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Assessment of Image Quality Performance of a Photon-Counting Computed Tomography Scanner Approved for Whole-Body
Francesca Saveria Maddaloni1,2,3, Antonio Sarno1,2, Alessandro Loria3
1Department of Physics 'Aldo Pontremoli', University of Milan, 20133 Milan, Italy.
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.
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