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BackgroundImage quality of photon‐counting and energy integrating CT scanners changes with object size, dose to the object, and kernel selection.PurposeTo comprehensively compare task‐generic image quality of photon‐counting CT (PCCT) and energy integrating CT (EICT) systems as a function of phantom size, dose, and reconstruction kernel.MethodsA size‐variant phantom (Mercury Phantom 3.0) was used to characterize the image quality of PCCT and EICT systems as a function of object size. The phantom contained five cylinders attached by slanted tapered sections. Each cylinder contained two sections: one uniform for noise, and the other with inserts for spatial resolution and contrast measurements. The phantom was scanned on Siemens’ SOMATOM Force and NAEOTOM Alpha at 1.18 and 7.51 mGy without tube current modulation. CTDIvol was matched across two systems by setting the required tube currents, else, all other acquisition settings were fixed. CT sinograms were reconstructed using FBP and iterative (ADMIRE2 – Force; QIR2 – Alpha) algorithms with Body regular (Br) kernels. Noise Power Spectrum (NPS), Task Transfer Function (TTF), contrast‐to‐noise ratio (CNR), and detectability index (d’) for a task of identifying 2‐mm disk were evaluated based on AAPM TG‐233 metrology using imQuest, an open‐source software package. Averaged noise frequency (fav) and 50% cut‐off frequency for TTF (f50) were used as scalar metrics to quantify noise texture and spatial resolution, respectively. The difference between image quality metrics’ measurements was calculated as IQPCCT – IQEICT.ResultsFrom Br40 (soft) to Br64 (sharp), f50 for air insert increased from 0.35 mm−1 ± 0.04 (standard deviation) to 0.76 mm−1 ± 0.17, 0.34 mm−1 ± 0.04 to 0.77 mm−1 ± 0.17, 0.37 mm−1 ± 0.02 to 0.95 mm−1 ± 0.17 for PCCT‐T3D‐QIR2, PCCT‐70keV‐QIR2, and EICT‐ADMIRE2, respectively, when averaged over all sizes and dose levels. Similarly, from Br40 to Br64, noise magnitude increased from 10.86 HU ± 7.12 to 38.61 HU ± 18.84, 10.94 HU ± 7.08 to 38.82 HU ± 18.70, 13.74 HU ± 11.02 to 52.11 HU ± 26.22 for PCCT‐T3D‐QIR2, PCCT‐70keV‐QIR2, and EICT‐ADMIRE2, respectively. The difference in fav was consistent across all sizes and dose levels. PCCT‐70keV‐VMI showed better consistency in contrast measurements for iodine and bone inserts than PCCT‐T3D and EICT; however, PCCT‐T3D had higher contrast for both inserts. From Br40 to Br64, considering all sizes and dose levels, CNR for iodine insert decreased from 52.30 ± 46.44 to 12.18 ± 10.07, 40.42 ± 33.42 to 9.48 ± 7.16, 39.94 ± 37.60 to 7.84 ± 6.67 for PCCT‐T3D‐QIR2, PCCT‐70keV‐QIR2, and EICT‐ADMIRE2, respectively.ConclusionsBoth PCCT image types, T3D and 70‐keV‐VMI exhibited similar or better noise, contrast, CNR than EICT when comparing kernels with similar names. For 512 × 512 matrix, PCCT's sharp kernels had lower resolution than EICT's sharp kernels. For all image quality metrics, except extreme low, every dose condition had a similar set of IQ‐matching kernels. It suggests that considering patient size and dose level to determine IQ‐matching kernel pairs across PCCT and EICT systems may not be imperative while translating protocols, except when the signal to the detector is extremely low.

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.