Optimization of reconstruction strategies for head and neck computed tomography angiography using photon-counting computed tomography: A comparative study with energy-integrating detector computed tomography.
Abstract
Background
Head and neck computed tomography angiography (CTA) requires high spatial resolution while maintaining acceptable image noise. This study aimed to compare image quality between photon-counting CT (PCCT) and energy-integrating detector CT (EID-CT) and to evaluate PCCT reconstruction strategies for specific clinical imaging tasks.
Materials And Methods
This retrospective single-center study included 113 head and neck CTA examinations, comprising 60 PCCT and 53 energy-integrating detector CT (EID-CT) examinations. EID-CT images were reconstructed at 1.0 mm using the Bv40 kernel. PCCT datasets were reconstructed using the following strategies: 1.0-mm Bv40; 0.4-mm Bv44, Bv48, Bv56, and Bv60; and 0.2-mm Bv64 and Bv72. Quantitative image quality metrics included vascular attenuation, image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and vessel sharpness. Two neuroradiologists independently assessed qualitative image quality. Blooming artifacts were evaluated in the calcified plaque and stent subgroups.
Results
PCCT showed lower CTDIvol (23.3 ± 3.0 vs 26.2 ± 4.4 mGy), dose-length product (795.6 ± 113.0 vs 891.6 ± 159.3 mGy·cm), and effective dose (2.5 ± 0.4 vs 2.8 ± 0.5 mSv) than EID-CT (all p < 0.01). Thinner and sharper PCCT reconstructions improved vessel sharpness but increased image noise and reduced SNR and CNR. Subjective image quality remained high, with substantial inter-reader agreement (mean weighted κ, 0.759-0.819). Calcified-plaque blooming decreased from 0.35 ± 0.08 with 1.0-mm Bv40 to 0.22 ± 0.04 with 0.2-mm Bv72 (p < 0.01).
Conclusions
Under the evaluated clinical protocols, the PCCT group showed lower radiation exposure while maintaining high image quality compared with the EID-CT group. Different PCCT reconstruction strategies had distinct effects on image quality, suggesting that reconstruction selection should be tailored to specific clinical tasks by balancing spatial resolution and image noise.