Abstract
Objectives
To evaluate the application of different tube voltages and image-reconstruction algorithms in paranasal-sinus computed tomography (CT) and optimizes the scanning protocols for paranasal-sinus CT while balancing between image quality and radiation dose.
Methods
Ninety patients were randomly divided into three groups (A, B, and C). Group A used conventional scanning parameters: tube voltage of 120 kVp, tube current uDose level 1, and the Karl iterative reconstruction algorithm. Groups B and C used tube voltages of 100 and 80 kVp, respectively, and tube current uDose level 1. The Karl iterative reconstruction algorithm and artificial intelligence iterative reconstruction (AIIR) algorithm were used. Optimal image reconstruction noise levels were selected for each group, and the image quality and radiation doses of the best images were statistically analyzed.
Results
The best image reconstruction noise levels for Groups A, B, and C were Karl level 5, AIIR level 5, and AIIR level 4, respectively. The signal-to-noise ratio, contrast-to-noise ratio, figure of merit, and subjective score values of the images in Groups B (AIIR level 5) and C (AIIR level 4) were higher than those in Group A (Karl level 5). The patients from Groups B and C had the CT dose-index volume, dose-length product, and size-specific dose estimate based on the water-equivalent diameter that were 68.86%, 71.76%, 69.84%, 84.39%, 85.95%, and 85.50% lower, respectively, than those of Group A (P < 0.001).
Conclusions
A low tube voltage combined with the AIIR algorithm effectively improves image quality and decreases the radiation doses for patients undergoing paranasal-sinus CT. The optimal parameters for paranasal-sinus CT are 80 kVp, uDose level 1, and AIIR level 4.
Keywords
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