  Differentiation of breast tissues is challenging in X-ray imaging because
tissues might share similar or even the same linear attenuation coefficients
$\mu$. Spectral computed tomography (CT) allows for more quantitative
characterization in terms of tissue density and effective atomic number by
exploiting the energy dependence of $\mu$. In this work, 5 mastectomy samples
and a phantom with inserts mimicking breast soft tissues were evaluated in a
retrospective study. The samples were imaged at three monochromatic energy
levels in the range of 24 - 38 keV at 5 mGy per scan using a propagation-based
phase-contrast setup at SYRMEP beamline at the Italian national synchrotron
Elettra. A custom-made algorithm incorporating CT reconstructions of an
arbitrary number of spectral energy channels was developed to extract the
density and effective atomic number of adipose, fibro-glandular, pure
glandular, tumor, and skin from regions selected by a radiologist. Preliminary
results suggest that, via spectral CT, it is possible to enhance tissue
differentiation. It was found that adipose, fibro-glandular and tumorous
tissues have average effective atomic numbers (5.94 $\pm$ 0.09, 7.03 $\pm$
0.012, and 7.40 $\pm$ 0.10) and densities (0.90 $\pm$ 0.02, 0.96 $\pm$ 0.02,
and 1.07 $\pm$ 0.03 g/cm$^{3}$) and can be better distinguished if both
quantitative values are observed together.
