Contrast-enhanced dual-energy digital subtraction mammography: optimization of the beam energy

Abstract

The implementation of contrast-enhanced dual-energy digital subtraction mammography may lead to better identification of breast tumors, and thus provide a lower cost and more widely available alternative to breast MRI. This technique involves the acquisition of low- and high-energy images after the IV administration of iodinated contrast agent. In this study, the effect of the beam energy (kVp) was examined using the <i>CNR²/dose </i>metric, where <i>CNR</i> is the contrast-to-noise ratio and dose implies the mean glandular dose. The mean glandular dose was calculated using parameterized normalized glandular dose coefficients (DgN), which allowed the computation of the mean glandular dose for the modeled spectra considered in this study, coupled with incident kerma measurements. Optimization studies were performed using a dedicated cone-beam breast CT scanner designed and fabricated in our laboratory, with the system operating in stationary imaging mode. A flat tissue-equivalent phantom (7.5 cm in thickness) was placed at the isocenter of the scanner, and an air gap of 34.5 cm was used in lieu of a grid. Dilute iodine-based contrast agent was introduced into the phantoms using plastic vials. Data were acquired from 40 to 90 kVp at 10 kVp intervals. Due to the low mA available on the breast CT system, a large number of images (1000) were acquired in fluoroscopic mode, which allowed us to match the dose and noise properties for each kVp combinations by changing the number of images used for averaging. Preliminary results demonstrate that the best <i>CNR2/dose</i> is achieved with a 50 kVp low-energy image and a 90 kVp high-energy image. Consequently, radiation doses for contrast-enhanced mammography should be far lower than regular mammography. Since the spatial resolution requirements should also be lower than regular mammography, dual-energy contrast-enhanced mammography, when performed using the optimal technique factor, may indeed provide very similar diagnostic information as breast MRI but at significantly reduced costs.