Ultra-low-dose lung screening CT with model-based iterative reconstruction: an assessment of image quality and lesion conspicuity

Abstract

Background: Reducing radiation dose inevitably increases image noise, and thus, it is important in low-dose computed tomography (CT) to maintain image quality and lesion detection performance. Purpose: To assess image quality and lesion conspicuity of ultra-low-dose CT with model-based iterative reconstruction (MBIR) and to determine a suitable protocol for lung screening CT. Material and Methods: A total of 120 heavy smokers underwent lung screening CT and were randomly and equally assigned to one of five groups: group 1 = 120 kVp, 25 mAs, with FBP reconstruction; group 2 = 120 kVp, 10 mAs, with MBIR; group 3 = 100 kVp, 15 mAs, with MBIR; group 4 = 100 kVp, 10 mAs, with MBIR; and group 5 = 100 kVp, 5 mAs, with MBIR. Two radiologists evaluated intergroup differences with respect to radiation dose, image noise, image quality, and lesion conspicuity using the Kruskal–Wallis test and the Chi-square test. Results: Effective doses were 61–87% lower in groups 2–5 than in group 1. Image noises in groups 1 and 5 were significantly higher than in the other groups (P < 0.001). Overall image quality was best in group 1, but diagnostic acceptability of overall image qualities in groups 1–3 was not significantly different (all P values > 0.05). Lesion conspicuities were similar in groups 1–4, but were significantly poorer in group 5. Conclusion: Lung screening CT with MBIR obtained at 100 kVp and 15 mAs enables a ∼60% reduction in radiation dose versus low-dose CT, while maintaining image quality and lesion conspicuity.