. Fifty unique phantoms were generated and used to simulate regions of interest (ROI) of pre-contrast images and logarithmically subtracted CEDM images using monoenergetic ray tracing. Power law exponents, β, were used as a measure of anatomic noise and were determined using a linear least-squares fit to log-log plots of the square of the modulus of radially averaged image power spectra versus spatial frequency. The power spectra for ROI selected from regions of normal parenchyma in 10 pairs of clinical CEDM pre-contrast and subtracted images were also measured for comparison with the simulated images. There was good agreement between the measured β in the simulated CEDM images and the clinical images. The values of β were consistently lower for the logarithmically subtracted CEDM images compared to the pre-contrast images, indicating that the subtraction process reduced anatomical noise.