Qualitative and quantitative image quality of coronary CT angiography using photon-counting computed tomography: Standard and Ultra-high resolution protocols.

Purpose: We aimed to identify the optimal reconstruction settings based on qualitative and quantitative image quality parameters on standard and ultra-high resolution (UHR) images using photon-counting CT (PCCT).
Method: We analysed 45 patients, 29 with standard and 16 with UHR acquisition, applying both smoother and sharper kernel settings. Coronary CT angiography images were performed on a dual-source PCCT system using standard (0.4/0.6 mm slice thickness, Bv40/Bv44 kernels, QIR levels 0-4) or UHR acquisition (0.2/0.4 mm slice thickness, Bv44/Bv56 kernels, QIR levels 0-4). Qualitative image quality was assessed using a 4-point Likert scale. Image noise (SD), signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated in both the proximal and distal segments.
Results: On standard resolution, larger slice thickness resulted in an average increase of 12.5 % in CNR, whereas sharper kernel led to an average 8.7 % decrease in CNR. Highest CNR was measured on 0.6 mm, Bv40, QIR4 images and lowest on 0.4 mm, Bv44, QIR0 images: 25.8 ± 4.1vs.8.3 ± 1.6 (p < 0.001). On UHR images, highest CNR was observed on 0.4 mm, Bv40, QIR4 and lowest on 0.2 mm, Bv56 and QIR0 images: 21.5 ± 3.9vs.3.6 ± 0.8 (p < 0.001). Highest qualitative image quality was found on images with Bv44 kernel and QIR level 3/4 with both slice thicknesses on standard reconstruction. Additionally, Bv56 with QIR4 on 0.2 mm slice thickness images showed highest subjective image quality. Preserved distal vessel visualization was detected using QIR 2-4, Bv56 and 0.2 mm slice thickness.
Conclusions: Photon-counting CT demonstrated high qualitative and quantitative image quality for the assessment of coronaries and stents.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024. Published by Elsevier B.V.)