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A phantom study using dual-energy spectral computed tomography imaging: Comparison of image quality between two adaptive statistical iterative reconstruction (ASiR, ASiR-V) algorithms for evaluating ground-glass nodules of the lung

Aims: To assess the image quality of the two adaptive statistical iterative reconstruction (ASiR and ASiR-V) algorithms for evaluating ground-glass nodules (GGNs) of the lung. Subjects and Methods: The chest phantom with ground-glass simulated pulmonary nodules was scanned by dual-energy spectral computed tomography (CT) using gemstone spectral imaging mode. The image was reconstructed with ASiR and ASiR-V from 0 (FBP) to 90% blending percentages, respectively. The average noise and signal-to-noise ratio (SNR) of reconstruction images were calculated. The data were statistically analyzed. Results: Compared with FBP, as the percentage of ASiR and ASiR-V increased from 10 to 90%, image noise reduced by 3.7%–45.2% and 14.1%–73.8%, respectively, and the SNR increased accordingly. There was significantly higher SNR value of ASiR-V images as the percentages of IR increased to 50% or greater, compared to those of ASiR. Subjective image quality scores of ASiR and ASiR-V improved significantly as percentage increased from 10 to 80% for ASiR and ASiR-V (peaked at 60% for both of them). Conclusions: Both ASiR and ASiR-V can reduce the image noise and improve the objective image quality for presenting pulmonary nodules on dual-energy spectral CT imaging compared with FBP. ASiR-V provided further image quality improvement than ASiR, and both ASiR and ASiR-V 60% had the highest image quality score.