Airway quantification using adaptive statistical iterative reconstruction-V on wide-detector low-dose CT: a validation study on lung specimen

Purpose To evaluate the accuracy of airway quantification of adaptive statistical iterative reconstruction (ASIR)-V on low-dose CT using a human lung specimen. Method A lung specimen was scanned on Revolution CT with low-dose settings (20 mAs, 40 mAs and 60 mAs/100 kV) and standard-dose setting (100 mAs/120 kV). CT images were reconstructed using lung kernel with eleven ASIR-V levels from 0 to 100% with 10% interval. ASIR-V level from 0 to 100% with 10% interval was reconstructed on lung kernel. Wall area percentage (%WA) and wall thickness (WT) were measured. Results Radiation dose of 20 mAs, 40 mAs and 60 mAs low-dose settings reduced by 87.6%, 75.2% and 62.8% compared to that on standard dose, respectively. Low-dose settings significantly decreased image SNR ( p < 0.05) and increased noise ( p < 0.001). ASIR-V level exponentially improved image SNR and linearly decreased image noise (all p < 0.001). The mean airway measurement ratios of low-dose to standard-dose were within 2% variation for %WA and within 3% variation for WT. Most %WA and WT values showed no obvious correlation with ASIR-V levels. Conclusion ASIR-V showed to improve image quality in low radiation dose. However, low-dose settings and ASIR-V strength did not significantly influence airway quantification values, although variation in measurements slightly increased with dose reduction.