BackgroundQuantitative imaging techniques, such as virtual monochromatic imaging (VMI) and iodine quantification (IQ), have proven valuable diagnostic methods in several specific clinical tasks such as tumor and tissue differentiation. Recently, a new generation of computed tomography (CT) scanners equipped with photon‐counting detectors (PCD) has reached clinical status.PurposeThis work aimed to investigate the performance of a new photon‐counting CT (PC‐CT) in low‐dose quantitative imaging tasks, comparing it to an earlier generation CT scanner with an energy‐integrating detector dual‐energy CT (DE‐CT). The accuracy and precision of the quantification across size, dose, material types (including low and high iodine concentrations), displacement from iso‐center, and solvent (tissue background) composition were explored.MethodsQuantitative analysis was performed on two clinical scanners, Siemens SOMATOM Force and NAEOTOM Alpha using a multi‐energy phantom with plastic inserts mimicking different iodine concentrations and tissue types. The tube configurations in the dual‐energy scanner were 80/150Sn kVp and 100/150Sn kVp, while for PC‐CT both tube voltages were set to either 120 or 140 kVp with photon‐counting energy thresholds set at 20/65 or 20/70 keV. The statistical significance of patient‐related parameters in quantitative measurements was examined using ANOVA and pairwise comparison with the posthoc Tukey honest significance test. Scanner bias was assessed in both quantitative tasks for relevant patient‐specific parameters.ResultsThe accuracy of IQ and VMI in the PC‐CT was comparable between standard and low radiation doses (p < 0.01). The patient size and tissue type significantly affect the accuracy of both quantitative imaging tasks in both scanners. The PC‐CT scanner outperforms the DE‐CT scanner in the IQ task in all cases. Iodine quantification bias in the PC‐CT (−0.9 ± 0.15 mg/mL) at low doses in our study was comparable to that of DE‐CT (range ‐2.6 to 1.5 mg/mL, published elsewhere) at a 1.7× higher dose, but the dose reduction severely biased DE‐CT (4.72 ± 0.22 mg/mL). The accuracy in Hounsfield units (HU) estimation was comparable for 70 and 100 keV virtual imaging between scanners, but PC‐CT was significantly underestimating virtual 40 keV HU values of dense materials in the phantom representing the extremely obese population.ConclusionsThe statistical analysis of our measurements reveals better IQ at lower radiation doses using new PC‐CT. Although VMI performance was mostly comparable between the scanners, the DE‐CT scanner quantitatively outperformed PC‐CT when estimating HU values in the specific case of very large phantoms and dense materials, benefiting from increased X‐ray tube potentials.

Objective. Differentiation of breast tissues is challenging in X-ray imaging because tissues might share similar or even the same linear attenuation coefficients μ. Spectral computed tomography (CT) allows for more quantitative characterization in terms of tissue density (ρ) and effective atomic number (Zeff) by exploiting the energy dependence of μ. The objective of this study was to examine the potential of ρ / Zeff 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. Approach. 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. Main results. 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. Significance. 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/cm3) and can be better distinguished if both quantitative values are observed together.

No abstract