Three-dimensional noise characteristics of clinical photon counting detector CT.

Background: Since the introduction of whole-body photon-counting detector CT (PCD-CT) into clinical practice, extensive physics assessments have been conducted to elucidate its image quality advantages over energy-integrating detector CT (EID-CT) and to support its clinical adoption. However, evaluations of its three-dimensional (3D) noise power spectrum (NPS), which simultaneously quantifies in-plane and through-plane noise texture and magnitude, remain limited.

Purpose: To experimentally evaluate the 3D NPS of an NAEOTOM Alpha PCD-CT system and its dependence on scan mode, reconstruction image type, quantum iterative reconstruction (QIR) strength, mono-energy (keV) level, spiral pitch, and radiation dose.

Methods: Repeated scans of a 20 cm water phantom and a 30 cm PMMA phantom were conducted under the clinical Standard mode, clinical Ultra-High-Resolution (UHR) mode, and an Expert Service mode. Reconstructed image types include T3D, virtual monoenergetic image (VMI), and T1 (a linear reconstruction of total-energy bin available via the Expert Service mode). Data were collected at seven dose levels (0.4-24 mGy) and four spiral pitch levels (0.35-1.5). T3D and VMI images were reconstructed with varying QIR strengths, and VMIs were reconstructed at energies ranging from 40 to 190 keV. The 3D NPS, $\mathrm{NP}{S}_{3D}\left(k_x,k_y,k_z\right)$ , was calculated from each ensemble of 3D image volumes. Axial $\mathrm{NP}{S}_{2D}\left(k_{xy}\right)$ ​ was obtained by integrating NPS_3D along $k_z$ , while $\mathrm{NP}{S}_{1D}\left(k_z\right)$ ​ was obtained by integrating NPS_3D over $k_x$ and $k_y$ .

Results: $\mathrm{NP}{S}_{1D}\left(k_z\right)$ ​ of T1 images were flat, indicating no noise correlation across PCD rows. In contrast, all clinical-mode reconstructions exhibited through-plane noise correlation, as reflected in the shape of their $\mathrm{NP}{S}_{1D}\left(k_z\right)$ . ​For clinical-mode reconstructions, the shape of their 3D NPS showed a mild to moderate dependence on dose, with lower doses producing NPS profiles shifted towards lower frequencies in both axial and z directions. With a matched post-object radiation exposure, the larger phantom resulted in higher noise and stronger noise correlation compared to the smaller phantom. QIR only mildly enhanced noise correlation. For a given CTDI_vol, spiral pitch has a negligible impact on 3D NPS. Due to through-plane noise correlation, the variance of T3D and VMI decreases with slice thickness ( $\Delta z$ ) approximately as $\Delta z^{-0.9}$ , in contrast to the $\Delta z^{-1.0}$ scaling observed in T1 images. The shape of the 3D NPS of VMI showed only weak dependence on the keV level along the axial frequency direction. Compared to the Standard mode, the UHR mode reduced image variance by 26% when using a soft-tissue (Br44) kernel and by 77% with a sharp (Br76) kernel. However, 3D NPS analysis revealed stronger through-plane noise correlation in UHR images.

Conclusion: The 3D NPS provides new insight into the noise characteristics of PCD-CT: Noise in the native PCD-CT projection data is uncorrelated across detector rows, but clinical reconstruction processes introduce noise spatial correlation along both axial and z directions, particularly at higher QIR strengths, lower radiation doses, or with larger image objects that increase the percentage of scattered photons. Compared to the Standard mode, UHR mode reconstruction exhibits stronger noise correlation due to its superior detector spatial resolution, allowing for more aggressive spatial smoothing to achieve the desired spatial resolution in the final image.