Effect of radiation dose on quantification of the liver iron and fat fractions using dual-energy computed tomography and material decomposition
Year: 2025
Type: article
Abstract: Background: Studying the impact of radiation dose on dual-energy computed tomography (DECT) quantification of liver iron and fat is clinically valuable for assessing fatty liver and chronic liver disease. Our objective was to investigate the effects of different radiation doses on the liver iron and fat fractions quantified using DECT. Methods: Rat liver iron and fat models were prepared. The modelled liver iron concentrations (LICs) were 25.000, 12.500, 6.250, 3.125, 1.563, and 0 mg/mL. The modelled liver fat concentrations (LFCs) were 0.910, 0.546, 0.273, 0.091, and 0 g/mL. All samples were scanned using a DECT scanner in Gemstone Spectral Imaging mode using three different electron tube currents. Material decomposition and characterization were performed using Gemstone Spectral Imaging Viewer. The virtual iron concentrations (VICs) and virtual fat concentrations (VFCs) were measured on iron-water and fat-water bases. Bland-Altman analysis, Pearson's correlation analysis and one-way analysis of variance were performed to determine differences in the VIC and VFC between the groups using SPSS 20.0 software. Results: In the liver-iron model, the correlation coefficients between each LIC and VIC were 0.999, 1.000, and 0.999, respectively. The correlation coefficients between each LFC and VFC were all 0.999. There were no significant differences in the VIC or VFC between the three tube currents employed, although absolute measured VIC and VFC consistently differed significantly from LIC and LFC. Conclusions: Different radiation doses had no effect on iron or fat content quantification by DECT. It is feasible to quantify the liver iron and fat fractions using low-dose CT.
Institution: Peking University Shenzhen Hospital
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4416613410
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