Optimization of image quality and accuracy of low iodine concentration quantification as function of dose level and reconstruction algorithm for abdominal imaging using dual-source CT: A phantom study

Abstract

PurposeThe purpose of this study was to assess the impact of advanced modeled iterative reconstruction (ADMIRE) algorithm and dose levels on the accuracy of Hounsfield unit (HU) measurement, image noise and contrast-to-noise ratio (CNR) in virtual monochromatic images (VMIs) with low iodine concentrations, and the accuracy of iodine quantification. Materials and methodsA CT phantom was scanned with dual-source CT using abdomen-pelvis examination parameters at four dose levels: 5, 8, 11 and 20 mGy. Images were reconstructed using filtered-back projection (FBP) and ADMIRE levels 3 and 5 (A3-A5). HU accuracy was assessed calculating the root-mean-square deviation (RMSDHU). Image noise and CNR were computed on VMIs at 40/50/60/70 keV for 4 iodine inserts with 0.5, 1, 2 and 5 mg/mL concentrations. Accuracy of iodine quantification was assessed by the RMSDiodine and iodine bias (IB). ResultsThe RMSDHU decreased significantly as the dose levels increased compared to 5 mGy, except for 8 mGy with A3 (P = 0.380) and with A5 level (P = 0.945). Noise increased by 63.0 ± 3.0 (standard deviation [SD])% from 20 mGy to 5 mGy. Noise decreased significantly by -53.8 ± 0.9 (SD) % with A5 compared to FBP. The CNR decreased by -43.1 ± 6.5 (SD)% from 20 mGy to 5 mGy. It increased using ADMIRE, and as the ADMIRE levels increased. The RMSDiodine and IB decreased as the dose level increased, and this was similar for all reconstruction types. ConclusionADMIRE strongly improves image quality in VMIs and slightly improves HU accuracy but does not affect the accuracy of iodine quantification.