Characterization of breast tissues in density and effective atomic number basis via spectral X-ray computed tomography

Differentiation of breast tissues is challenging in X-ray imaging because tissues might share similar or even the same linear attenuation coefficients . Spectral computed tomography (CT) allows for more quantitative characterization in terms of tissue density ( ) and effective atomic number ( ) by exploiting the energy dependence of . The objective of this study was to examine the potential of / decomposition in spectral breast CT so as to explore the benefits of tissue characterization and improve the diagnostic accuracy of this emerging 3D imaging technique. 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 ± 0.09, 7.03 ± 0.012, and 7.40 ± 0.10) and densities (0.90 ± 0.02, 0.96 ± 0.02, and 1.07 ± 0.03 g cm ) and can be better distinguished if both quantitative values are observed together.