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

Abstract

PurposeTo evaluate the accuracy of airway quantification of adaptive statistical iterative reconstruction (ASIR)-V on low-dose CT using a human lung specimen.MethodA lung specimen was scanned on Revolution CT with low-dose settings (20\xa0mAs, 40\xa0mAs and 60\xa0mAs/100\xa0kV) and standard-dose setting (100\xa0mAs/120\xa0kV). 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.ResultsRadiation dose of 20\xa0mAs, 40\xa0mAs and 60\xa0mAs 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\u2009<\u20090.05) and increased noise (p\u2009<\u20090.001). ASIR-V level exponentially improved image SNR and linearly decreased image noise (all p\u2009<\u20090.001). 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.ConclusionASIR-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.