Model-based iterative reconstruction in ultra-low-dose pediatric chest CT: comparison with adaptive statistical iterative reconstruction

Abstract

PurposeTo evaluate image quality and dose reduction of ultra-low-dose pediatric chest CT reconstructed with model-based iterative reconstruction (MBIR), as compared with adaptive statistical iterative reconstruction (ASIR). Materials and methodsFifty-seven patients (mean age 14 years, M:F=31:26) who underwent ultra-low-dose chest CT reconstructed with both MBIR and ASIR were enrolled in the study. The subjective and objective image qualities of both reconstruction techniques were assessed by 3 radiologists, and compared using statistical analysis. We also evaluated radiation dose of ultra-low-dose chest CT as well as degree of dose reduction in comparison to the prior CT (either standard dose or reduced dose protocol) available in 36 patients. ResultsThe image quality of MBIR was superior to ASIR both subjectively and objectively. While MBIR showed preserved diagnostic acceptability in 100%, ASIR showed 92% at mean 0.31 mSv (range, 0.13–0.57 mSv) ultra-low-dose CT. In the 36 patients who underwent the prior CT, mean decrease in size-specific dose estimate (SSDE) and dose length product (DLP) at ultra-low-dose CT was 88% (range, 34% - 98%) and 86% (range,42% - 99%), respectively. ConclusionsMBIR significantly improves image quality, as compared to ASIR. Furthermore, MBIR facilitates diagnostically acceptable ultra-low-dose chest CT with nearly 90% less radiation.