Assessment of Image Quality Performance of a Photon-Counting Computed Tomography Scanner Approved for Whole-Body Clinical Applications

Abstract

Background: Photon-counting computed tomography (PCCT) represents a major technological advance in clinical CT imaging, offering superior spatial resolution, enhanced material discrimination, and potential radiation dose reduction compared to conventional energy-integrating detector systems. As the first clinically approved PCCT scanner becomes available, establishing a comprehensive characterization of its image quality is essential to understand its performance and clinical impact.

Methods: Image quality was evaluated using a commercial quality assurance phantom with acquisition protocols typically used for three anatomical regions-head, abdomen/thorax, and inner ear-representing diverse clinical scenarios. Each region was scanned using both ultra-high-resolution (UHR, 120 × 0.2 mm slices) and conventional (144 × 0.4 mm slices) protocols. Conventional metrics, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), slice thickness accuracy, and uniformity, were assessed following international standards. Task-based analysis was also performed through target transfer function (TTF), noise power spectrum (NPS), and detectability index (d') to evaluate diagnostic relevance.

Results: UHR protocols provided markedly improved spatial resolution, particularly in the inner ear imaging, as confirmed by TTF analysis, though with increased noise and reduced low-contrast detectability in certain conditions. CT numbers showed linear correspondence with known attenuation coefficients across all protocols.

Conclusions: This study establishes a detailed technical characterization of the first clinical PCCT scanner, demonstrating significant improvements in terms of spatial resolution and accuracy of the quantitative image analysis, while highlighting the need for noise-contrast optimization in high-resolution imaging.

Keywords: CT image quality; photon-counting detectors; task-based metrics.

Figure A1

Low-contrast module of the Catphan600 phantom shown for some of the acquired districts: (a) Head; (b) Abdomen; (c) Inner Ear at standard mode (144 × 0.4 mm); (d) Inner Ear at UHR (120 × 0.2 mm). Window/Level settings were chosen to achieve the best visibility possible of the low-contrast objects.

Figure A2

CTP404 module shown for the Inner Ear acquisitions: (a) standard (144 × 0.4 mm), (b) UHR (120 × 0.2 mm) acquisitions. The red arrow shows the polystyrene insert used for TTF calculation.

Figure 1

(a) 128 × 128 noise ROI for head protocol; (b) noise ROIs for all the analyzed thorax/abdominal protocols; (c) noise ROIs for all the analyzed inner ear protocols.

Figure 2

(a) HU distribution for head protocol; (b) HU distribution for abdomen protocol; (c) HU distribution for inner ear protocol.

Figure 3

Representation of NPS2D for (a) head, (b) abdomen, and (c) inner ear UHR. Axis ticks refer to the spatial frequencies in x–y directions.

Figure 4

(a) Comparison between standard and flash abdomen protocols; (b) NPS curves for two acquisition collimation widths (144 × 0.4 mm and 120 × 0.2 mm) in the inner ear protocol; (c) comparison between two reconstruction kernels (Hr68 and Hr72) at two different CTDIvol values for inner ear; (d) NPS for the head protocol.

Figure 5

(a) TTF curves for inner ear at 140 kV, 200 mAs comparing 144 × 0.4 mm and 120 × 0.2 mm collimation widths; (b) TTF curves for inner ear at 100 kV, 300 mAs comparing 144 × 0.4 mm and 120 × 0.2 mm collimation widths; (c) TTF curves for thorax/abdominal protocol; (d) TTF curves for thorax/abdominal protocol comparing standard and flash acquisitions; (e) TTF curves for the head protocol.

Figure 6

Linearity of the HUs vs. linear attenuation coefficients computed for the specific spectrum, for abdominal (a) and head (b) protocols.