  Spectral imaging is a method in medical x-ray imaging to extract information
about the object constituents by the material-specific energy dependence of
x-ray attenuation. Contrast-enhanced spectral imaging has been thoroughly
investigated, but unenhanced imaging may be more useful because it comes as a
bonus to the conventional non-energy-resolved absorption image at screening;
there is no additional radiation dose and no need for contrast medium. We have
used a previously developed theoretical framework and system model that include
quantum and anatomical noise to characterize the performance of a
photon-counting spectral mammography system with two energy bins for unenhanced
imaging. The theoretical framework was validated with synthesized images.
Optimal combination of the energy-resolved images for detecting large
unenhanced tumors corresponded closely, but not exactly, to minimization of the
anatomical noise, which is commonly referred to as energy subtraction. In that
case, an ideal-observer detectability index could be improved close to 50%
compared to absorption imaging. Optimization with respect to the
signal-to-quantum-noise ratio, commonly referred to as energy weighting,
deteriorated detectability. For small microcalcifications or tumors on uniform
backgrounds, however, energy subtraction was suboptimal whereas energy
weighting provided a minute improvement. The performance was largely
independent of beam quality, detector energy resolution, and bin count
fraction. It is clear that inclusion of anatomical noise and imaging task in
spectral optimization may yield completely different results than an analysis
based solely on quantum noise.
